When Microsoft and Qualcomm launched the first Copilot+ PCs sporting Snapdragon X Elite processors, the CPU performance was beyond reproach, but whether due to immature software or underwhelming integrated hardware, the GPU horsepower left a lot to be desired. The easiest way to solve that is to hook up a discrete GPU, of course, but nobody's managed that yet. Instead, an enterprising hacker in China has become the first person to publicly get an Nvidia GeForce RTX GPU running on an Arm-based platform using Windows 11, but it's not Snapdragon, and it's not an Nvidia CPU, either, WindowsLatest reports.

We knew that the Nvidia RTX Spark processors used an integrated GPU directly derived from Nvidia's Blackwell technology, and we also knew that those machines would run Arm Windows 11, so this was bound to happen sooner or later, because that necessarily means that there is an Nvidia client graphics driver for Arm-based Windows 11 out there. That's exactly what "VoidTech" on BiliBili used for his experiment, though the experiment wasn't without some pitfalls.

Specifically, VoidTech got an Nvidia GeForce RTX 4060 8GB graphics card working in a Huawei Qingyun W510 workstation. This machine does not have a Snapdragon processor, of course; Huawei makes its own CPUs, and indeed this chip is the Kunpeng 920, created by Huawei's HiSilicon division. This chip was considered a major milestone when it was introduced in 2019, as it's a 7nm server CPU with up to 80 cores, although the specific implementation in the Qingyun W510 has "only" 24 cores.

All those cores don't help it much in gaming. As PC gamers will be well aware, CPU gaming performance is basically down to single-threaded CPU performance and system memory latency. The custom TaiShan v110 cores in the Kunpeng 920 only offer up around a sixth of the single-core performance of something like a Ryzen 9 9700X, at least going by Passmark, with the usual caveats that apply to Passmark. Combined with relatively small caches and a DDR4 memory interface that's clearly tuned for throughput, not latency, and you have a recipe for middling gaming performance. That's before we even start talking about x86 emulation penalties.

So did it work? Well, more or less. Actually, the GeForce RTX 4060 did about half of its job flawlessly, running advanced games like the Unreal Engine 5-based Black Myth Wukong and slightly less advanced games (Genshin Impact), as well as various 3DMark tests. Most software seemed to work without any issues aside from overall weak performance due to the slow Kunpeng 920 CPU; the Wukong benchmark finished at 21 FPS, while Genshin Impact struggled to break 25 FPS and stuttered frequently. However, Arknights: Endfield refused to launch, likely due to an incompatibility between its restrictive "Anti-Cheat Expert" package and the Prism translation layer required to run the x86 Windows games on Arm Windows.

The half of its job that the RTX 4060 didn't do was that VoidTech wasn't actually able to get a video signal out of the graphics card. He notes that the graphics card was recognized, and the monitor was picked up, too. He simply couldn't get the system to properly push pixels to the monitor. This likely comes down to the Nvidia Arm driver being built specifically for the RTX Spark and thus missing the necessary code to support the HDMI and DisplayPort encoders on desktop graphics cards. To get around this issue, VoidTech used the Sunshine game streaming server and the Moonlight game streaming client (on another system) to run the Huawei machine headlessly. A janky solution to be sure, but it does seem to have worked.

There's a bit more to the video, including how VoidTech had a hard time getting Windows 11 to boot on the machine at all due to broken ACPI tables, some frustration with missing Windows 11 drivers for the HiSilicon Network Subsystem (HNS), a bit where he runs a Blender Cycles render on the GeForce RTX 4060, and a couple of Nvidia RTX demos including the Star Wars "Reflections" demo that was shown with the introduction of the RTX 20 Series "Turing" GPUs. It's an interesting saga of making hardware that was never meant to work together run on an operating system that none of it supports.

This does somewhat bode well for RTX Spark. While you probably shouldn't expect the Cortex-X925 CPU cores in the RTX Spark to outpace the latest AMD or Intel CPUs due to still being forced to pay the Prism penalty, they're going to be a damn sight faster than this seven-year-old workstation chip. Since the drivers seem to be in good shape, the consumer laptops should indeed offer capable gaming performance when they arrive later this year—at least, as long as your game doesn't have kernel-level anti-cheat

Nvidia first debuted DLSS 5 earlier this year to a strong, critical response. The upscaling tech was almost slammed by some press and enthusiasts for overstepping its boundaries and going too far with AI.

At the time, Nvidia reassured the community that DLSS 5 would preserve artistic intent and CEO Jensen Huang even went as far as to claim that gamers didn't understand it. Now, at SIGGRAPH, the company has once again showcased DLSS 5, and it admittedly looks different this time around.

The main takeaway is the introduction of three different models with varying levels of detail and impact on performance. A game doesn't need to be confined to a single model the whole time; instead, developers can choose to employ different models for different scenes. Individual elements of scene, such as the characters versus the world, can also be fine-tuned in respect to how much DLSS touches them up (or not at all).

Then, you have the liberty to switch between the models in real time without incurring latency. DLSS 5 uses a combination of techniques to take the original rendered frame and apply effects on top, going beyond just upscaling the image. These days, DLSS, FSR, and XeSS are mandatory parts of the equation, acting as the preferred anti-aliasing solution in modern titles, and helping in other areas like ray tracing.

The upscaling part works conventionally and is still responsible for dictating the foundational blocks of the image, like lighting and geometry. The part that was so heavily criticized is therefore optional, as it only comes into play after the original rendered frame has been upscaled. However, it's unclear whether developers (or you) can actively choose to not process the frame through the beautification features.

Nvidia outlined three main challenges that the company faced when developing DLSS 5, some of which is probably reactionary after the initial reveal. The first challenge is preserving the original creative vision, which we already explained. The second challenge was to handle one frame at a time, which generative AI models don't — they process multiple frames together. That means DLSS 5 shouldn't negatively affect response times.

The third and final challenge pertains to the optimization of DLSS 5. The slides shown at SIGGRAPH say the model can run on a single GPU and that it's "VRAM efficient." For context, last time we saw it running on two RTX 5090s. Nvidia did not say whether it still needs the highest-end Blackwell gaming GPU to work properly. The company is promising real-time 4K performance thanks to a more compact model that has learned from a larger diffusion model.

DLSS 5 is building up to be a significant step for upscaling tech just when we thought AMD was finally catching up. However, many people may still worry about artistic intent, even if the new demos look a lot more polished and mature. We'll have to see what happens when it finally releases. There is no official release date for DLSS 5, but it should launch during Q3 2026 as Nvidia continues to tweak the models and its parameters based on community feedback.

Nvidia's upcoming Vera Rubin platform, set to arrive later this year, will take the stage as the AI world shifts towards an era dominated not by frontier training runs but by the demands of agentic AI inference at massive scale. The hunger for generated tokens in agentic workflows and the demands of delivering them quickly, efficiently, and at low unit cost now dominate the discussion.

We’ve already gone in depth on new performance data around the Vera CPU and how it helps to accelerate agentic AI workloads, but that’s not all Nvidia is sharing today. It’s also detailing some new features of the Rubin architecture and how those features are meant to increase inference efficiency from the GPU level to rack-scale and data-center-scale implementations of this accelerator platform.

The full Vera Rubin NVL72 rack-scale system is built up from 36 Vera CPUs and 72 Rubin GPUs, but our focus today is on the GPU proper. Rubin joins two compute dies onto a single package using the Nvidia High Bandwidth Interface. The resulting chip offers 224 Streaming Multiprocessors (SMs) containing a total of 896 Tensor Cores alongside 288GB of HBM4 memory providing 22 TB/s of memory bandwidth.

As an inference-focused accelerator, Nvidia touts Rubin’s 50 sparse PFLOPS of NVFP4 inference throughput as its headline performance figure, although that’s only one of a dizzying array of data types this chip can handle. Here are some key rates to keep in mind for this chip so far:

Let’s dive into some of Rubin’s refinements for inference workloads to understand how Nvidia aims to keep all of those resources fully utilized.

The Rubin Tensor Memory Accelerator efficiently manages growing MoE models

First up, Nvidia highlights efficiency improvements in the Tensor Memory Accelerator (TMA) that help feed the Tensor Cores with data. The TMA is a dedicated engine built to handle memory address calculations and perform direct loads of array data into a GPU's shared local memory.

Leading AI model architectures have moved from dense models where every parameter is activated per output token to a mixture-of-experts (MoE) architecture where only certain specialized sub-networks are activated per token, based on the guidance of a router that helps judge which experts are best suited to processing a given input.

MoE expert weights can be distributed across GPUs in order to efficiently utilize limited per-GPU HBM capacity. Nvidia says that Rubin's TMA has been improved to deal with the challenges of managing the growing numbers of experts in today’s leading models.

The TMA in Blackwell GPUs needed to maintain separate MoE descriptors in memory for the location of every expert, meaning that the overhead of locating and moving those expert weights requires more compute resources as the number of experts grows.

The Rubin TMA now supports GPU kernels that maintain and update a single unified MoE descriptor directly in the TMA instruction at runtime, reducing computation of MoE descriptor metadata and requiring less calculation overhead for data movement. This approach frees up GPU cycles for inference calculations, which is, of course, the place that you want your expensive AI accelerator spending the vast majority of its time.

Doubled K-dimension throughput, double the Tensor Core output

Rubin also improves the fundamental performance of matrix operations in the Tensor Core by doubling the amount of work those cores can perform on the K dimension, or the shared inner dimension of a pair of matrices to be multiplied. Without going too deep into the math, the size of the K dimension is directly related to the number of times the Tensor Core has to loop over the elements of the two matrices being multiplied.

In Nvidia's example, then, the calculation of a result matrix that would require four loop iterations on Blackwell can be completed in only two on Rubin. Nvidia says this improvement has wide-ranging benefits for throughput-, memory-, and latency-bound kernels, and it’s helpful for both context processing and decode phases of inference.

Softmax on Rubin gets up to a 4X boost versus Blackwell

Rubin also focuses on improving the performance of the attention mechanism that’s foundational to transformer-based LLMs More advanced models now support context lengths of up to a million tokens, and quickly performing attention calculations on such long input sequences quickly is a key driver for improved inference performance.

Softmax is an essential operation in attention calculations, and in order to keep up with the improved Tensor Core throughput in Rubin, Nvidia has once again boosted softmax throughput in the GPU SM’s Special Function Unit (SFU).

Since it relies on the transcendental math capabilities of the SFU, softmax throughput can become a bottleneck for subsequent inference work, and it's a limitation that Nvidia already sought to address with enhancements to the Blackwell Ultra SFU. Blackwell Ultra doubled FP32 and BF16/FP16 exponential throughput compared to the first-gen Blackwell GB200.

Rubin maintains Blackwell Ultra's 2X speedup over Blackwell in FP32 exponential math, and it doubles BF16/FP16 exponential calculations again compared to Blackwell Ultra, leading to a 4X improvement in throughput compared to Blackwell for those lower-precision data types.

Finer-grained dependency management, better Tensor Core occupancy

Rubin also increases Tensor Core occupancy by providing finer-grained opportunities for coordination between dependent kernels than on Blackwell. One case that Nvidia cites where these dependencies arise is the generation of activations for an LLM, where one kernel produces and stores data that is then used by a subsequent kernel as a prompt proceeds through a neural network.

On Blackwell GPUs, a long-running producer kernel on one thread block (perhaps within a CUDA structure like a cluster) might delay the execution of a subsequent consumer kernel on those thread blocks, even as other thread blocks of the producer kernel have finished their work.

Rubin offers finer-grained dependency resolution between kernels, such that a consumer kernel can begin executing on individual thread blocks as soon as the producer kernel’s output from each thread block becomes available, instead of waiting for the entire batch of producer kernel data to become available. This finer-grained management results in better GPU utilization, lower kernel-to-kernel latency, and ultimately increases tokens per second per user.

More efficient inter-GPU communication, lower NVLink overhead

All of the improvements we've discussed so far relate to how work happens on one GPU, but the Vera Rubin NVL72 rack-scale accelerator comprises many GPUs connected over an NVLink fabric within the rack. Model weights, key-value cache data, and inter-GPU synchronization messages all move over this fabric, so keeping overhead and latency low is key to realizing maximum performance.

GPUs running CUDA kernels can directly initiate communication with other GPUs in the rack using Nvidia Collective Communications Library (NCCL) API, lowering overhead. Nvidia notes that because the GPU performs those operations directly as part of the compute kernel, the efficient execution of those communications becomes critical to performance.

On a Blackwell system, an NVLink transfer between GPUs might require data store operations followed by a memory barrier and an atomic flag. The Rubin architecture introduces a feature called counted writes that reduces the amount of coordination and synchronization traffic necessary to share data between GPUs across the fabric.

On Rubin, the memory barrier and atomic operations are replaced by a single write counter update on the receiving GPU, reducing network traffic and latency and improving compute utilization by reducing the time spent waiting for coordination overhead.

All told, in tandem with the high single-threaded performance of the Vera CPU for agent harnesses, tool calling, code compilation, and more, the improvements in the Rubin GPU for performance on critical inference operations, as well as improved efficiency for data movement on-chip and across the rack, promise to help create a rack-scale and data-center-scale system that will both increase inference performance and lower per-token inference costs in the increasingly agentic future that Nvidia envisions. We’re excited to see more of what this GPU can do as deliveries of Vera Rubin systems are set to begin this fall.

Nvidia’s Vera CPU is its first bid to become a key player in the data center CPU market. Although Grace has seen some success (most notably with Grace standalone deployments at Meta), Vera is Nvidia’s first CPU with a custom core design. It’s arriving at an ideal time, as well, with the server CPU market exploding in the last few months on the back of agentic AI demand.

Vera isn’t a chip built to chip away at the market share of AMD and Intel in the cloud. It’s built to grab market share in an expanding market, as hyperscalers look to widen AI infrastructure beyond legacy clouds. As such, it’s designed in a much different way than Nvidia’s x86 competitors, and it even holds some unique architectural design points compared to the swath of Arm-based designs.

Nvidia has slowly revealed more details about Vera as it ramps into general availability, which is on track for the back half of this year. Now, we have a full picture of the chip. Nvidia shared its Vera white paper, along with unofficial SPEC CPU 2026 results comparing Vera to AMD’s Turin-based Epyc 9755.

We’re going to break down the white paper here, including all of the details about the Olympus core and a look at the benchmarks Nvidia ran. At the end of this piece, we’ll also take a brief look at the larger context of Vera and how it fits into Nvidia’s wider AI ecosystem compared to standalone deployments.

But plenty of ink has been spilled about Vera’s technical capabilities and Nvidia’s next-gen AI infrastructure vision. Let’s start with the important thing: the benchmarks.

Nvidia Vera CPU benchmarks

We’ve seen Vera in action before, though only through a series of selected benchmarks ran at Nvidia HQ by Phoronix. In the Vera white paper, Nvidia shared benchmarks for SPEC CPU 2026, specifically the integer suite from SPECrate, against AMD’s Epyc 9755, with both chips running in a dual-socket configuration. Before getting into the results, there are some important notes about how SPEC runs work, and the reporting criteria for them.

Nvidia’s run here isn’t official, as Vera was tested in a reference system due to the fact that it’s not broadly available yet. It’s ramping for general availability in the second half of the year. Due to that, Nvidia is unable to report its results. That’s why you see “estimated” in some of the charts below. Nvidia ran SPEC CPU 2026; it’s not extrapolating expected performance like we’ve seen from AMD so far with its upcoming Venice chips.

SPEC CPU 2026 is split into four suites, but Nvidia tested the SPECrate integer suite, which is focused on system throughput with integer-based workloads. The “rate” result is looking at how much work is completed within a certain amount of time. Here, each thread in the system has a copy of the workload. The score is how much time it takes for those workloads to complete, regardless of thread count, naturally giving chips with more cores an advantage.

If you want more detail on the benchmarks included in the suite, make sure to read our original coverage of SPEC CPU 2026. Here are the overall results:

Nvidia didn’t share the exact results for the 9755 it tested, short of the overall score of 898. Taking that overall score into account, Vera is 3% ahead of the 9755. It’s worth noting that Vera is ahead here despite a large thread disadvantage. An overall score of 898 for a dual-socket Epyc 9755 system isn’t unreasonable compared to publicly-submitted SPEC CPU 2026 runs, though higher results have been published. SPEC CPU ships as source code, which the tester must compile with their compiler of choice, and that can heavily influence results (particularly with vendor-specific compilers). Nvidia used GNU 15.2 with both systems.

Above, you can see Vera’s results stacked up against the 9755, but these aren’t comparing the numbers directly. Nvidia has normalized the per-core performance, which isn’t how SPECrate results are normally shared. According to the overall numbers, Vera is still completing more work within the same amount of time, despite a thread disadvantage, but the margins aren’t in the range of a 70% or 80% advantage as the above chart suggests.

We asked Nvidia about the results given that they're obfuscated by comparison; we could not reverse-engineer the Epyc 9755's scores with the information Nvidia has provided. Here's the response it gave: "Per-core performance under a fully loaded socket is important because agentic AI and RL run many sandboxes concurrently, while each agent step remains sequential and latency-sensitive. It measures how much performance each core sustains amid contention for shared power, memory, cache, and fabric. We therefore normalize by physical core, with SMT enabled on both systems."

The “agentic” workloads Nvidia has highlighted here are code compilation and interpretation workloads, which is something an agent is often doing, querying repos for dependencies and building source code. Below are data science workloads (or Exploratory Data Analysis), and below that are data processing workloads like SQLite database management. The results here align with Nvidia’s overall messaging of Vera, that it’s highly competent at data-rich, backend operations.

Although Nvidia is sharing per-thread results, it argues that SPECrate is still the correct benchmark to run. The per-thread results here are in the context of a fully-loaded socket. Here’s the justification from the white paper: “This metric is non-trivial for agentic AI and RL systems, where many sandboxes, tools, and environments run concurrently rather than as isolated single-thread tests. Fully loaded per-core performance captures how well each core sustains throughput while sharing socket-level power, memory bandwidth, cache, and fabric resources.”

In addition to running the workloads, Nvidia analyzed the code execution for architectural benchmarks, which you can see in the gallery above. Nvidia claims an overall IPC gain of up to 1.9x compared to Turin, up to 2.3x more branch predictions and 3.5x taken branches per cycle, and up to 2.4x higher instruction fetch operations per cycle.

Outside of SPEC, Nvidia shared a few benchmarks highlighting the capabilities of the Olympus core. First up is PageRank, an algorithm developed by Google to originally rank web pages, which highlights Olympus’ prefetch engine. Nvidia scaled this workload to higher core counts, showing Vera maintaining much of its single-core performance up to 32 cores, while the Turin chip hits a wall around 20 cores.

In addition to the above results, Nvidia shared some tests of the Vera memory system compared to Turin. These microbenchmarks are good for validating Nvidia’s specifications, but they’re looking at architectural performance, not application performance. An architectural advantage translates into a performance advantage, but not always in a linear, expected fashion.

Nvidia used internally-developed tools for the memory tests, though they're available on GitHub for anyone to run.

First is loaded memory latency, stressing the memory subsystem as bandwidth usage increases. Vera has much higher bandwidth overall, but you can see the Turin chip hit a latency wall below its maximum, which Nvidia attributes to Non-Uniform Memory Access (NUMA) domain traversal and CCD-to-CCD latency.

Looking at per-core bandwidth, Nvidia claims Vera provides more than four times the bandwidth of AMD’s 9755. The suggestion here is that “real-world” per-core bandwidth is even better than Nvidia’s specs lead on (or perhaps worse than AMD’s).

Maybe the most consequential of these tests is the one you can see above, looking at core-to-core latency. It’s no secret that crossing the CCD on AMD’s chiplet-based architecture incurs a big latency penalty. You can see that in action even in our Ryzen 9 9950X3D2 review, and the penalties compound as you scale up the number of CCDs.

In fairness to AMD here, chiplet-based designs aren’t built for this type of cross-CCD traversal, preferring to keep workloads localized and optimizing for core density. Vera’s design goal is clearly to keep latencies consistent across the entire die and sacrificing core density in the process. Nvidia’s Ian Buck told us that this design trade-off “will come at the cost of the legacy workload,” when we recently visited Nvidia HQ.

That’s important context. Nvidia isn’t gunning to steal existing market share from AMD and Intel as much as it’s trying to grab market share in an expanding market before AMD and Intel can. Some financial institutions (including Morgan Stanley and Bank of America) suggest the server CPU market could double in size (or grow even larger) by 2030. That context is important because there will be a continuing demand for CPUs that can handle workloads Vera is not optimized for, and it’ll be interesting to see how AMD and Intel tackle that dynamic with future products, trying to keep a legacy base of customers while pushing ahead into the expanded market.

Nvidia clearly has a vision of how that expanded market looks, and to that end, hasn’t shared SPEC CPU floating point results. Presumably, this is due to the fact that SPEC’s vectorized suite is focused primarily on HPC workloads, whereas Nvidia focused on what it believes are critical agentic workloads that are integer-based. Vera has a vector engine complete with SVE, but that doesn’t seem like Nvidia’s focus.

In an end-to-end Nvidia system, those vectorized workloads would be offloaded to a Rubin GPU. Still, we don’t have any vector results for Vera yet. Up to this point, we’ve only seen integer results, which is strange given the memory system at play in Vera.

Vera is Nvidia’s first CPU with a core design created in-house, which is the Olympus core. It’s built on Arm v9.2-A, but the design was created by Nvidia, unlike Grace, which leveraged a stock Arm design. Each Vera CPU has 88 Olympus cores on a monolithic die, breaking from the chiplet-based designs available from Nvidia’s x86 competitors.

Nvidia says Vera comes with a 1.5x increase in instructions per cycle (IPC) throughput compared to Grace, and 50% higher performance compared to x86 competitors (it seems that number is per-thread performance with a fully-loaded socket). Nvidia has a single 88-core design with Vera that supports spatial multithreading for 176 threads.

The CPU has a configurable TDP range of 250W to 450W. It uses a SOCAMM2 LPDDR5X memory system with capacity of up to 1.5 TB and speeds up to 9600 MT/s, and comes with 164 MB of L3 cache and 2 MB of L2 per core. Vera includes significantly less L3 than Intel’s highest-specced Xeon 6 and AMD’s Zen 5 chips. It actually has more L2 than L3 overall. This, presumably, is due to Nvidia’s fabric, which distributes the L3 in a mesh across the monolithic die.

Below, you can see a layout of the Olympus microarchitecture. Nvidia has disclosed some of the highlights of the architecture previously, such as the 10-wide instruction decode and neural branch predictor, but we now have a full view of the architecture courtesy of Nvidia’s Vera white paper.

The front end starts with Nvidia’s neural branch predictor that can run two branches per cycle “with zero penalties,” according to Nvidia. Research on neural branch prediction dates back to the late 90s, but Nvidia says it has a “novel” neural branch predictor, perhaps building on previous research such as BranchNet.

The BPU feeds into the Instruction Fetch Unit, which holds 64 KB of L1 instruction cache, and loads into a decode queue that supports 48 instructions (we’ll go into the memory/cache layout later). At the last stage of the front end is that 10-wide decode, feeding more instructions into the execution engine per cycle than the 8-wide decode in AMD’s Zen 5 microarchitecture.

Past the front end, the mid-core rename / allocation engine is built to keep instructions moving while waiting on dependencies. In addition to renaming and allocation, instructions work through value prediction, which can speculatively execute the instruction, and memory renaming, where the instruction can move forward while a load is happening if the data relationship can be determined.

Inside the execution engine, Nvidia includes eight simple Arithmetic Logic Units (ALUs), two complex ALUs, and four branch units for resolution. For SIMD instructions, the execution engine includes a vector cluster for Arm’s Scalable Vector Extension (SVE), including six vector units that support 128-bit SVE instructions at FP8 precision, along with two crypto-enabled vector units that can handle AES, SHA, and SM3, among other prominent algorithms. Keeping data moving through the engine are four load units and two store units.

The cores support spatial multithreading, giving a Vera CPU with 88 cores access to 176 threads. Traditional SMT time-slices execution, giving both threads access to all of the core resources and sharing them as instructions execute in parallel. With spatial multithreading, each thread of an Olympus core has access to dedicated resources, allowing one of the threads to execute with high-throughput while the other thread handles simple tasks, or to operate as two independent execution environments.

The execution resources are partitioned, explaining the wide decode front end. It’s not clear, however, if the SMT implementation can also opportunistically grab resources, particularly in the scenario Nvidia describes where one of the threads is maximizing throughput while the other handles smaller tasks.

There’s a lot going on in Vera between the 10-wide decode, neural branch predictor, and spatial multithreading, but perhaps the most significant architectural design point is Nvidia’s second-generation Scalable Coherency Fabric (SCF). It underpins Nvidia’s approach of using a monolithic die as opposed to a chiplet-based design, distributing last level cache in a mesh across the die and avoiding the cross-CCD latency penalty with localized L3.

The mesh distributes data through a series of Coherency Switch Nodes (CSNs) that serve as routing points between cores and the 164 MB of distributed L3. These routing points further connect the cores and L3 to the memory system, I/O, and NVLink C2C for cache-coherent communication between chips. Nvidia’s benchmarks comparing Vera to AMD’s Epyc 9755 show that AMD can achieve slightly lower core-to-core latencies within a cluster, but Vera maintains significantly better core-to-core latency across the die, as expected.

Nvidia says SCF inside Vera has 3.4 TB/s of bandwidth, enabling faster core-to-core communication, especially when traversing the die. However, Vera also supports Memory System Resource Partitioning and Monitoring (MPAM), allowing portions of L3 to be partitioned in multi-tenant environments.

Vera uses SOCAMM2 LPDDR5X, which is a relatively new advancement that Nvidia’s competitors haven’t had the chance to benefit from. With the use of SOCAMM2, LPDDR5X provides similar modularity and capacity as traditional RDIMMs, but at significantly lower power draw.

The memory can run at up to 9600 MT/s, with aggregate bandwidth of 1.2 TB/s and per-core bandwidth of 14 GB/s, doubling the bandwidth of Grace. The Vera board supports eight SOCAMM2, offering capacity ranging from 256 GB to 1.5 TB. Nvidia claims a “fully populated” memory subsystem consumes between 30W and 40W depending on capacity.

For I/O, Vera supports PCIe 6.4 with 88 lanes per CPU and bifurcation support down to x2. It also supports CXL 3.1.

Unlike Grace, Vera includes Arm’s Confidential Computing Architecture (CCA) and Realm Management Extension (RME), including Device Assignment and Coherent Device Assignment, offering a boon to multi-tenant environments where VM isolation is key. Nvidia also implements TDISP for coherent devices, allowing for encrypted communication between GPUs and PCIe devices.

Nvidia is already sampling Vera as a standalone chip to partners, and it says it will continue to do so, but the vision is an end-to-end solution built on Nvidia’s CPUs, GPUs, switches, NICs, and even rack specifications. Nvidia doesn’t make all of these individually, at least not at scale — just like with desktop graphics cards, Nvidia provides its MGX reference design, which customers can purchase, but partners also offer their own racks, some built solely to Nvidia’s specifications and others with more speciality.

Each tray comes with two Vera Rubin superchips, each of which contain a single Vera CPU to two Rubin GPUs, giving you two CPUs and four GPUs per tray. At the front, Nvidia partitions off three spaces, with the MGX design carrying two NVIDIA ConnectX-9 SuperNIC on either side and a Bluefield 4 DPU in the middle. Critically, this design doesn’t include any hoses or fans. It’s entirely liquid cooled, and it contains just two cables throughout the entire tray.

Nvidia demonstrated this cable-less design, showing the Vera Rubin Superchip sliding in and out of the track with a retention mechanism in a matter of seconds. The company says assembling the rack takes less than a few minutes and is handled entirely by robots, which is a far cry from GB200 and GB300 trays.

GB200 and GB300 trays are dense designs, but they’re also cluttered with cables and hoses. Nvidia says this massively slowed down production time, eventually leading to production issues that delayed Nvidia’s rollout. The company says that won’t happen with Vera Rubin and its largely cable-less design. Whereas a Grace Blackwell tray took around two and a half hours to assemble by a human, the company says a Vera Rubin tray is assembled within five minutes and entirely automated by robots.

Each tray needs to dissipate several kilowatts of heat, which Nvidia says it’s able to do using dry cooling. Liquid cooling is nothing new in the data center, either through an external chiller (essentially an A/C unit) or evaporation, where a fan evaporates water over a mesh and cools without the need for a compressor. With Vera Rubin, Nvidia uses “dry cooling,” with a maximum inlet temperature of 45 degrees Celsius.

Nvidia says it’s able to get the full performance out of a tray given an inlet temperature of 45 °C, allowing trays to operate without an additional water consumption in environments up to 100 degrees Fahrenheit. The tray essentially uses a large closed-loop similar to what you find from a consumer AIO, just scaled up. Water moves out of the tray and outside the data center, and it passes through a radiator where fans dissipate the heat. There’s some extra power consumption from water pumps and fans, but not nearly on the scale of evaporation methods or chillers.

The result is a tray completely free of fans, essentially noise-less in operation, and doesn’t strain local water infrastructure. That’s what Nvidia says, at least. In many locations around the U.S. where data centers are located (Texas and Virginia chief among them), temperatures easily climb above 100 °F during the Summer, prompting some sort of backup method of cooling. Nvidia says the external temperature ceiling can go higher depending on different factors — running at lower power, for example, and using more efficient heat exchangers — but under normal conditions, 100 °F is the ceiling.

It’s worth noting that nothing about a Vera Rubin tray explicitly requires this method of dry cooling; the hardware is just capable of offering full performance with an inlet temperature of 45 °C.

In addition to an NVL72 design, Nvidia has a Vera standalone deployment that compacts each tray into a series of SOCAMM2 slots and Vera chips. In Nvidia’s 48U MGX design, a standalone Vera deployment can include up to 256 CPUs in a rack.

Underpinning scale-up communication is Nvidia’s sixth-generation NVLink, which is deployed as switches in the rack and connected to compute trays using Nvidia’s NVLink spine. You can see the spine on its own in the image above, which features over two miles of thin copper wire to allow every tray in the rack to communicate with each other.

Localizing storage, networking, security, and telemetry operations is Nvidia’s BlueField-4 DPU. A Vera Rubin NVL72 compute tray includes a single DPU and two ConnectX-9 NICs to maximize CPU/GPU utilization. You can read more about Bluefield 4 in our original coverage from GTC.

Nvidia’s Ian Buck, vice president of hyperscale and high-performance computing and the inventor of CUDA, says the company has “shipped... let's put it in the hundreds of thousands of Grace standalone servers.” In May, Nvidia disclosed that it had shipped over 2.5 million Grace CPUs in total, and the company announced a partnership with Meta to deploy standalone Grace servers in February. Buck’s comments suggest the scale of deployment may be even larger, however, as Nvidia tries to compete in a market dominated by other players.

It’s an interesting comment, though not a surprising one. Nvidia has become the dominating force of Silicon Valley as demand for its GPUs skyrocketed during an unprecedented data center buildout for AI inference. Since peaking earlier this year, however, around $1 trillion in Nvidia’s market cap has been wiped away as investors rally behind CPU makers like Intel. Evolving agentic AI workloads have changed the hardware balance, shifting away from as many as eight GPUs per CPU, toward a one-to-one ratio in some cases.

Nvidia wants to ride that train with its new Vera CPU, which was architected specifically for those types of workloads. Even before the recent rise of agents, however, Nvidia says it has seen demand for its CPUs for data-hungry workloads. “They weren’t running a web server [with Grace]… or they aren’t being used for, what the cloud uses, of cheap, dollar-per-core,” Buck said. “They were being deployed for the backend, data-rich operations, like the data processing.”

Grace represents an on-ramp for Nvidia into data center CPUs. It uses 72 stock Arm Neoverse V2 cores, but it’s differentiated by Nvidia’s Scalable Coherency Fabric (SCF). Vera uses an updated SCF, but it also features Nvidia’s first custom core design, called Olympus. Grace cracked the door, and Vera represents Nvidia's big entrance into the market against AMD and Intel.

Regardless of where Vera ends up in the battle of next-gen data center CPUs — which is heating up now, as AMD is expected to launch its Zen 6 Venice CPUs this week — the design is vastly different from what we’ve seen out of Intel and AMD. Most notably, Vera is monolithic, placing all of its 88 cores on a single piece of silicon. AMD and Intel, years ago at this point, pivoted away from monolithic dies in favor of chiplets, allowing an extremely high density of cores at the cost of latency and coherency issues. Vera is radically different in that regard, not only being built on a single die, but also dedicating significant die space to the fabric.

“One of the reasons we don’t have 128 cores is because we’ve dedicated so much of the die area toward the fabric,” Buck said. “It’s 3.4 TB/s of bandwidth inside of that CPU that is dedicated toward allowing every core to talk to every cache, every memory [controller] at full speed without any collisions.”

For clarification’s sake, Buck is referencing 3.4 TB/s of core-to-core bandwidth in Vera. There’s up to 1.2 TB/s of aggregate memory bandwidth (14 GB/s per core) through the LPDDR5X interface.

But just as chiplet-based designs made trade-offs in per-thread performance, Vera will likely make trade-offs for its unique architecture. The majority of data center workloads are still “legacy” tasks that hyperscalers have built for, and even with seemingly insatiable demand for AI infrastructure, that is unlikely to change for several years.

Buck recognizes this trade-off, asking: “Can Intel and others build rich fabrics? Do they have the IP and the ecosystem to do it and connect it all the way through to LP memory? They need to tell you when they’re going to do it… but that trade-off will come at the cost of the legacy workload.” Earlier this year, at GTC in March, Buck was even more clear. “The world is not going to be served by one SKU of CPU, and that is not our intention,” the executive said in a news conference at the time.

Still, it’s clear Nvidia has ambitions with data center CPUs beyond what headlines are floating around on the New York Stock Exchange. Nvidia says CPUs represent a $200 billion TAM (Total Addressable Market) opportunity for the company, a rather rosy forecast compared to the rest of the industry, which sees a TAM of around $120 billion by 2030 (though recent estimates have climbed as high as $170 billion). And agentic AI is expanding that market, with Morgan Stanley in April estimating that agents could add as much as $60 billion to the data center CPU market.

Vera is in full production alongside Nvidia’s next-gen AI infrastructure, including Rubin GPUs, ConnectX-9 NICs, SpectrumX Ethernet switches, and the various components that go into building a Vera Rubin NVL72 rack. The company says there are around 1.3 million components that go into a rack, and it has a list of over 300 partners globally to build them. As part of our visit to Nvidia HQ last week, we saw a Vera Rubin NVL72 rack in action, running workloads for OpenAI.

Our local AI testing in 2026 has focused on large language models that can fit entirely into the 128GB of unified memory on Nvidia GB10 and AMD Strix Halo systems. Useful as those smaller open models can be, there is sometimes no replacement for displacement. Today, we’re exploring what’s possible from a local AI cluster with a pair of Nvidia GB10 systems, namely Dell’s Pro Max with GB10 (henceforth Pro Max), which gives us 256GB of RAM for a local AI sandbox.

Quantizing an AI model from higher-precision to lower-precision data types involves tradeoffs for performance and accuracy. And even in quantized form, some advanced open models are still too large to fit within 128GB. But those models can be distributed across multiple local systems using the network as a scale-out backbone, just as they are in the data center.

Why scale out GB10 systems (or Strix Halos, or Macs)? Local token factories with large VRAM pools built up from discrete GPUs can get crazy, fast. Scaling one to even 128GB of VRAM requires a costly host system with enough PCI Express slots and bandwidth to feed those cards, and going beyond 128GB means spending $20K or more in Nvidia GPUs at a minimum, even if you're building up from older 48GB Ada cards.

The preferred recipe for this kind of setup typically includes a Threadripper Pro or Epyc platform, which means a costly CPU, motherboard, and DDR5 kit even before you start adding graphics cards. The power requirements for such a system can quickly get beyond the capabilities of a standard USA 15A circuit (1,800W maximum).

And having four discrete GPUs running their blower fans at high speeds under load, along with whatever other active cooling you might need for what is essentially a GPU server, is not going to make for the most pleasant company if you’re sharing a space with it.

While a GPU server with four RTX Pro 5000 or RTX Pro 6000 cards is useful for getting the absolute best performance for a given application, those potentially high costs, platform challenges, and quality of life concerns have led local AI enthusiasts to explore other ways of achieving large local memory pools with acceptable LLM inference performance, like the GB10 cluster we’re building today.

Nvidia made the DGX Spark and its Spark-alikes scalable, cluster-able systems right out of the box thanks to their built-in ConnectX 7 200Gbps NICs. These high-end interfaces support Remote Direct Memory Access over Converged Ethernet, or RoCE, so two (or more) GB10 boxes can use them as the backbone for a distributed AI computing cluster.

We didn't have multiple Sparks to test RDMA clustering during our initial review, but Dell sent us a pair of Pro Max GB10 systems along with the QSFP cables necessary to join them together.

These systems still aren’t anywhere near cheap, but at $6332 each as of the time of this writing for the tested configuration with 4TB SSDs, you can build a complete, turn-key cluster with 256GB of RAM for less than the cost of the four 48GB or 72GB GPUs you’d need to scale a similar GPU server build.

If you need to save cash and can trade off absolute performance in the bargain, there’s no cheaper way to get into big local models right now, period, but especially not with the level of networking performance that the DGX Spark platform offers.

Dell’s Pro Max with GB10 closely follows the Spark template, but it adds an extremely handy power LED to the front panel that the DGX Spark lacks, and the hexagonal grilles on the front and rear panels doesn't catch on clothes or microfiber cloths like the metal foam front and rear panels of the DGX Spark do.

Dell also provides a large 280W USB-C power adapter with each Pro Max GB10 system, or 40W more capacious than the adapter included with the reference DGX Spark. However, there’s nothing to suggest this system has a higher TDP or clocks than the reference Spark design as a result.

Dell does drop the Pro Max with GB10 back to a PCIe Gen 4 SSD compared to the launch DGX Spark’s Gen 5 drive, but it appears that the ongoing NANDpocalypse has forced Nvidia to source Gen 4 drives for its reference systems to keep costs down, so we’re not holding this decision against Dell here.

Setting up

We’ve already covered the DGX Spark reference design in its own review, so if you’re unfamiliar with the basics of this platform, we’d suggest reading that coverage first. We’ll keep the focus today on the specific challenges and hurdles of clustering two of these systems together.

While the ConnectX 7 NIC on these systems supports both Infiniband and Ethernet protocols in its add-in card form, Nvidia has stated on its official DGX Spark forums that GB10 systems exclusively support Ethernet, and therefore, RoCE for clustering. Don’t buy multiples of these systems hoping to connect them through any Infiniband switches you might have lying around.

The ConnectX 7 NIC on the Spark and Spark-alikes like the Dell Pro Max is also connected to the GB10 SoC in a somewhat weird way due to some possible platform limitations. In short, the largest PCIe bus width one can apparently get off GB10 is a PCIe 5.0 x4 link, so to achieve 200Gbps on any one QSFP port, the two x4 links to the ConnectX 7 have to be teamed behind any one physical port. As a result, each physical port on the NIC is presented to the system as two logical interfaces.

To achieve the full 200Gbps bandwidth available from the ConnectX 7, you have to configure your networking topology carefully. Nvidia has a Spark playbook on how to do this, and the spark-vllm-docker project also offers its own guide on how to set up these interfaces. I’d recommend following them closely unless you have good reason to roll your own configuration.

After connecting my Dell Pro Max boxes together using the same QSFP cages on their back panels, configuring their network interfaces according to the spark-vllm-docker guide above, configuring passwordless SSH on my second node, and running the recommended NCCL bandwidth test on the link, I found that I was only getting a small fraction of the expected RDMA bandwidth, despite both boxes reporting that they were fully up to date through the DGX Dashboard app.

Community wisdom suggested that a firmware version mismatch was to blame, so I verified that the head Pro Max node in my cluster was fully up to date, both through the DGX Dashboard app and through the command line using the apt package manager.

But even though the DGX Dashboard reported that my second Pro Max system was fully up to date, running the recommended command-line apt checks revealed that there was an update for the fwupd package stuck behind a phasing fence, so I force-installed it.

Once this forced update was complete, it unlocked a new round of firmware updates for the second Pro Max, which I dutifully applied. After rebooting both systems and re-running the recommended NCCL bandwidth tests, I was finally getting something approaching the full 25GB/s one would expect from a proper 200Gbps link.

While none of the issues I had getting my Pro Max GB10 systems clustered were show-stopping, it's also far from a plug-and-play experience. But once both systems were settled in, I didn't see the bandwidth over the ConnectX 7 ports drop back to the degraded performance levels I first observed, even across multiple reboots of the cluster.

Cluster management and performance

If you're thinking about clustering Sparks, you want an inference engine that can handle tensor parallelism, or the distribution of model weights across GPUs during computation. vLLM is an easy choice for doing this on the DGX Spark platform thanks to actively maintained community tools like spark-vllm-docker and sparkrun, but you can also achieve these results with SGLang if that’s your platform of choice.

The spark-vllm-docker project comes with several handy scripts that make starting the cluster and distributing models across it easy, and the sparkrun project provides similar functionality. We focused on spark-vllm-docker for this round of tests, but you have options in this space if you want to explore them.

With our inference engine settled, we went off in search of an advanced model that would utilize a decent chunk of the 256GB of VRAM available from our cluster.

DeepSeek v4 Flash is one such model. It’s a 284-billion-parameter mixture of experts model with 18 billion active parameters per token, and it claims to support a context window of up to 1 million tokens. (vLLM gave us a 400K-token cap on this setup). spark-vllm-docker offers a prebaked vLLM recipe for it, so we downloaded it, deployed it across our cluster, and got to benching.

The DeepSeek v4 Flash vLLM recipe we used takes advantage of this model’s built-in multi-token prediction capabilities, so decoding throughput remains essentially the same even as time to first token climbs with context lengths up to 200K+ tokens, or about 333 pages of A4 text. That’s impressive and usable performance for a model of this size and capability.

We also loaded up CyanKiwi’s four-bit quantization of MiniMax M2.7. This is another large mixture-of-experts model with 230 billion total parameters and 10 billion active parameters, and it supports a context window out to 200K tokens, which is exactly what vLLM gave us after initialization on our Spark cluster.

This model doesn’t have the built-in MTP advantage of DeepSeek v4, so even with the four-bit quantization we used for this test, its time-to-first-token and tokens-per-second throughput follow a more familiar curve. Throughput starts in a relatively usable range, but falls off quickly as we approach the limits of the context window.

Our experience running DeepSeek v4 Flash and MiniMax 2.7 shows that even though a Spark cluster isn’t fast, it can still produce enough tokens per second to be a useful sandbox with these demanding models.

Power and thermal notes

As we discussed in our intro, a major advantage of a cluster like this is that it doesn’t require exotic power and cooling to run, and you also don’t have to banish it to a garage or server closet to keep it quiet.

Imeasured peak wall power draw of about 375W to 415W across my cluster during inference performance testing, which is just a bit higher than the TGP of a single RTX 5080 without its host system.

That figure bodes well for adding even more Spark-alikes to a local cluster if you need to, as even four of them running all-out are likely to need less than 1kW from a circuit (before any outboard networking gear is factored in, at least).

Noise levels from my dual Dell Pro Max setup under load were also well controlled, measuring about 40 dBA at 18 inches away. If you need to keep these systems in an inhabited office space or cubicle, they’ll be perfectly tolerable to be around.

If you’re expanding beyond two GB10 systems, I’d guess that any 200G/400G networking gear that you’d need to throw into the mix will likely be far louder than even four of these systems under load, as it’s likely built for a server closet, not a continuously inhabited space.

Bottom line

If you're a local LLM trailblazer and need more VRAM for large, capable models, and don't want to fiddle with or don’t have the cash for a from-scratch GPU server build with more than 128GB of memory, the Dell Pro Max with GB10 cluster we’ve built here exemplifies how clustering Nvidia GB10 systems is a straightforward, space-efficient, low-power, low-noise, and relatively cost-effective way to scale up your local AI sandbox beyond 128GB of VRAM.

"Relatively" is doing a lot of work here because a pair of Dell Pro Max with GB10 boxes as tested here rings in at $12,664 right now, plus another $50 for the QSFP cable you'll need to hook them together. For organizations or institutions with departmental budgets to spend and existing Dell accounts and support contracts to work within, that dollar figure is likely secondary to the ROI on whatever proposal might drive a purchase order.

But for individuals who just want to build a bigger AI sandbox in their home lab and don't have those relationships to worry about, it's still possible to construct a similar cluster with Asus's Ascent GX10 from stock for under $10K, even at current prices. And as we explained in the intro, going above 128GB of local memory by using multiple discrete GPUs will cost you far more than such a cluster, even before you factor in the cost of a host system.

Not everybody needs to connect multiple Sparks, of course, but if that possibility does intrigue you, the ConnectX 7 NIC in every GB10 box means that there isn't a cheaper way to achieve a 256GB (or larger) distributed memory pool with this class of networking performance behind it.

Some AMD Strix Halo mini-PCs offer PCIe slots for expansion, but they're limited to PCIe 4.0 x4 speeds, so even the funky teamed PCIe 5.0 x4 links to the ConnectX 7 NIC inside GB10 boxes means you're getting far higher potential RDMA bandwidth than you would from adding an aftermarket NIC to a Strix Halo system.

Even though Apple's Mac Studio briefly enjoyed a turn in the spotlight as a cluster-friendly alternative for local AI thanks to the massive memory pools and high bandwidth available from Apple Silicon, along with RDMA over Thunderbolt 5, that star has dimmed, as the company no longer offers memory options larger than 64GB with M4 Max Studios or 96GB with M3 Ultra models. And the lead times on either of those systems are currently over three months out, which is an eternity in the rapidly evolving local AI market.

So Nvidia sort of has this field to itself right now, as GB10 boxes remain readily available from stock with 128GB of RAM at prices that aren't completely bonkers. And if you're a novice to distributed computing concepts, the active community, actively developed tools, and ecosystem software support around GB10 systems are all invaluable for getting your AI cluster running quickly. All that makes Dell’s Pro Max with GB10 (and other Spark-alikes) hard to beat for building a big local AI sandbox to experiment with.

A PC gamer has DIYed a passive Nvidia GeForce RTX 4060 graphics card system. Perhaps unhappy with the Palit GeForce RTX 3050 KalmX 6GB still being the pinnacle of commercial passive graphics cards in 2026, Bilibili user NexFrame (h/t Fanless Tech) has bolted a hulking finned aluminum heatsink onto an RTX 4060.

NexFrame appears to be a small or up-and-coming ‘brand’ with a penchant for passive PC systems, from what we can understand from their Bilibili bio (machine translation). Unfortunately, we don’t have a lot of information about this passive 5.5-pound (2.5kg) aluminum heatsink-wearing RTX 4060, like whether it is tuned to run cooler than a standard model for fanless operation.

Squinting at the Bilibili video source, a system monitor window seen towards the end of the video appears to show that the GPU is running in a gaming scenario at 58C, with a 71C hotspot. Meanwhile, the graphics fan is running at 0 RPM, which seems accurate. However, the modder doesn’t seem to be taking it easy on the GPU. Further down the system info screen, we see the GPU reportedly pulling 198W. A standard actively cooled RTX 4060 would consume far less than that under load, more like 115W to 120W, so some data must be mangled here, or being misreported.

Elsewhere in the images shared by NexFrame, we can see that the CPU is also being cooled passively. It looks like a hexacore Intel CPU has been combined with a Noctua NH-P1 Passive CPU cooler. This commercial passive cooler was capable of keeping a CPU consuming up to 75W cool and stable enough over extended periods during our review testing. The system monitor tool overlaid on NexFrame’s game testing session shows the CPU sipping between 35 and 50W.

Passively cooled PCs are of interest to a significant number of enthusiasts for eliminating what is typically the noisiest component of a modern PC – fans. In a standard gaming PC, there will be fans built into the CPU cooler, on the GPU shroud, in the PSU, and also arranged at strategic places around the case. Even so-called liquid cooling systems usually rely on their CPU or GPU contact heatsinks being attached to an array of fans cooling a radiator in the case. Just think how blissfully peaceful your computing experience could be if all these moving parts were eliminated.

It is now possible to monitor every thermal aspect of Nvidia’s GeForce RTX 50-series (codenamed Blackwell) products, renowned for being some of the best graphics cards you can buy. Thanks to the efforts of Overclock.net (OCN) member asder00, users can now monitor the temperatures for each memory module on Blackwell graphics cards in addition to the recently exposed hotspot sensor.

Nvidia grants direct access to the company's graphics cards and drivers through Nvidia API (NVAPI). Game and software developers employ NVAPI for a range of advanced features. Developers of monitoring tools, specifically, leverage NVAPI to retrieve real-time thermal sensor data so users can keep a close eye on their graphics card's conditions.

While there is a world of information through NVAPI, there are certain sensor readings that Nvidia intentionally kept hidden from developers. Yet, Nvidia's safeguards have not stopped resourceful enthusiasts from discovering creative workarounds to tap into the previously inaccessible sensors. Skilled modders recently managed to gain access to the hotspot sensor, which was only available on internal Nvidia tools like MODS, and now collaboration within the community has enabled individual memory module monitoring.

The new plugin, aptly named Hotspot.dll, is specifically for MSI Afterburner. It exists because MSI Afterburner is software from MSI, an Nvidia partner, so it cannot legally poll sensor data not officially made available through NVAPI. Nevertheless, third-party software solutions such as AIDA64 and HWiNFO are not bound by the same partner agreements and will likely add the functionality for individual memory module monitoring the same way they previously adopted support for the hotspot sensor. The latest beta version (v8.51-6304) of HWiNFO already has the function and had no issues reporting the temperature of all 16 of the GDDR7 memory modules inside our GeForce RTX 5090.

While asder00 developed the plugin, it is important to highlight that it is part of a collective effort. The list of contributors to the breakthrough includes Alexey “Unwinder” Nicolaychuk, the developer behind MSI Afterburner; olealgoritme, known for his work on the open-source Linux GDDR6/GDDR6X temperature reader; Brazilian hardware modder Paulo Gomes; and Martin “Mumak” Malík, the creator of HWiNFO.

The Hotspot.dll plugin reveals the GPU hotspot temperature, die thermal channel readings, average die temperature, GPU memory junction temperature, and per-chip DRAM thermal data. It is compatible with GDDR6, GDDR6X, and GDDR7 memory modules, so it works with the entire Blackwell product stack from the GeForce RTX 5050 to the GeForce RTX 5090. While the original focus of the development was Blackwell, it should work on previous generations of GeForce RTX graphics cards, including the GeForce RTX 40 (codenamed Ada Lovelace) and GeForce RTX 30 (codenamed Ampere) series.

Access to these new sensor readings opens a new level of transparency and control for Nvidia graphics card owners. They will be very beneficial for those who want to fine-tune their graphics card to maximize performance or those who are diagnosing problems.

AMD is expected to refresh both its desktop and mobile lineups with Zen 6 next year. Ryzen AI 500 series, codenamed Medusa Point, will be the company's next-gen mobile family and we've already seen a 10-core part leak from it a couple of times. Now, that same SKU is back with another Geekbench listing, this time posting its best results that put it ahead of any mobile chip currently made by Intel or AMD (in one way).

AMD's upcoming chip ended up scoring 3,329 points in the single-core test and 16,555 points in the multi-core test. The Geekbench page once again shows the platform name as "AMD Plum-MDS1," which we've known to be associated with Medusa Point for a while now. The SKU is listed as "AMD Eng Sample 100-000001713-33_N," which is identical to how we saw in the last leak, basically confirming we're looking at the same chip.

The single-core result is almost 5% higher while the multi-core score is about 9.7% higher compared to the numbers we saw previously. In fact, the single-core result is better than any mobile part on Geekbench apart from the new Snapdragon X2 Elite lineup. Compared to desktop equivalents, it's very close to the 9900X and the 9800X3D — two absolute desktop powerhouses carrying 12 cores and 8 cores, respectively.

The multi-core score puts this 10-core SKU right alongside the Ryzen AI Max+ 390, which is just a tier below the top-end AI Max+ 395 from Strix Halo. Since this is a 10-core part, we can infer it's the Ryzen AI 9 565 because the Ryzen AI 9 365 (from Strix Point) and Ryzen AI 9 465 (from Gorgon Point) share the same configs. The Ryzen AI 9 365 has an average score of 12,410, so Medusa Point's offering is 33% faster in this regard.

The Geekbench listing also reports the correct clock speeds this time — 2.0 GHz is still lasted as the base frequency, but the boost frequency is marked at 5.37 GHz, which makes a lot more sense. Moreover, the listing shows 10MB of L2 cache and 32MB of L3 cache while the Ryzen AI 9 465 had a combined cache tally of 34MB.

Overall, this benchmark is an incredibly promising showing for Medusa Point. The Red Team's next-gen mobile lineup seems to benefit heavily from an architectural jump thanks to the Zen 6 silicon. Keep in mind that this is the company's mainstream mobile offering that's supposed to compete with Intel's Panther Lake, while Nova Lake mobile and AMD's own Gator Range (Ryzen 10000) will serve only as high-end CPUs.

The Zilog Z80 has just turned 50 years old. This iconic 8-bit processor first went on sale in July 1976 and stayed in production for 48 years until Zilog, now a Littelfuse subsidiary, stopped accepting orders in June 2024. However, there’s an open-source replacement closer than ever to shipping in the chip’s original 40-pin DIP package thanks to community-funded fabrication.

The original Z80 packed 8,500 transistors on a 4μm process and typically ran at 2.5 MHz, with later CMOS variants reaching 20 MHz. Binary compatibility with the Intel 8080 let it absorb the existing CP/M software base, with an on-die DRAM refresh counter that cut the number of support chips a system needed. Development of working prototypes cost roughly $400,000 against $500,000 in funding from Exxon, per the Computer History Museum.

The chip powered the ZX Spectrum, TRS-80, MSX machines, Nintendo's Game Boy, Sega's Master System, the Pac-Man arcade cabinet, and Texas Instruments' graphing calculators, then shipped in industrial controllers for decades after home computing moved on to more powerful successors. Zilog's end-of-life notice, dated April 15, 2024, told customers its wafer foundry was discontinuing support for the Z84C00 family, and last-time-buy orders closed that June.

However, Renaldas Zioma's FOSS Z80 project, launched shortly after the end-of-life notice, now has working silicon. The first version, fabbed on SkyWater's 130nm node through Tiny Tapeout 7 on a die of just 0.064mm², has been confirmed as functional via the project’s GitHub repository. A QFN64 version with all 40 pins exposed followed on the Efabless CI2406 shuttle, two further runs then went through IHP's 130nm process, and the current run targets the classic DIP40 form factor using chip-on-board assembly on GlobalFoundries' 180nm GF180MCU node via Wafer.Space. The end goal here is to fab a drop-in replacement for machines like the ZX Spectrum and RC2014 kits.

The design is built around Guy Hutchison's TV80 Verilog core, and the project's Tiny Tapeout page says the 130nm CMOS implementation should support clocks up to 50 MHz, against 4 MHz for the original NMOS part.

Zilog is trimming the Z80's official successor line as well. A product change notification from last October put the eZ80L92, along with several Z8F-series microcontrollers, on end-of-life, citing "little to no demand." Last-time-buy orders closed on January 20 this year, with shipments scheduled through April 20, on non-cancelable, non-returnable terms. The eZ80L92 is the only eZ80 part named in the notice; the pipelined eZ80 architecture, introduced in 2001 and still inside TI's current TI-84 Plus CE calculators, otherwise remains in Zilog's catalog.

Hobbyists keep finding work for the original chip regardless. For example, earlier this year, a developer ran a tiny conversational AI on a Z80 with 64KB of RAM.

An engineering student has demonstrated a piece of music being played via coil whine. In the PC world, this electronic noise pollution is usually an unwanted side effect from running high-performance components at full pelt. However, keen electronic DIYer Battery Potato has videoed an inductor coil playing a catchy chip tune.

Sorry I don’t recognize the tune being played. It sounds like it could be a classic Nintendo Game Boy game music track, but almost anything played through a coil may sound like that.

Many of you will have bought or built a high-performance PC that is afflicted with components that produce audible coil whine. In my long computer tinkering history, I only remember two coil whine emitting components: a Zotac RTX 4080, and a (recent) lesser-known Chinese brand NVMe SSD. Other components that might have noisy coils are PSUs and motherboards.

Coil whine is an audible phenomenon that occurs when inductors (and sometimes capacitors) vibrate in response to rapidly changing electrical loads. For PC enthusiasts this can be maddening if you have what is otherwise a pleasingly quiet machine. PCs most often exhibit coil whine when you are hitting very high frame rates (GPU) or transferring oodles of data files (SSD). It is usually a high-pitched audible effect, so coil whine can be particularly bothersome to those who can hear high-pitched sounds clearly and are sensitive to them.

Battery Potato, an electrical engineering student at Nagaoka University of Technology, has sought to make coil whine a feature instead of an electronics bug. You can see from the video that a simple toroidal inductor has been constructed, and the electronics DIYer is running current through it. Perhaps this simple homebrew inductor was chosen for this ‘music’ project as it produced clearer sound than off-the-shelf components. A modulated current waveform is likely being fed directly to the coils to make them 'sing' as intended.

The OCCT stress tester introduced musical coil whine last year

The above story of music being squeezed out of a coil whine noisescape isn’t unprecedented. Last October we reported on stress tester OCCT version 15 release, which included a coil whine detection tool that can output "three pre-defined tunes."

The OCCT devs reasoned that pushing components with a coil whine pattern that has musical characteristics would help users more easily recognize the issue. It especially helps listeners pick out actual coil whine in noisier environments.

AMD launched the Ryzen 7 7700X3D a couple of days ago to universal acclaim, with reviews praising its consistently excellent gaming performance while critiquing the price point. It's officially priced at $329, which is just shy of what the Ryzen 7 7800X3D goes for these days, rendering the newest X3D chip a bit pointless. However, thanks to a new promo code on Newegg, you can purchase it for as low as $279 right now.

• Get the Ryzen 7 7700X3D on Newegg

Just add the CPU to your cart, and at checkout, the promo code "PKC337" will be automatically applied to give you a $49 discount. That should bring the price down to just $279 before tax. At that price, the Ryzen 7 7700X3D suddenly becomes much more feasible thanks to its improved value proposition. Now, there's at least $120 separating the Ryzen 7 7700X3D from the Ryzen 7 7800X3D, freeing up money you can put toward other upgrades.

For context, both chips are essentially the same; you can look at the Ryzen 7 7700X3D as the binned-down version of the Ryzen 7 7800X3D silicon that couldn't be used for the more expensive SKU. Both are 8-core, 16-thread parts with 104MB of combined cache and 120W TDPs. The Ryzen 7 7700X3D can boost up to 4.5 GHz, while the Ryzen 7 7800X3D has a 5 GHz boost clock. That's enough to just barely edge the Ryzen 7 7700X3D in gaming performance.

On the other hand, if you're looking for an all-rounder that also excels in professional workloads, then Intel's latest Arrow Lake refresh chips are better. Both the Core Ultra 5 250K Plus and the Core Ultra 7 270K Plus are faster at productivity tasks than the Red Team's offerings in the same class. But now that there's a clear price distinction among them, the Ryzen 7 7700X3D makes sense if you're just gaming.

The Ryzen 7 7700X3D is also a Newegg exclusive in North American markets till Q4 2026 so it makes sense that the retailer can discount it this quickly. The Ryzen 7 7800X3D is also on sale, but it has not received any promo codes on the site as of now. So, if you're looking to finally jump on the X3D train and on the AM5 socket, but don't want to spend over $300, this is your chance to grab the Ryzen 7 7700X3D for as low as $279.

TrashBench recently decided to test whether adding more and more fans to what used to be one of the best graphics cards would improve its performance. The result wasn’t significantly faster performance, sadly, even when the thermal headroom was used for overclocking (vs. stock OC). Nevertheless, lessons were learned, and the self-described “punk-rock GPU death lab” was still proud of the temperature reductions, plus the GPU contraption's “awesome” looks and sounds.

The experiment began with an overview of the Asus ROG GeForce RTX 3080, a nice example of the breed. But it was a choice that would perhaps end up making the 11-fan wonder look like less of an accomplishment. TrashBench stated the goal was to add more and more fans, plus duct tape and cable ties, then see whether the reduced temperatures from the boosted airflow result in more frames.

After cleaning and repasting the guinea pig GPU, a baseline was set with the stock cooler. Running 100% fan speed on the Asus ROG resulted in a stable temperature of 63°C (down from 70°C) during stress testing with the Unigine Heaven benchmark.

Replacing the Asus ROG cooling shroud with a trio of Arctic case fans dropped the reported GPU temperatures to a stable 52 degrees Celsius. That’s a decent result. Next, the trio of case fans was swapped for thicker server fans, shaving another 2 degrees Celsius off the GPU temperature, bringing it to 50 degrees Celsius precisely. Duct tape was added to prevent air venting from the sides of the server fans. Oops, the GPU temperature actually stabilized at a warmer 54 degrees Celsius.

So, that was the end of fans-at-the-front modifications. TrashBench next looked at adding a quintet of tiny Arctic server fans that run at up to 15,000 RPM along the top of the card. This jet-engine-soundalike configuration didn’t shift the needle, though. The RTX 3080 still wouldn’t hold below 50 degrees Celsius when tested for any length of time.

Trying backplate fans was the next idea. After another ineffective endeavor, though, TrashBench decided to upgrade the backplate fan to an AiO 360mm cooler. Wow - a new best was recorded with this setup, with the GPU reporting a top stable temperature of just 41 degrees Celsius in Heaven.

Momentarily happy with this low-temperature achievement, the tech tinkerer decided to check whether benchmark runs in Shadow of the Tomb Raider showed any benefit. There were some performance uplifts charted, but only very modest, as you can see from our results table, which even includes cases where the newfound overclocking headroom was taken advantage of.

TrashBench concluded with some positives. “It nearly cut the temperatures in half. It looks awesome. It sounds awesome,” underlined our hardware hacking hero. However, the tech tinkerer kept it real by adding “And it got me 2 FPS. So, not worth it.” In some ways, then, the good quality of the stock triple-fan Asus ROG RTX 3080 graphics card detracted from the 11 extra-fan hijinks.

The upcoming Super refresh of the Nvidia RTX 50-series GPU is reportedly on hold due to the high cost of 3GB GDDR7 memory chips. A VideoCardz source confirmed that one board partner already has RTX 50 Super GPUs on hand, but Nvidia has allegedly told the company that the products are on hold because of the price of 3GB GDDR7 memory chips.

This means that the AI GPU giant has already set an internal release date but is reportedly pushing it back because of memory pricing. If the cost of GDDR7 chips becomes too high, then the RTX 50 Super GPUs would either have a selling price that’s way above Nvidia’s targeted MSRP or, if it forces its partners to stick with or remain close to its set prices, GPU board manufacturers wouldn’t just make any units at all, as they’re going to lose money with every sale.

The RTX 50 Super GPUs are rumored to have 3GB GDDR7 chips, which offers 50% more capacity than the 2GB found in current-gen RTX 50-series graphics cards. This would allow the upcoming GPUs to have more memory without needing to increase or change their memory bus configurations.

According to the publication, the cards expected to be released soon include the RTX 5080 Super, RTX 5070 Ti Super, RTX 5070 Super, and RTX 5050 9GB. The first two will each receive 24GB of GDDR7 VRAM with a 256-bit bus width, while the RTX 5070 Super will have 18GB of VRAM with a 192-bit bus width. Unfortunately, these chips cost twice or thrice as much as their 2GB variants, which will likely push the retail price of these cards beyond Nvidia’s envisioned MSRP.

Nvidia used to supply VRAM chips alongside GPU dies to its board partners, but it changed this policy in late 2025 as the memory chip crisis unfolded. Because of this, the companies that complete the final assembly of the graphics cards are forced to source their own memory chips in an increasingly competitive market. SK hynix, one of the big three memory chip manufacturers, even says that 2027 is set to be the “worst year” for the memory shortage and said that the crunch will last until 2030.

Even Nvidia, one of the biggest winners in the AI race, has been affected by the RAMpocalypse, with the company not announcing a new GPU at CES 2026. This is the first time this has happened in five years, with Jensen Huang releasing the 30-series, 40-series, and their respective mid-generation refreshes despite supply chain limitations and several other issues that arose during that period. Its latest AI systems are now more expensive than ever, with memory accounting for 25% of the BOM, as costs have soared by nearly 500%.

It’s still unclear what Nvidia and its board partners plan to do about the memory situation, especially as things don't seem to be improving. While it could delay the launch of the RTX 50 Super, it can only do so for so long, especially if it’s true that its dies are already in the hands of its board partners.

AGI is back with another drive, this time with one more oriented at budget shoppers who want different capacity options with a heatsink. The AI828 slots in somewhere between the AI818 – a drive that didn’t impress us at all – and the AI858, a drive that was surprisingly good. The AI828 is a “one size fits all” type of drive that can work in a desktop, the PS5 console, or in a laptop if you don’t use the included heatsink. It’s not the best choice for any of these, but beggars can’t be choosers in this market. After all, we have PCIe 3.0 drives returning and entry-level drives like the TeamGroup NV5000 showing up, as well. The AI828 can outdo those and some of our original PCIe 4.0 favorites like the TeamGroup MP44L. Just don’t expect miracles.

AGI AI828 Specifications

The AGI AI828 covers every capacity you could ever hope for: 512GB, 1TB, 2TB, 4TB, and 8TB. Unfortunately, only 1TB and 2TB units were available at the time of review. These were going for $239.99 and $449.99 which is on the expensive side in both cases. Right now, however, this drive comes in and out of stock and can be priced competitively. It’ll probably be difficult to find the 8TB SKU, though.

The drive can hit up to 7,400 / 6,700 MB/s for sequential reads and writes, with no specification for IOPS given. IOPS tend not to be important for this segment – that is, a budget drive – and AGI is likely mixing multiple controllers and flash types based on availability and cost, which makes it less straightforward to try and nail down performance numbers. However, we would expect it to match the Seagate FireCuda X1070, with more than enough performance for this class.

AGI’s warranty covers the drive for the standard five years, with a bit extra on the writes front: the drive can absorb up to 750TB of data writes per TB capacity. The industry standard is 600TB. You probably won’t need this amount of writes, but it can be reassuring nonetheless, especially when dealing with less well-known brands and drives. It also suggests, but doesn’t guarantee, that TLC flash is used on the drive.

AGI AI828 Software and Accessories

AGI does not offer any substantial, direct software support. We recommend using CrystalDiskInfo for monitoring the health status of your drive. For basic benchmarking, CrystalDiskMark is a good choice. If you’re looking to backup data we suggest MultiDrive for windows and either Clonezilla or Rescuezilla for bootable options.

AGI AI828: A Closer Look

This is a single-sided drive that comes with an optional heatsink. This makes it great for the PS5 and many desktops, with the heatsink, and for laptops without. As this is intended to be a budget drive, that’s a bonus, as often there is no heatsink option. It’s best not to have to worry about a drive overheating in any circumstance, and the heatsink is sufficient for the job, but may not always be necessary.

The drive is pretty barebones with a DRAM-less SSD controller, two NAND flash packages, and a power management IC. As there is room for four flash packages, this drive could very well be single-sided at even high capacities. Not having a DRAM package helps. The PMIC is an Active-Semi or Qorvo part similar to what we’ve seen on some WD drives in the past. Power management can be handled this way, with discrete components, or as an embedded feature of the controller, each method with its own trade-offs.

The use of the PMIC makes sense when we look at the alignment of the drive: the controller is in the center. Leaving enough space for four NAND flash packages is ideal for a budget drive, and having the controller in the middle can be beneficial in some ways. We remember the WD Black having this configuration to help with cooling and to make even-length traces to the flash packages. Cooling is also aided as the heatsink can spread heat out to either side, with flash usually running cooler than the controller. This gives the center, hottest area of the drive a lot of heatsink surface area to dissipate heat before thermal equilibrium is attained.

As for traces, SSD controllers generally have to contend with timing issues to make sure all the flash operates in tandem, and even small differences can impact latency and, ultimately, drive efficiency. While we don’t think you should buy a drive based on this arrangement, it shows attention to detail on AGI’s part, even though that’s probably giving them too much credit with this being focused on the lowest possible BOM cost.

The flash is not directly identifiable through decoding or through utility use. We suspect the flash can vary on this drive, anyway, especially at different capacities. Examples we’ve seen have used TLC flash, and that matches the endurance rating of the drive. On the other hand, the Seagate X1070 with the same controller and TLC levels of TBW is using Micron’s 232-Layer QLC flash. Looking at the performance characteristics of the drive as a whole, we’re limited by the controller and relatively small capacities on hand. Usually, you will have TLC flash with smaller SKUs as it offers higher baseline performance, as historically, QLC flash dies have been denser, which means fewer dies. However, in this era of 1Tb dies for both TLC and QLC, this is less of a certainty.

The flash that can be paired with this drive is somewhat limited to newer generations due to the required I/O speed, but there is still enough variance – especially if you take flash quality into consideration – that nothing is guaranteed. This isn’t particular to this drive, especially in the current market where flash supply is limited. Still, we can be reasonably certain that it won’t be using “bad” flash, which puts it a cut above lower-end drives that are once again becoming common.

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Comparison Products

We’re pulling no punches. The AGI AI828 is going up against drives that can match or outclass it and are generally of a higher capacity. This puts the drive at a disadvantage, but we don’t really think it belongs in a lower class, either. Adjust your expectations accordingly.

The drive is up against some of the best DRAM-less PCIe 4.0 drives we’ve tested, with both TLC and QLC flash. These include the Crucial P310 with QLC, the Biwin Black Opal NV7400, the Addlink A93, the Inland TN470, and the WD Black SN7100 with TLC. The last one is using exceptional BiCS8 TLC, which has very low latency and very high power efficiency.

Drives that may be considered a step or half step lower include the Klevv CRAS C925 with different TLC flash, the Biwin NV7200 with QLC, and the Kingson NV3 with variable hardware. The AI828 is more of a match with these drives, but they are all tested at 2TB versus the 512GB and 1TB SKUs of the AI828. With fewer flash dies, the AI828 is at a disadvantage in some sequential workloads.

Trace Testing — 3DMark Storage Benchmark

Built for gamers, 3DMark’s Storage Benchmark focuses on real-world gaming performance. Each round in this benchmark stresses storage based on gaming activities, including loading games, saving progress, installing game files, and recording gameplay video streams. Future gaming benchmarks will be DirectStorage-inclusive, and an evaluation for future-proofing is included where applicable.

The AI828 is at the bottom of the chart, but it's not as bad as it could be. Poor performance at 512GB is to be expected – remember that most of the comparison drives are 2TB or larger. Such a low capacity for the AI828 does not allow for optimal use of newer, denser flash. Even at 1TB, things are stretched a bit.

We recorded 53µs for latency in 3DMark for the 2TB Seagate X1070, which means the AI828 1TB’s result here is actually not that bad. 50µs is far from a good score, but it's good enough for gaming. 512GB probably isn’t enough space for a gaming drive, but the AI828’s other capacities would work. This is not our first choice for a gaming drive unless it’s the least expensive, but your experience in general will not suffer from using it.

Trace Testing — PCMark 10 Storage Benchmark

PCMark 10 is an industry standard trace-based benchmark that uses a wide-ranging set of real-world traces from popular applications and everyday tasks to measure the performance of storage devices. The results are particularly useful when analyzing drives for their use as primary/boot storage devices and in work environments.

Things are significantly better in PCMark 10, which is not entirely surprising, as the flash compatible with this controller is likely to be newer. We want to point out that this doesn’t necessarily help us discern the flash in use. QLC flash, for its part, can have surprisingly good read performance because, for one, you can end up reading hot data from the pSLC cache, and two, QLC tends to be optimized for 4KB reads to compensate for the flash’s slower native speed. So the flash type is not always made clear through synthetic tests.

We consider ~45µs to be an ideal target for drive responsiveness, and both capacities of the drive hit this. We should add that 44µs is the same score we got on the 2TB X1070, so we see nothing unusual here. As always, a drive with BiCS8 TLC or QLC flash – that would be the Black SN7100 here – is optimal for the very lowest 4KB read latency. However, the AI828 is quite fast enough to serve as a primary drive or as the only drive in your system.

Console Testing — PlayStation 5 Transfers

The PlayStation 5 is capable of taking one additional PCIe 4.0 or faster SSD for extra game storage. While any 4.0 drive will technically work, Sony recommends drives that can deliver at least 5,500 MB/s of sequential read bandwidth for optimal performance. Based on our extensive testing, PCIe 5.0 SSDs don’t bring much to the table and generally shouldn’t be used in the PS5, especially as they may require additional cooling. Check our Best PS5 SSDs article for more information.

Our testing utilizes the PS5’s internal storage test and manual read/write tests with over 192GB of data, both from and to the internal storage. Throttling is prevented where possible to see how each drive operates under ideal conditions. While game load times should not deviate much from drive to drive, our results can indicate which drives may be more responsive in long-term use.

Our main PS5 tests show no problems with the PS5. These would be the read test and the game transfer test from the M.2 SSD. The problem comes with the write test – game transfer test to M.2 SSD – where clearly the 512GB drive is not writing or not writing fully to the pSLC cache. Generally, this is not a problem in our testing because pSLC caches are large enough to handle even larger writes, plus drives have sufficient idle time to free up the cache. However, the cache size varies with capacity, so it is smaller at 512GB, and for drives using denser flash, especially that is going to be an issue.

This is not likely to be a real-world problem as a drive, and especially a PS5 drive, probably won’t be taxed this hard, and even if it is, the average speed here is still largely sufficient. This just demonstrates why smaller drives have gone away as the move to denser flash makes performance less consistent – even a 512GB drive lacks sufficient dies for optimal parallelization. In fact, it’s just one die per channel with 1Tb dies. On the other hand, SSD prices scale with flash, especially with the price hikes, which means lower-capacity drives are making a return. Unfortunately, that just doesn’t work well at this performance level. So you are left in a situation where you either have to make do with a much slower drive or spend enough money to get 1TB or more to make a faster drive worthwhile.

Transfer Rates — DiskBench

We use the DiskBench storage benchmarking tool to test file transfer performance with a custom 50GB dataset. We write 31,227 files of various types, such as pictures, PDFs, and videos to the test drive, then make a copy of that data to a new folder, and follow up with a reading test of a newly-written 6.5GB zip file. This is a real-world type workload that fits into the cache of most drives.

The AGI reads data fine, but struggles a bit during write workloads. This impacts copy performance, as writes are more limited than reads. Write performance can be impacted by the size of the pSLC cache, but if that is not too small, then it is impacted by the amount of parallelization the drive achieves. Smaller drives have fewer flash dies, and therefore less parallelization, and as a result write more slowly, which in turn reduces copy performance. This means the 512GB AI828 struggles to match the larger drives in this list, although, actually, its performance is not terrible for a drive of its size.

When you double the number of dies, you can reach up to double the speed, and with half the dies, you might drop to half the speed. The 512GB SKU here manages to maintain 1.1 GB/s, which, for this type of workload, isn’t world-endingly bad.

The 1TB SKU also struggles against the larger drives. The only other 1TB drive, the TN470, is near the bottom of the list. The budget NV3 is about as fast as the 1TB AI828. So, we can be somewhat happy with the AI828’s result. We’d figure that with at least a slower controller, the AI828 is going to fall behind the TN470. That doesn’t change the fact that this drive should be at a discount as a result. We are merely saying that the performance here is not unexpected, although things should be better at 2TB.

Synthetic Testing — ATTO / CrystalDiskMark

ATTO and CrystalDiskMark (CDM) are free and easy-to-use storage benchmarking tools that SSD vendors commonly use to assign performance specifications to their products. Both of these tools give us insight into how each device handles different file sizes and at different queue depths for both sequential and random workloads.

Fundamentally, we don’t see any issues with the AI828 in ATTO. The dips for 1KiB and 2KiB writes, for example, have little to no impact on real-world performance. This is not only because you mostly feel the reads with consumer workloads, but because writes are preferably combined into full 16KiB pages, and typically your logical page will be at 4KiB. Likewise, the dip for larger writes with the smaller 512GB SKU is expected because you lack sufficient dies for parallelization. This could be an issue if you intend to write or store larger files to the drive, but then a 512GB drive is probably not ideal. One exception might be if it’s used externally, in which case picking a heatsinked drive is odd, but even if that weren’t the case, the typical NVMe to USB enclosure is rated for a meager 10Gbps, anyway.

Read performance is more problematic. The 512GB SKU still has issues with larger I/O for the reason mentioned, although this begins at a smaller size. You will likely have files or blocks at 128 KiB or larger, and your performance may suffer from going with a smaller drive. The 1TB drive is better off except at 2MiB, where we have a dip. We’ve in the past hypothesized this could be a flash alignment issue, which would suggest this drive uses six-plane flash. With the 2,400 MT/s requirement here, that would mean 232-Layer YMTC or Micron TLC.

In CDM, we can move right over to sequential reads and writes to get a fuller idea of performance. For example, both capacities are fine with sufficient queue depth, but at queue depth 1 – which is a realistic workload for file transfers – the smaller 512GB model struggles. It’s still within striking distance of the 2TB NV3, which means it’s actually pretty good for a drive of its size. The 1TB drive has no issues at all. We see something similar with sequential writes, except that the 512GB SKU sees no performance improvement with queue depth. It simply doesn’t have enough flash to eke out more than ~4.1 GB/s.

With random 4KB operations, though, the amount of dies won’t matter at QD1. This is because you’re only hitting one die at any given time. As a result, both capacities have the same latency for both reads and writes. This isn’t always the case, as sometimes a large-capacity model might have more overhead, or you may see different hardware combinations at some capacities. However, in this case, both drives are dead even. While the 4KB write latency is fine, the 4KB read latency is not great. However, this is actually better than the X1070’s 55.44µs we got at 2TB and is better than any of the 5 GB/s budget, PCIe 4.0 SSDs we’ve tested.

Again, we consider ~45µs to be excellent, with ~50µs being a second dividing point. The AI828 is close enough to put it above last-generation drives, but it’s slow enough to be relegated to game duty. The exception would be if you really only need 512GB and have to save money any way you can. In that case, this drive is passable, as you might otherwise be looking at older PCIe 4.0 or even PCIe 3.0 drives. This one still feels more snappy than those. At higher capacities and on a tight budget, if you can find the drive at the right price, it could also work, but would not be our first choice.

Sustained Write Performance and Cache Recovery

Official write specifications are only part of the performance picture. Most SSDs implement a write cache, which is a fast area of pseudo-SLC (single-bit) programmed flash that absorbs incoming data. Sustained write speeds can suffer tremendously once the workload spills outside of the cache and into the "native" TLC (three-bit) or QLC (four-bit) flash. Performance can suffer even more if the drive is forced to fold, the process of migrating data out of the cache in order to free up space for further incoming data.

We use Iometer to hammer the SSD with sequential writes for 15 minutes to measure both the size of the write cache and performance after the cache is saturated. We also monitor cache recovery via multiple idle rounds. This process shows the performance of the drive in various states including the steady state write performance.

The AI828’s first, fastest mode in pSLC writes at ~6.4 GB/s for 51 seconds with a 328GB cache on the 1TB SKU. Given that this is almost one-third of the full capacity, we’re dealing with TLC flash. This is a large cache, which means the drive will struggle once it’s depleted. That is the case with the 1TB drive, averaging below 200 MB/s in the post-cache mode. This is very slow, HDD slow, and even QLC flash slow, but that is not completely unexpected. A modern 1TB drive does not have enough dies to hit a higher speed, and if the cache is very large, as is the case here, the trade-off is slow performance outside the cache. The good news is that the large cache hides this very well in 99% of real-world cases.

The 512GB SKU has even fewer dies, too few to really manage sustained writes very well. It’s better in a read-heavy role, but it's too small for large media. In many cases, you’re better off with an HDD in that case. If, however, you need a smaller option for a primary drive in, say, an older machine, this could do the trick. Older machines benefit greatly from going to an SSD – especially an NVMe SSD – and will usually be read-heavy or even read-exclusive. If you are intending to get a small, 512GB caching drive, this is certainly not the way to go.

We must admit that, in our testing, the smaller SKUs’ cache size is tiny. This is highly unusual and points to AGI using a static cache in that circumstance. Such a small cache means the drive can rebound better, even with half the interleaving or parallelization of the 1TB drive, so it scores higher in steady state write performance testing. The use of static pSLC makes sense here to improve post-cache performance and potentially also to improve flash endurance. Static pSLC can lead to lower effective write amplification if you’re not doing big writes, and it is still ample enough to cache potentially damaging random writes. So, it’s possible AGI is making the best of a bad situation.

Power Consumption and Temperature

We use the Quarch HD Programmable Power Module to gain a deeper understanding of power characteristics. Idle power consumption is an important aspect to consider, especially if you're looking for a laptop upgrade, as even the best ultrabooks can have mediocre stock storage in terms of capacity and performance. Desktops are often more performance-oriented with less support for power-saving features, so we show the worst-case scenario for idle.

Some SSDs can consume watts of power at idle while better-suited ones sip just milliwatts. Average workload power consumption and max consumption are two other aspects of power consumption, but performance-per-watt, or efficiency, is more important. A drive might consume more power during any given workload, but accomplishing a task faster allows the drive to drop into an idle state more quickly, ultimately saving energy.

For temperature recording, we currently poll the drive’s primary composite sensor during testing with a ~22°C ambient. Our testing is rigorous enough to heat the drive to a realistic ceiling temperature, but real-world temperatures will vary due to the environment and workload factors.

Power efficiency is rough on the AI828. We also saw this with the X1070, so it must be chalked up to the controller. We suspect it’s because our workload is hard on the drive, and this controller is not as strong. You will likely not have issues with everyday, read-heavy activities. Also, our idle testing is for desktops, and a laptop with proper power-saving states will not be in as bad a shape. That’s all to say that we don’t think these results preclude the drive’s use in a laptop because, frankly, this drive isn’t fast enough to be an issue in most cases. We might recommend a different drive like the Black SN7100 if you're aiming at power efficiency or want/need a cool-running option, though.

Speaking of the heatsink, it kept both drives at a maximum temperature of 54°C. This means plenty of headroom, and the drive should be suitable for any machine that can take it. It won’t overheat. That’s a bonus for PS5 usage because the thermal envelope can be tighter.

Test Bench and Testing Notes

We use an Alder Lake platform with most background applications, such as indexing, Windows updates, and anti-virus, disabled in the OS to reduce run-to-run variability. Each SSD is prefilled to 50% capacity and tested as a secondary device. Unless noted, we use active cooling for all SSDs.

AGI AI828 Bottom Line

The AGI AI828, like the Seagate X1070, is not a great drive, but it’s also not one to dismiss. Memory prices have risen greatly within the last year, which impacts SSD prices through NAND flash costs and, sometimes, DRAM costs as well. An SSD’s cost is derived almost entirely from the flash, in fact. We’ve seen budget drives return in force, and we’re seeing low-end PCIe 4.0 and even PCIe 3.0 drives coming back.

This is also a reality for volatile memory markets – DDR4 is coming back, there was a threat that included even DDR3, and, believe it or not, DDR2 prices are increasing as well – with no end in sight. To put it simply, the AI828 would not have gotten far a year or so ago, but in the current climate, it’s not too bad. We feel that Seagate did a better job of presenting and supporting its drive, and, simultaneously, we feel like AGI has made improvements in its SSDs, so our score falls somewhere in between.

Let’s start with the good. AGI offers a wide capacity range for the drive, which is good for people who need 512GB or, theoretically, 8TB at a lower price. We think 8TB luxury buyers might opt for a faster drive like the Sandisk Optimus GX Pro 8100, WD Black SN8100, or Samsung 9100 Pro, or frankly, the less-expensive WD Black SN850X. The lower-end 512GB version of the AI828 perhaps makes more sense, but that’s one area where older technology might make sense. Newer flash is more dense and so really prefers higher capacities. On the other hand, the AI828 is more responsive than older drives, which is probably more important from a user experience perspective. So, despite some of the bad results, the fact that it’s using newer hardware is a bonus.

The drive also comes with a heatsink and runs pretty cool. It should be great for a normal desktop or in a PS5. It’s not very efficient, but that generally doesn’t matter in these two scenarios. Certainly not in most desktops, although there are exceptions. If you do have proper power-saving, it should be fine, though. The drive is designed to pull 5.5W or less at peak, which frankly isn’t concerning. So, we’re willing to give it a pass on the power side, although there are better options for laptops. One thing we have to mention again is that smaller SKUs don’t perform as well, and, since we’re testing at 512GB and 1TB today, the AI828 looks worse than it is. Most of the competition is sitting at 2TB because that was the sweet spot back when prices were sane.

It’s still hard to love the performance on this one. Like the X1070, which uses QLC flash, things are inconsistent across our benchmarks with relatively poor results on the whole. We opted not to put this one up against older or slower drives, even though some of those are making a comeback. The fact is, this drive will beat PCIe 3.0 and many lower-end PCIe 4.0 options and really shouldn’t be compared to those. You’re probably better off going with its newer tech unless budget is your only priority. Against other PCIe 4.0 drives in this range, however, even adjusting for capacity, it’s going to struggle. This drive has to be priced inexpensively to make sense, and if it is, we can recommend it for lighter duty.

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As Apple and other American companies seek to use memory chips from China-based CXMT and YMTC amid massive supply constraints, U.S. lawmakers want to ban exports of Chinese memory chips to the U.S., citing concerns of weakening domestic and allied suppliers and indirectly supporting the development of 3D NAND and DRAM by Chinese companies, reports the Financial Times.

John Moolenaar, Republican chair of the U.S. House China Committee, and Democratic Congressman George Whitesides asked Commerce Secretary Howard Lutnick to prevent U.S. companies from purchasing semiconductors from businesses included either on the Pentagon's Chinese Military Companies blacklist or the Commerce Department's Entity List. They also called on the administration to add CXMT to the Entity List and impose additional restrictions on YMTC.

"Dependence on Chinese memory manufacturers creates an unacceptable risk for U.S. national security, economic security, and supply chain security," the letter by Moolenaar and Whitesides reads.

Apple has been seeking approval from the Trump administration to source memory from CXMT amid a severe global DRAM supply crisis caused by the rapid expansion of AI infrastructure. Corsair, Patriot Memory, and some other suppliers of branded memory modules and SSDs have been using DRAM from CXMT and 3D NAND from Yangtze Memory for some time now.

"We are alarmed that Apple and other U.S. tech companies seek to purchase memory from Chinese semiconductor manufacturers, including those with ties to the Chinese military," the U.S. lawmakers wrote.

DRAM maker CXMT is already on the Pentagon's Chinese Military Companies list, whereas 3D NAND producer YMTC is already in the DoC's Entity List. Their presence in the lists does not outright prevent American companies like Apple from buying their products, but at a significant political risk.

Technically, American companies could buy chips from CXMT and YMTC to use inside products bound for China or other countries and continue to use memory from traditional suppliers in products aimed at the U.S. market. To prevent this, Moolenaar and Whitesides also urge the American government to coordinate with Japan, South Korea, and the EU to prevent CXMT and YMTC from taking advantage of the current supply shortage to establish themselves in allied supply chains, which they believe could ultimately leave the West strategically dependent on Chinese memory.

Moolenaar and Whitesides argue that purchases from Chinese memory manufacturers could indirectly support technologies applicable to China's military.

"Leading Chinese memory manufacturers are all closely intertwined with the Chinese military; thus, every memory purchase by a U.S. company will directly subsidize the People’s Liberation Army's development of this critical dual-use technology," the letter stresses.

The lawmakers argue that CXMT and YMTC could repeat China’s playbook in solar, steel, telecom, and EV markets: use state subsidies to undercut foreign rivals, weaken their investments, and ultimately exploit the resulting dependence for strategic leverage. That said, using Chinese memory now could permanently weaken Western production capacity and leave the West strategically dependent on China for a critical component of AI infrastructure, Moolenaar and Whitesides believe.

Intel was expected to unveil its next-generation desktop processors later this year. The upcoming Nova Lake lineup has been making the rounds online, and a new report from VideoCardz suggests that Intel could introduce it under the Core Ultra Series 400 branding. For context, the current Arrow Lake and Arrow Lake Refresh desktop CPUs follow the Core Ultra Series 200 naming scheme, while Intel's latest Panther Lake mobile processors carry the Core Ultra Series 300 branding.

The report also claims to reveal the review embargo windows and launch timeline for several Nova Lake models. According to the report, Intel will initially introduce a 28-core DS package, which is expected to launch between January and March 2027. The new DS suffix is said to be an internal package designation for processors featuring dual-compute tiles. This will reportedly be followed by 28-core K-series (unlocked) models between March and April 2027, while 16-core and 8-core variants are expected to arrive between late March and May 2027. The flagship 52-core DS model is reportedly scheduled for a much later launch, potentially between late May and September 2027.

While Intel is yet to officially confirm a launch date for Nova Lake, various leaks have suggested that the lineup could be one of the company's biggest generational leaps in recent years. The flagship desktop SKU, featuring a 52-core configuration, is expected to combine 16 Coyote Cove Performance (P) cores, 32 Arctic Wolf Efficiency (E) cores, and four Low Power Efficiency (LPE) cores. This would be a notable jump over the current Core Ultra 9 285K, which features a total of 24-cores. The introduction of Coyote Cove and Arctic Wolf also points to an entirely new CPU architecture, replacing the Lion Cove and Skymont cores found in Arrow Lake.

Nova Lake is also rumored to bring new platform upgrades including support for DDR5-8000 memory, up to 24 PCIe 5.0 lanes for expansion, Thunderbolt 5, and Intel's next-generation Xe3 Celestial integrated graphics. The processors are also expected to feature an upgraded NPU5 for AI workloads along with a 150W Processor Base Power (PBP) and 253W Maximum Turbo Power (MTP) on the flagship model, despite the substantial increase in core count. Earlier reports have also indicated that Nova Lake will transition to a new LGA1954 socket, meaning users will likely need a new motherboard to upgrade from the existing Arrow Lake platform.

Last month, at Computex 2026, AMD unveiled the Ryzen 7 7700X3D — its brand-new 3D V-Cache chip meant to slot in between the 7600X3D and the 7800X3D. As such, it comes in at a suggested retail price of $329 and, surprisingly, is available exclusively at Newegg in North American markets. It's a capable CPU in a vacuum, almost matching the 7800X3D in gaming while being more efficient in some titles, but it still doesn't provide the best value overall given the existence of the 7600X3D.

• Buy the Ryzen 7 7700X3D at Newegg

The 7700X3D and 7800X3D chips share pretty much identical specs. Both are 8-core, 16-thread CPUs based on the Zen 4 architecture, carrying a combined 104MB of cache. They have the same 120W TDP as well, with a 162W max power limit. The difference lies in the clocks, where the 7800X3D can boost up to 5 GHz; the new 7700X3D is limited to just 4.5 GHz.

When it comes to performance, at 1080p, the 7700X3D is actually the third fastest chip we've ever tested, right behind the 7800X3D and the 9800X3D. The stepped-down 7600X3D is very close to the 7700X3D as well, despite being almost $100 cheaper — this is the 7700X3D's biggest downfall: it's only 2% faster than the much cheaper 7600X3D. In our efficiency geomean, the 7700X3D posted the best FPS per watt results we've ever seen, just edging out the aforementioned 7600X3D.

Productivity is where the 7700X3D takes a hit, as it ranks toward the bottom of our charts when it comes to professional workloads. Intel takes the lead in this department, but it doesn't really matter since no one is buying an X3D chip outside of gaming priorities. If you're looking for an all-rounder, we suggest taking a look at the Core Ultra 250K Plus for around $200 or the Core Ultra 270K Plus for over $300.

The Ryzen 7 7700X3D is available across the world, but we can confirm that Newegg is the only place you can buy it if you're in Canada or the United States. This exclusivity runs through till Q3 2026, so the CPU isn't available even on Amazon or Micro Center — the latter of which has exclusivity for the Ryzen 5 7600X3D, Ryzen 5 7500X3D and the older Ryzen 5 5600X3D in America.

As per our review, the 7700X3D comes within 5% of the 7800X3D's gaming performance, but is only 2% faster than the 7600X3D, which you can buy on Amazon for $239. This makes it a tough sell, but if you're set on grabbing one, Newegg is the place to be.

Nvidia today announced that it's working with Japan's Noetra Corp. to build a 140-megawatt AI factory packing 27,500 Rubin GPUs and 13,750 Vera CPUs, the compute foundation for FRONTia, the Japanese government's state-funded physical AI program. The facility will be built from Vera Rubin NVL72 racks on Nvidia's DSX reference platform, connected with Spectrum-X Ethernet, and will train open multimodal foundation models for robotics, digital twins, and industrial automation, with pretrained weights shared broadly with domestic developers.

"Japan invented modern manufacturing. Now, it is building the AI factories that will power the next industrial revolution," said Jensen Huang, founder and CEO of Nvidia, in the announcement.

The chip counts divide exactly into 382 Vera Rubin NVL72 racks, each housing 72 Rubin GPUs and 36 Vera CPUs. Neither company disclosed the project's cost, but VR200 NVL72 systems are currently quoted at $5 million to $7 million apiece, which puts the rack hardware alone somewhere between $1.9 billion and $2.7 billion. Morgan Stanley estimates Nvidia will charge $55,000 per Rubin GPU in volume, pricing the GPU silicon at roughly $1.5 billion before memory, networking, and cooling.

No deployment timeline was given in the announcement, but Rubin racks are only expected to reach volume production in the second half of this year, and Nvidia said the facility will support trillion-parameter model training "as the AI factory expands," suggesting a phased ramp.

Noetra is a new consortium founded by SoftBank Corp., Sony, NEC, and Honda, with investment from 44 companies and organizations, NEC said in a press release also published today. Noetra and the national research institute AIST won a NEDO public tender on June 30 to run the FRONTia project from fiscal 2026 through fiscal 2030, with ¥387.3 billion (roughly $2.4 billion) in first-year funding and up to ¥1 trillion (roughly $6.1 billion) over five years, Asia Times reported. Funding beyond the first two years is subject to annual stage-gate reviews, so the full amount isn't guaranteed.

Noetra's roadmap targets a reasoning foundation model in fiscal 2026, an omni-modal model that processes text, images, video, and audio by fiscal 2028, and "real-world native AI" capable of spatial awareness by fiscal 2030, per NEC.

The AI factory follows SoftBank's Blackwell-based DGX supercomputer, announced in 2024, and FugakuNEXT, the $740 million RIKEN, Fujitsu, and Nvidia zetta-scale system due around 2030, but it's the first that's state-tendered national infrastructure rather than a corporate or scientific machine. Japan's AI Robotics Strategy, released in March, targets more than 30% of the global AI robotics market by 2040, an opportunity the government estimates at $133 billion.

The 7700X3D always made sense. Ever since the 5800X3D released and showed itself as the best CPU for gaming (at the time), AMD has continued to double down on 3D V-Cache, dominating the competition from Intel in games by double-digit margins. Because of the immense success of X3D CPUs, we’ve seen several variations with lower bins. Originally we had the 7800X3D, and now we have the 7700X3D. It’s cheaper and has lower boost clocks, but it gives you the same eight Zen 4 cores and 104 MB of combined L2 and L3 cache. It’s a 7800X3D for less money.

That, at least, is the assumption. Reality is a bit different.

• AMD Ryzen 7 7700X3D available exclusively at Newegg

A little less than two years after the 5800X3D released, AMD introduced the 5700X3D. Like the 7700X3D, it came with a cut to maximum boost clocks (400 MHz with the 5700X3D instead of 500 MHz here, but we’re splitting hairs), but still largely offered the gaming performance of the 5800X3D for less money. The problem here is that, although the 7700X3D could be a worthy successor to the 5700X3D, it’s too expensive.

The 5800X3D released in April 2022 for a suggested price of $450. Flash forward to January 2024, and the 5700X3D rolls out at $250. The 7800X3D launched in April 2023 for $450. The 7700X3D is arriving more than three years later in July 2026 for a suggested retail price of $330. It’s safe to call the 7700X3D a day late and a buck short, even ignoring the external pricing circumstances of the DIY market now.

That’s just a high-level analysis of launch pricing, too. Looking at prices now, the comparison is even more rough. Intel’s Core Ultra 7 270K Plus is the same price, within 5% of average gaming performance, 2X multi-threaded performance, and around 40% faster in single-core performance. AMD’s own Ryzen 7 7800X3D is, at the time of writing, available for $349, just $20 more than the 7700X3D (though I suspect that price will change). Buy a secondhand 7800X3D from Amazon, and it’s cheaper than the 7700X3D.

And, if you’re just focused on gaming performance and getting the best bang for your buck, the Ryzen 5 7600X3D is around $100 cheaper than the 7700X3D and within 2% of the average gaming performance.

The 7700X3D performs exactly how I expected it to. It’s not as fast as the 7800X3D, but if you squint hard enough, it’s close enough. It’s just too expensive. At $330, you’re almost forced to step up or down to AMD’s other Zen 4 X3D chips to get into a value sweet spot, and if you’re not solely focused on gaming, Intel offers much more powerful CPUs around the same price.

If the 7700X3D followed in the 5700X3D’s footsteps and released at $250 (even after three years of the 7800X3D on the market), it’d be a slam dunk. That’s not where we are for release, so let’s hope a price cut is waiting in the wings.

AMD Ryzen 7 7700X3D specifications and pricing

There’s a good chance the Ryzen 7 7700X3D is the last X3D processor we’ll see sporting AMD’s Zen 4 architecture, short of a potential Ryzen 5 7500X3D in the future. It further segments AMD’s last-gen lineup, and although there’s good pricing separation between each of the Zen 4 options, the spec differences are small.

For the Ryzen 7 7700X3D, the only spec difference it carries is a cut to clock speed compared to the Ryzen 7 7800X3D. You lose 200 MHz on the base clock and 500 MHz on the maximum boost clock. It’s a similar setup to what we saw with the Ryzen 7 5800X3D and 5700X3D, just a bit more aggressive. The 5700X3D shaved 400 MHz off the base and boost clock of the 5800X3D.

Otherwise, you’re getting the same eight Zen 4 cores available in the 7800X3D, along with 104 MB of combined L2 and L3 cache (64 MB of that L3 is stacked on the CCD). It also comes with the same rated TDP of 120W, though as we’ll see throughout our benchmark results, the 7700X3D never crossed into triple-digit wattages during our testing.

The 7700X3D slots into existing 600- and 800-series motherboards, and AMD says that it will boot on existing AM5 BIOS images (though the company recommends flashing the latest firmware). We didn’t need to install a specific BIOS image or chipset drivers to boot with the 7700X3D, so if you already have an AM5 motherboard, you should be set. In addition, the 7700X3D does not come with a stock cooler, despite arriving in AMD’s larger box design that we saw in the previous generation.

Outside of the step up to the 7800X3D, there’s a step down to the 7600X3D, which trades two cores (and consequently 2 MB of L2 cache) for a bump to a 4.7 GHz boost clock. As we’ll get to in our gaming benchmarks, there’s something about the range of 4.5 to 4.8 GHz where these Zen 4 X3D chips hit their stride, and the 7700X3D just barely hits that range without PBO assistance.

The 7700X3D arrives at a recommended retail price of $330, putting it in hotly contested waters. Intel has its newer 270K Plus around that same price, while the last-gen Core i7-14700K lands closer to the $380 mark. Down a step, the 250K Plus is more than $100 cheaper at $220, while the Core i5-14600K is available for around $250.

For AMD, you can step up to the 7800X3D for a $50 premium (at current prices) or down $90-$100 and get the 7600X3D. Of this tight grouping of Zen 4 X3D chips, none of them are bad options purely for gaming. Deciding between them is tricky. We’ve seen the 7800X3D on sale for as low as $348, which is a negligible price difference compared to the 7700X3D. And even at list price, the Ryzen 5 7600X3D is significantly cheaper, yet comes within just two points of the average gaming performance of the 7700X3D.

It’s impossible to give a concrete conclusion about which is the best because even a minor sale of $20 or $30 off tips the scales. The 7700X3D isn’t a bad processor, but there are a lot of situations where it’s not the optimal choice, mainly due to its proximity in price to the 7800X3D. Given the 7700X3D’s performance, it would ideally be priced around $260 to $280.

You’ll spend much more if you want to get one of AMD’s latest X3D chips with the Zen 5 architecture, which represent somewhere around a 15% to 20% improvement in average gaming performance. The 9800X3D is the cheapest Zen 5 X3D processor right now, and you can expect to spend about $450 to $480 on one. AMD suggested to Tom’s Hardware that it’s looking into a cheaper Ryzen 5 9600X3D for a future release, but that’s not available at the moment.

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The Ryzen 7 7700X3D puts to bed any notion that clock speed is irrelevant in a modern gaming PC. The chip is sandwiched between two other X3D chips: the coveted Ryzen 7 7800X3D and the less-considered Ryzen 5 7600X3D. The 7700X3D shares its DNA with the 7800X3D, both sporting eight Zen 4 cores and 104 MB of combined L2/L3 cache. The 7700X3D just shaves 200 MHz off the base clock and 500 MHz off the boost clock.

As usual, we tested a suite of modern games at 1080p with a mixture of High and Ultra settings, and without upscaling or frame generation enabled. We use the RTX 5090 on our CPU test bench to remove any GPU bottlenecks and isolate CPU performance as much as possible.

Given that we have eight cores to play with, I expected the 7700X3D’s gaming performance to land closer to the 7800X3D, not the 7600X3D. That’s not the case. The 7800X3D is 4% faster than the 7700X3D on average in games, while the 7700X3D is just 2% faster than the 7600X3D. You don’t give up much performance with the 7700X3D compared to the 7800X3D, but on the other hand, you don’t gain much performance compared to the 7600X3D, despite a $90 to $100 difference in price.

The Ryzen 7 9800X3D remains the fastest gaming CPU on the market, outside of the better-binned Ryzen 7 9850X3D, and it’s 19% ahead of the 7700X3D. Looking backwards a generation, the re-released Ryzen 7 5800X3D at $350 is in a tough spot. The 7700X3D is nearly 20% faster despite arriving on the market for $20 less. The impact of memory shortages has created some bizarre value comparisons, especially for CPUs.

Breaking out of the X3D bubble, Intel’s latest Core Ultra 7 270K Plus remains potent competition. The 7700X3D is ahead by 5%, and slightly less compared to the Core i7-14700K, which isn’t as wide of a margin as we’re used to seeing with new X3D chips. Particularly when bringing application performance into the mix, which we’ll get to next, the Core Ultra 7 270K Plus justifies a single-digit drop in gaming performance for how much it gains elsewhere; that’s assuming, of course, that you aren’t going for a pure gaming rig.

With Raptor Lake Refresh and Alder Lake chips, we tested with DDR5 memory (you can read more about our testing procedure later in this review). We tested DDR4 memory recently on these chips in our Ryzen 7 5800X3D re-review. That data is excluded here to keep the charts readable, but you shouldn’t expect miracles with DDR4. Based on our results, Raptor Lake Refresh chips with DDR4 are in the low single digits behind the Ryzen 7 5800X3D.

Outside of frame rate, you can see that the Ryzen 7 7700X3D landed squarely on 4.5 GHz in our gaming tests. Interestingly, the Ryzen 7 7800X3D locked in the same average as the 7600X3D at 4.7 GHz, despite the former boosting up to 5 GHz. The Ryzen 7 7700X3D also arrived at the lowest average power consumption, despite carrying a 120W TDP, clocking in just 0.1 W behind the 7600X3D.

The power consumption figures are interesting. The 7700X3D carries the same TDP as 7800X3D, but real-world power consumption is closer to the 7600X3D, which has a 65W TDP. And that lowered power consumption helps temperatures, with the 7700X3D clocking a cozy 55-degree Celsius average.

There’s headroom here in temperatures and power consumption for AMD’s Precision Boost Overdrive (PBO) to close the gap with the 7800X3D (but, then again, that chip has access to PBO, as well). We manually disable PBO in our testing, as it can push the chip outside of AMD’s default specifications, and in turn, void your warranty. If the warranty isn’t a concern for you, however, the 7700X3D should take nicely to a PBO bump.

007 First Light Benchmarks

007 First Light is the newest game in our test suite, and despite IO Interactive’s Glacier engine taking particularly well to X3D CPUs in Hitman 3, we see a shift toward Intel here. The 270K Plus is 7.6% faster than the 7700X3D, and that’s without optimization for Intel’s new iBOT feature. We can also see slightly weaker 1% lows on the 7700X3D compared to the other Zen 4 X3D chips, though nothing that completely changes the perceived smoothness.

Baldur’s Gate 3 Benchmarks

Baldur’s Gate 3, on the other hand, sees a nice boost with 3D V-Cache, as evidenced by the fact that the 5800X3D nearly matches the much newer 9700X (though with worse 1% low performance). The 7700X3D is in lockstep with the 7600X3D, and just shy of 6% behind the 7800X3D. Compared to the 270K Plus, the 7700X3D handily earns a victory with a 16.7% lead in average performance.

Looking at clock speeds, you can see Baldur’s Gate 3 gets much more out of these chips than First Light, all without an increase in power consumption. That leads to some exceptional efficiency results, with the 7700X3D offering two and a half frames for every watt consumed.

Crimson Desert Benchmarks AMD Ryzen 7 7700X3D

Crimson Desert is another recent addition to our test suite, and it shows remarkable CPU scaling in our benchmark of the dense city streets in the Hernand town center. Breaking from our other results, the 7700X3D is 6.9% ahead of the 7600X3D here, and just 1.3% behind the 7800X3D. The efficiency here is second to none at nearly three frames per watt. The 7700X3D is offering 7800X3D-like performance at 7600X3D-like power, which is the best-case scenario for this CPU.

Counter-Strike 2 Benchmarks

Counter-Strike 2 offers a closer look at the importance of 1% low performance, with our averages exceeding 600 FPS across most of the test pool. The 7700X3D is just 1.1% faster than the Core i7-14700K on average, but we can see a 24.7% jump in 1% low performance. That’s a common theme among all the X3D chips we tested in this game. That smoothness is important here. With such high average frame rates, swinging 100 FPS (or more) in either direction isn’t uncommon.

Cyberpunk 2077 Benchmarks

Cyberpunk 2077 shows a much tighter contest in average performance. Here, the 7700X3D is in lockstep with the Core Ultra 7 270K Plus and 14700K. Interestingly, the 7600X3D is a little faster here, though by less than a frame compared to the 7700X3D. Flipping over to our clock speed geomean, we can see what’s going on. Most of the chips in our test pool pushed up toward their maximum boost clock in this game, leaving the tame boost clock of the 7700X3D behind.

We’re looking at very tame power usage here, with an average of just 67 watts, and plenty of thermal headroom. PBO would help the 7700X3D push out a small lead over the Intel competition.

Doom: The Dark Ages Benchmarks

Doom: The Dark Ages is the only game in our suite using the Vulkan API, and it features always-on ray tracing. However, we still see CPU scaling even with such a GPU-focused pipeline. The 270K Plus squeezes out a marginal lead over the 7700X3D, but AMD’s chip is a bit more consistent in 1% low performance. The 250K Plus is especially impressive here, offering average performance on the level of $300+ CPUs for just $220.

As we can see from our clock speed results, the CPUs we tested ran comfortably below maximum boost clocks, suggesting the game is heavily threaded. As a result, the 7700X3D claims a clean 5% lead over the 7600X3D, nearly matching the 7800X3D.

F1 2024 Benchmarks

F1 2024 is an interesting benchmark because it provides yet another example of the 7600X3D outclassing the 7700X3D. The performance is close enough to call it identical, but I ran five passes on this game on both the 7600X3D and 7700X3D, and came away with the same results. Regardless, F1 2024 shows a massive advantage toward X3D chips, with even the lowly Ryzen 7 5800X3D beating every non-X3D chip in our test pool.

Far Cry 6 Benchmarks

Far Cry 6 mirrors what we saw in Doom, with the 7700X3D, 7600X3D, and 270K Plus all arriving around the same average frame rate. We don’t see an upper ceiling like in Doom, however, allowing the 7800X3D to claim a lead of 6.9%, and the 9800X3D shooting ahead to a 30% lead.

The power use for the 7700X3D here is especially low, falling behind the 7600X3D by about 6%. There’s probably some small, untapped optimization here that would help the 7700X3D close the gap with the 7800X3D.

Final Fantasy XIV Benchmarks

Final Fantasy XIV is another title that loves 3D V-Cache, and even among X3D CPUs, the game shows big jumps for newer architectures. The 7700X3D is 21% ahead of the 270K Plus here, but all of the Zen 4 X3D chips are tightly grouped between 175 and 180 FPS. In a blind shootout, it’d be impossible to tell between them.

Once again, the efficiency of the 7700X3D is remarkable at over three frames per watt consumed. The chip drew just 55.7 watts on average during our test, 32% lower than the 270K Plus and in line with the 7600X3D.

Flight Simulator 2024 Benchmarks

The Ryzen 7 7700X3D slips in the rankings in Flight Simulator 24, clocking in a frame behind the 250K Plus and 4.6% behind the 270K Plus. The Ryzen 7 9800X3D enjoys a comfortable lead, but there’s very little difference between AMD’s Zen 4 X3D offerings. They remain the most efficient of the bunch, however, with average power consumption below 60W.

Hogwarts Legacy Benchmarks

The 7700X3D once again trails Intel in Hogwarts Legacy, with the 270K Plus offering a 9% bump in average performance. The 7700X3D is a marginal 1.5% faster than the 7600X3D in this game, and it trails the 7800X3D by 3.8%. The 9800X3D, meanwhile, is a staggering 29% faster than the 7700X3D.

Marvel Rivals Benchmarks

The Unreal Engine 5-based Marvel Rivals remains the most popular hero shooter on Steam, but despite its technical backbone, the game shows clear CPU scaling at 1080p. As expected, the 7700X3D is marginally faster than the 7600X3D, and 5.1% behind the 7800X3D. Similar to Hogwarts Legacy, Intel holds an advantage with Arrow Lake refresh, though at significantly higher power draw and worse efficiency as a result.

Minecraft RTX Benchmarks

Minecraft is easily the most difficult benchmark for Intel. We’ve seen consistently low performance out of Arrow Lake CPUs in this test. Note that our Minecraft test uses a render chunk distance of 96, specifically stressing the CPU and memory chain to it.

Spider-Man 2 Benchmarks

Spider-Man 2 shows the 270K Plus once again besting the 7700X3D, this time by 4.9%. The 7800X3D also offers around a 5% jump. We can again see clock speed acting as a big influence in this test, but that extra clock speed comes at the cost of increased power draw, with the 270K Plus nearly doubling the average wattage of the 7700X3D in this test.

Starfield Benchmarks

Starfield is one of the few examples where we can see a clear benefit of the 7700X3D over the 7600X3D, with the former posting a 6% lead. The 270K Plus is slightly ahead of the 7700X3D, with a 3.6% lead, while the 7800X3D pushes further with a 6.7% jump in average performance.

The Last of Us Part One Benchmarks

Rounding out our game suite is The Last of Us Part One, where both the 270K Plus and 7800X3D are around 6% faster than the 7700X3D. AMD’s latest CPU is 5% faster than the base Ryzen 7 7700X, and 4% faster than the 7600X3D. You can see AMD’s non-X3D chips running into a performance wall, with the 7700X and 9700X posting virtually identical results.

This is one of the few games where the 7700X3D consumed more power than the 7600X3D, though only with a 5% bump to average wattage. Still, that’s enough for the 7600X3D to steal the top slot in efficiency away from the 7700X3D, which sits at the top of the efficiency rankings in most other titles.

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AMD’s X3D chips are built first and foremost for gaming, with only niche (and expensive) chips like the recent Ryzen 9 9950X3D2 pulling double duty in gaming and productivity applications. The hindered clock speed of the 7700X3D means it struggles even moreso than the 7800X3D in lightly- and heavily-threaded applications, which is already an area of weakness.

In our multithreaded geomean, the 7800X3D is 6.9% ahead of the 7700X3D while the base Ryzen 7 7700X is 12.8% ahead. AMD’s latest non-X3D eight-core, the Ryzen 7 9700X, is around 13% ahead with its default 65W TDP and a massive 28% ahead in its 105W TDP mode. The Ryzen 7 9800X3D pushes things even further with a 37% lead.

Short of the Ryzen 5 7600X3D, which the 7700X3D leads by a clean 25%, AMD’s latest X3D chip is at the bottom of the pile for multithreaded performance, at least among our DDR5 offerings. The comparison isn’t great among AMD’s offerings, but it's far worse among Intel’s.

The Core Ultra 7 270K Plus is 130% ahead, more than a 2X increase. We’re comparing radically different architectures and core counts, but the 270K Plus is leaps and bounds faster than the 7700X3D in multithreaded applications, and within 5% in games. Even the $220 Core Ultra 5 250K Plus is 70% ahead in our multithreaded geomean. The 7700X3D wins for gaming, even if its lead is small. But if you even just dabble in apps like Handbrake, Blender, and DaVinci Resolve, you’re giving up a lot of performance at this price with the 7700X3D.

The margins are always tighter in our single-threaded geomean, but the limited clock speed of the Ryzen 7 7700X3D means it ends up below every other DDR5 option in our test pool. The 7800X3D is 10% ahead, while the 9800X3D pushes ahead with a 25% lead. The base Ryzen 7 7700X also leads by a clean 20% margin.

In Intel’s camp, the Core Ultra 7 270K Plus is 42% ahead, while the 250K Plus is 33% faster. The Core i7-14700K and Ryzen 7 9700X are in lockstep, both beating out the 7700X3D by around 29%.

Single-threaded performance is especially limited on the 7700X3D, not only due to lower maximum boost clocks, but also the SRAM stacked on top of the CCD. It acts as an insulating layer between the CCD and IHS, giving you minimal headroom for large clock speed boosts on a single core, even with manual overclocking and robust cooling.

Rendering Benchmarks

In demanding rendering workloads like Cinebench, Blender, and POV-Ray, the 7700X3D struggles. The 4.5 GHz boost clock limits single-core performance, while the underlying Zen 4 architecture can’t scale up to AMD’s modern eight-core offerings. And, bringing Intel into the mix, strong single-core performance and Intel’s hybrid architecture with large core arrays allow Team Blue to sit near the top of the chart in most of our testing.

In Cinebench 2024, the 270K Plus was 135% faster than the 7700X3D in a multi-core render. The base 7700X, meanwhile, is 10% faster and the 9700X with its 105W TDP is 21% faster. Single-core performance shows big gaps, as well. The 7600X3D is faster than the 7700X3D with its higher boost clocks, while the 270K Plus offers around a 39% boost in performance.

There are even bigger gaps elsewhere. In POV-Ray, the 270K Plus is nearly three times as fast as the 7700X3D in the multi-core test. In Blender, the 7700X is 11% faster than the 7700X3D, and the 9700X 24% faster, in the Monster scene. And in V-Ray 6, even the $220 Core Ultra 5 250K Plus is 66% faster than the 7700X3D.

In heavily-threaded workloads, the 7700X3D and 7800X3D offer very similar performance, with a slight edge to the latter. We only see a big divergence between them in single-threaded workloads.

Encoding Benchmarks

Alongside rendering, our encoding benchmarks factor heavily into our geomean. We can also see a repeat here of what we saw in our rendering benchmarks, particularly among heavily-threaded video encoders like Handbrake. Across codecs, the 270K Plus is usually twice as fast (and sometimes more), while the non-X3D 9700X offers around a 30% boost depending on the codec. Compared to the 7800X3D, the 7700X3D is 7% slower with x265 and AV1.

In single-threaded audio encoding via LAME, the 7800X3D was nearly 9% faster than the 7700X3D, and that gap grows to nearly 10% in our extended LAME results.

Surprisingly, there’s a decent gap between the 7700X3D and 7800X3D in our image encoding/decoding benchmarks. In our multi-threaded JPEG-XL decode, the 7800X3D is 7% faster, while the 9700X is 26% faster. Similar margins appear in the encode.

Creator App Benchmarks

Creator applications like the Adobe suite and DaVinci Resolve are some of the most important for the 7700X3D; if you’re building a PC for gaming, the most likely non-gaming workload is some sort of video or photo editing application. These applications feature a ton of workloads spanning heavily-threaded and lightly-threaded tasks, so the margins between chips are much tighter.

Starting with Photoshop, AMD holds a strong position in this application across all of its CPUs, 7700X3D included. It matches the 14700K and closes in on the performance of the 270K Plus. The scales turn toward Intel in Premiere Pro, with the 270K Plus outperforming the 7700X3D by 9.5%. However, the 7800X3D is only a meager 1.9% ahead. We can see a similar situation in DaVinci Resolve.

Rounding out our tests is After Effects, where the 7800X3D is around 5% faster than the 7700X3D, and the 270K Plus is more than 30% faster.

Web and Office Benchmarks

General-purpose web and office workloads are usually lightly-threaded, so the 7700X3D struggles in these benchmarks. However, all of the CPUs in our test pool are more than capable of running these workloads, so although the 7700X3D often ends up near the bottom of the pile, the performance difference in real-world use isn't as big as the numbers would suggest.

In web-based workloads measured via WebXPRT, you can see the 7700X3D only manages to outclass AMD’s DDR4 options in our test pool, even falling short of the Core i7-12700K. Those single-core speeds really put a damper on performance here, though the extra two cores on the 7700X3D allowed it to achieve 15% better application start-up time than the 7600X3D in PCMark 10.

Microsoft Word and Outlook show similar performance differences, but the 7700X3D gains back some places in Excel and PowerPoint. A strong performance in Excel is important, but PowerPoint is tricky. As you can see from our results, the 7700X3D actually outperformed the 7800X3D; that’s just a consequence of PowerPoint not being a demanding application to run in most situations.

Chess Engines, Compilation, Compression, AVX, and Other Benchmarks

Rounding out our application tests are a series of highly specific workloads. We have a mixture of practical workloads like LLVM code compilation and compression/decompression with various algorithms, as well as some tests like various chess engines that drill down on IPC and applications like Optcarrot, which is an NES emulator looking at Ruby application performance.

Depending on what you plan to do with your PC, many of these workloads might not be applicable to you. Because of that, they aren’t included in our geomean, as some CPUs scale especially well in these niche workloads in a way that isn’t representative of overall performance.

SPEC Workstation 4 Benchmarks

Similarly, we run SPECWorkstation 4. We already run a subset of the tests included in SPEC in our own benchmark suite, but our full SPEC results give you numbers for the particular benchmark configuration used in the suite, as well as some additional scientific and security results.

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The 7700X3D is one of the most efficient gaming CPUs on the market, even offering more performance per watt than the 7800X3D. It’s highly optimised for that workload. Outside of games, power consumption remains very low, often below 80W even in all-out heavily-threaded tasks. Performance also slips, however, leading to worse efficiency.

Starting with raw power consumption, the 7700X3D averaged just 74W during a multithreaded Cinebench 2024 run, matching the 7600X3D. Again, the 120W rated TDP here is interesting, as the 7700X3D isn’t pushing past what the 7600X3D demands. In Blender and Handbrake, we can see the two chips in lockstep, as well.

The 7700X3D justifies its higher TDP a bit more in Linpack, where it drew 74W to the 7600X3D’s 65W. It’s worth highlighting our single-threaded y-cruncher pass, as well. In this test, the 7700X3D drew less power than the 7600X3D.

Outside of heavy workloads, we also measure idle and active idle (YouTube playback) power, and the 7700X3D does surprisingly well in these tests. As you can see from our two Zen 3 chips, AMD’s idle power consumption increased massively with a switch to a DDR5 platform with Zen 4. The 7700X3D pulls that idle power consumption back significantly, even compared to the 7600X3D and 7700X3D.

Turning to efficiency, you can see that the 7700X3D remains one of the most efficient options out of our test pool, though the margins are much thinner. In games, the X3D stack blows everything else away, but in Handbrake, we can see the 9700X offering similar efficiency. More interesting is the 270K Plus. The 7700X3D is 33% more efficient in our Handbrake x256 encode, but the two CPUs are in completely different performance classes.

When there’s such a wide disparity in application performance, these efficiency numbers can look a bit skewed. Cinebench provides a good example of that. The 7700X3D was nearly 40% more efficient than the 270K Plus, but the 270K Plus is around two and a half times as fast in this test. The 270K Plus and 9800X3D offer identical efficiency metrics, on the other hand.

A clearer way to visualize that is with a scatterplot. You can see in our Blender scatterplot, for example, a tight grouping of AMD’s processors around the bottom left of the chart, noting great efficiency but weaker performance. There are a few CPUs that hit an efficiency sweet spot, most notably the 9800X3D and 250K Plus.

Test Setup

We use a frozen test image and nearly identical test benches across the platforms in our pool. You can see the exact configuration we used for testing below. All of our tests are run on the same stack, including the OS build, chipset drivers, GPU drivers, and application versions. Particularly in game testing, where new updates are released constantly, we retest every chip in our test pool to validate our results, opting for the latest data for each CPU.

Our AMD and Intel test images never mix, so there aren’t remnants of AMD drivers on an Intel platform or vice versa. Across both vendors, we enable EXPO/XMP, turn off Virtualization-Based Security (VBS), and enable ReBAR. We also don’t enable any motherboard-specific optimizations, such as Gigabyte’s X3D Turbo Mode, as that adds an uncontrolled variable to our testing (and can sometimes even hurt performance).

On that thread, we also explicitly disable any performance profiles or optimizations that push the processor outside of warrantied operating specifications. That means running with Intel’s default performance profile (enforced power limits) and disabling PBO. Both push the processor out of the warrantied specifications.

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It’s surprising we didn’t see the 7700X3D sooner. AMD has told us that the 7700X3D (and the re-released 5800X3D) are both targeted releases to ease the burden of high DDR5 prices, but just like with the 5800X3D, it feels like AMD could’ve done more to ease that burden. The 7800X3D has already approached the MSRP of the 7700X3D with sales, and the 7600X3D has clearly come out on top as the value-focused option among AMD’s Zen 4 X3D CPUs.

It’s a tough pricing situation regardless, a consequence of continuing to bin and release various versions of largely similar silicon. Still, the 7700X3D has a pricing window. That window just doesn’t exist at $330. At $300, it would be more competitive with the rest of the market, and at $280, it’d be a difficult CPU to contend with. At $250 like we saw the 5700X3D, it’d be a no-brainer. $330 is the maximum price where you might be able to justify the 7700X3D, and that’d only be if you completely ignore CPUs going on sale and wipe out Arrow Lake Refresh from your memory.

The two CPUs that remain the most potent competition are Intel’s 270K Plus and the 7600X3D, not the 7800X3D. On sale, the 7800X3D is the better buy, full stop, but if the 7700X3D is targeting gamers that want to stretch their dollar the furthest, the 7600X3D offers a lot more value.

You can see that clearly in our gaming geomean. The 7600X3D is just 2% slower than the 7700X3D on average, and even in extreme situations, the performance gap between them never approaches double digits. The 7800X3D and 7700X3D offer a similar value at list price, which is about half a frame per dollar. Meanwhile, the 7600X3D offers three-quarters of a frame per dollar.

The value isn’t bad with the 7700X3D, make no mistake. It’s in line with the 270K Plus and 7800X3D, but it shouldn’t be. It’s a value-focused alternative to the 7800X3D, but it doesn’t provide much additional value. At around $280, it’d shoot up in the value rankings and become much easier to justify.

On the other end of the spectrum is Intel’s 270K Plus. It’s 5% slower in average gaming performance than the 7700X3D, but it makes up for that small gap with more than twice the multithreaded performance of the 7700X3D. Even if you only commonly use one non-gaming application, the performance uplift of the 270K Plus is large enough to justify a small hit to gaming performance.

With most 3D V-Cache CPUs, the drop-in application performance is easy to justify, even if the boost in gaming performance can’t keep pace. You buy an X3D chip primarily for playing games, not compiling code, running Fourier Transforms, or building a web server. Here, however, the margins in gaming are some of the smallest we’ve seen between X3D and non-X3D CPUs, while the margins in applications are some of the largest.

There’s three paths away from the 7700X3D right now. The 270K Plus offers a much more well-rounded CPU around the same price. The 7600X3D delivers the gaming value that the 7700X3D is sorely lacking, and the 7800X3D is only slightly faster in games, but it’s also only slightly more expensive. Hopefully we’ll see the 7700X3D drop to between $250 and $280. At that price, it’s a CPU worth considering. At its current price, it’s hard not to go with another option.

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Homegrown DDR5 memory from China, manufactured by ChangXing Memory Technologies, has been making the rounds lately as more and more vendors start legitimizing it. However, new testing from overclocker Safedisk, shared by Uniko's Hardware, purportedly shows that it actually carries inferior performance compared to similar options from SK Hynix, alongside significant variance in the silicon between different batches.

CXMT began producing DDR5 in late 2025 despite lacking any cutting-edge EUV lithography tools. Fast forward to today, and reports of the company matching Micron's memory capacity by this year are now floating around. If true, China would become the second-largest memory maker in the world. At such scale, it's no wonder that many companies in China have already started sourcing CXMT-made RAM to fill the gap in the consumer market.

Throughout 2026, we've seen motherboard manufacturers verify CXMT's DDR5 with official BIOS optimizations that allow it to run beyond 8,000 MT/s at this point. OEMs such as Dell and HP are using CXMT RAM in their region-bound systems, and even proper PC hardware companies like Corsair are using CXMT modules. Lexar, Kingbank, Netac, Asgard, Gloaway and more are also producing retail DDR5 kits with CXMT chips.

As such, the testing features a Kingbank 48GB (2x24) DDR5-6000 kit running at CL36 and found several weaknesses despite successfully achieving an 8,600 MT/s overclock at CL44. The first revelation is that CXMT modules don't scale with voltage, meaning you can't just increase voltage in hopes of achieving higher clocks. CXMT's DDR5 apparently doesn't respond well to tuning sub-timings either, forcing you to remain stuck with baseline CAS latency (or higher, like in this case).

Different batches of CXMT-equipped memory perform differently, too, so silicon lottery plays a much bigger role than it would with other vendors. Speaking of which, SK Hynix-made DDR5 modules allegedly performed better at identical clock speeds, while CXMT's modules were less susceptible to overclocking in general. We didn't get any comparative benchmarks for any metric, so take these claims with a grain of salt.

Overall, if the testing is to be believed, it serves as counterprogramming against the popular narrative forming around China as the savior of consumer interests. CXMT's strength lies in the fact that it doesn't have to cater to opulent AI clients as much as the Big Three, which reduces opportunity cost, allowing CXMT to produce more DDR5 memory. That doesn't mean it would be cheaper, though, or at least no evidence has suggested that so far.

CXMT has remained limited to the Chinese region for now, and breaking through to the Western market would mean impressing a lot of skeptics. Not only would pricing play a big factor, but the reliability of a new DRAM manufacturer would raise serious concerns. Stories like these certainly don't help, but with CXMT's IPO on the way, it's only a matter of time before it becomes a serious mainstream contender.

ASRock is well known among PC enthusiasts for its graphics cards, motherboards, power supplies, and gaming monitors. Now, it has entered the market for liquid cooling solutions.

We’re looking at two of the company’s first AIOs here, the Phantom Gaming 360 LCD and Steel Legend 360 LCD. Both of these liquid coolers feature 3.4-inch 480 x 480 displays for showing off animations and monitoring performance metrics. Aside from aesthetics, the main differences between the two are the included fans and radiator size. The Steel Legend 360 incorporates a standard 27 mm thick radiator, whereas the Phantom Gaming 360 uses a thicker-than-normal 32 mm radiator.

Let's take a look at the specifications and features of the coolers, then we’ll go over thermal and noise benchmarks and decide whether ASRock’s Phantom Gaming and Steel Legend AIOs deserve to make our list of the best CPU coolers.

Cooler specifications

Features of ASRock Phantom Gaming & Steel Legend 360 LCD

▶️ 60hz 3.4-inch LCD display

Both the Phantom Gaming 360 LCD and the Steel Legend 360 LCD include a 3.4-inch square IPS screen with a 480 x 480 resolution and 60 Hz refresh rate, with brightness rated at 250 nits.

To control and customize the screen, you’ll need to download ASRock’s Polychrome Display software. You have the option of selecting six preset themes, or you can build your own theme, and/or customize the individual elements shown on the display.

While I certainly wish there were more presets available, my biggest complaint using this software is the extreme file compatibility limits. If you’d like to upload a custom background, the image or video file needs to be less than 20 megabytes and 1080p or lower in resolution.

▶️ RAM Clearance

As with most liquid coolers, the design of both the Steel Legend and Phantom Gaming 360 has the CPU block set so it doesn’t overhang or interfere with the DIMM slots – ensuring that all sizes of RAM, no matter how tall, are compatible.

▶️ VRM fan

Included on top of the CPU block is a 70 mm, 3,000 RPM fan designed to help keep your RAM and motherboard’s VRM modules cool. As you’ll see in our Karhu benchmarks, it does an excellent job of cooling these parts of your computer.

▶️ Thick CPU cold plate

The copper contact plate is unusually thick, like you’d more typically see in an AIO supporting AMD Threadripper or Intel Xeon server CPUs.

Differences between the ASRock Phantom Gaming 360 LCD and Steel Legend 360 LCD

▶️ Color schemes and aesthetic

While they are similar in many ways, each of these AIOs has a different aesthetic, similar to what you’d see in the company’s motherboard lines. The Steel Legend might appeal to those who prefer simpler designs, with a white body and gray fan blades.

If you want flashy lighting, the Phantom Gaming 360 might be your thing. In addition to ARGB lighting on the fan blades, it also includes a lighting strip across the side of the radiator.

▶️ Radiator sizes: 32 mm and 27 mm

There are two primary technical differences between the Phantom Gaming 360 LCD and the Steel Legend 360 LCD; one of those is the radiator size. The Steel Legend 360 LCD has a standard 27 mm radiator, whereas the Phantom Gaming 360 features a thicker 32 mm radiator.

▶️ 120 mm fans

There’s more to a liquid cooler than just the radiator and liquid pump. The included fans directly impact noise levels and cooling performance. This constitutes the second primary technical difference between the AIOs we’re reviewing today.

Both units include fans that are 28 mm thick and pre-installed for user convenience. The Steel Legend 360 features three individual 120 mm fans, with a white shell and gray blades.

The Phantom Gaming includes a fancier fan block instead of individual fans, and features ARGB lighting on the fan blades and a strip across the radiator. These fans aren’t as powerful – or as noisy – as the fans included with the Steel Legend, but this is balanced by the thicker 32 mm radiator included on the Phantom Gaming 360 LCD.

Packaging

The outer packaging is a bit flashy – at least, in comparison to your normal AIO box. It features a rendering of the cooler against a black background with streaks of purple hues.

The inner packaging is just as fresh as the outside, with each component of the cooling system well protected from the chaos that shipping can bring by using a combination of soft covers and individual cardboard walls for each component.

Included with the package are:

• Mounting hardware for AMD and Intel platforms
• Tubing clips
• A small tube of thermal paste
• 360 mm radiator and 120 mm fans
• 3.4-inch LCD display

AM5 Installation

This section assumes you’ve already mounted the 360 mm radiator. Installation of AIOs is typically much easier when you have already secured the radiator to your computer case.

To begin putting things together, you’ll first need to remove the default AM4/5 retention from the motherboard.

The next step is to place the mounting bars on top of the studs, securing them with the included screws. The middle of the mounting bars includes a helpful image indicating the direction the bars should be installed, with an arrow pointing towards where the CPU should be.

Now you’ll want to apply the included thermal paste. If you’re not sure how to do that, we have a handy thermal paste application guide that covers the different methods you can use.

Afterwards, place the pump block against the CPU and mounting bars, and use a screwdriver to secure it. You should have the liquid tubing in the south position for best thermal performance.

The next step is to slide the LCD display on top of the VRM fan. To complete the AIO’s installation, you’ll want to connect the USB, PWM, and ARGB headers as appropriate – then you can power on your system.

Real-world testing configuration – AMD AM5 platform

We’ve tested coolers with both the Ryzen 9950X3D and its non-V-Cache sibling, the 9950X. There are some differences in how the 9950X and 9950X3D CPUs are impacted by thermal events. While the heat output of the CCDs of AMD’s 9950X3D is relatively balanced, the 9950X I used has one CCD that runs much hotter than the other, with a difference of over 10 degrees Celsius in some scenarios, shown below.

We’ve since returned to using a 9950X3D for cooler testing, as it has a more balanced heat profile, and is almost certainly a more widely adopted CPU. The benchmark results shared in these reviews may differ from others because I emphasize results that are comparable to real-world use. This means I generally test CPU coolers inside of a closed desktop case, which increases cooling difficulty compared to other testing methods.

Many reviewers test coolers on open test benches, which have a combination of lesser airflow needs and lowered ambient temperatures. This results in making weak coolers appear stronger than they really are. Some also use generic thermal plates to test cooling solutions. I reject both of these methods because they don’t accurately reflect real-world cooler conditions.

Our latest testing setup uses the Flova F50 computer case from Tryx.

This case features a unique “crossflow” fan that pulls air from the side, which the company claims is more effective than traditional intake fans. For air cooling tests, we’ve added a single Noctua NF-A12 G2 intake fan.

We’re going to start this review’s benchmark section by focusing on a traditional maximum performance test, with the CPU cooler’s fans allowed to reach their fastest speeds for the best cooling possible.

Turning on PBO allows AMD’s Ryzen 9 9950X3D to stretch its legs to an extent, and all air coolers I have tested with PBO enabled using MSI’s X870E Carbon Wifi motherboard reach the maximum CPU temperature of 95 degrees C (203 F) and thermally throttle to some extent.

The thermals of both ASRock AIOs are excellent, able to keep AMD’s Ryzen 9 9950X3D under its peak temperature (TJ Max) in Cinebench R23 with PBO enabled – allowing for the best possible benchmark performance. Of particular note is the performance of ASRock’s Steel Legend 360; it maintained an average of 61.5C over ambient (83.5C), the best result we’ve seen on this test bench.

Some coolers perform well in maximum strength tests, but require running loudly to maintain said performance. The ASRock AIOs we tested reach 46.9 and 47.8 dBA, which is about average for most liquid coolers on the market.

200W thermal benchmarks

For the next thermal test, I leave the motherboard settings at their defaults, which results in a power limit of 200W when running Cinebench R23.

When a standard power limit is imposed, the thermal differences between the two ASRock coolers close, with both coolers performing about the same. I measured 47.3 and 47.9 degrees over ambient, giving them the third- and fourth-best performing results from this test bench.

150W + GPU thermal results, noise levels

Our next test runs Cinebench on the CPU with a 150W power limit, while also running Furmark on MSI’s RTX 4070 Ti Super Ventus 3x OC. This causes the GPU to consume ~295W of power. This test is designed to emulate the thermals of games, which primarily stress the CPU and GPU.

ASRock’s Steel Legend stood out in this test, outperforming all other competitors, with an average temperature of 57.4 C (35.4 C above ambient). The Phantom Gaming AIO also performed well, taking the fourth-place spot.

But thermals are only part of the story. Noise levels, especially when you’re gaming, are far more important here. When tied to my motherboard’s default fan curve, ASRock’s Steel Legend 360 had a noise level measured at 39.2 dBA. The Phantom Gaming 360 LCD was just a hair louder, measuring 39.6 dBA.

Noise-normalized testing

Most testing is performed with the cooler tied to the default fan curve of our MSI X870E Carbon motherboard, but some prefer to see tests when the noise levels of coolers are equalized. This is especially important to those of you who prefer silent computers. This next test has the CPU cooler noise-normalized to 38.9 dBA, with PBO enabled for the Ryzen 9 9950X3D CPU.

With recordings of 258.8 and 258.2W average CPU power consumption, ASRock’s AIOs perform essentially on par with each other while noise-normalized.

Karhu DDR5 RAM thermals testing

Your CPU cooler does not operate in isolation. It has an impact on not just your CPU’s temperatures, but also the other components in your build, like your RAM and GPU. To that end, I’ve run the Karhu RAM stress test. This places a load of ~153W on the CPU and ensures system RAM (DDR5 in my case) is fully stable. In this type of scenario, most AIOs tend to produce worse results than air coolers.

DDR5 temperatures were excellent in this test, with averages of 20.9 C (Steel Legend) and 21.5 C (Phantom Gaming) recorded. Of the AIOs I’ve tested on this configuration, only Silverstone’s IceMyst Pro with its unique stackable fans performs better.

We’ve also included a chart showing the CPU temperatures in this test, and thermal performance was strong – outperforming air coolers by ~5 degrees C. But I haven’t recorded this data for other AIOs yet.

Conclusion

ASRock’s Steel Legend 360 LCD and Phantom Gaming 360 LCD are both strong coolers, well suited to heat-intensive CPUs like AMD’s Ryzen 9950X3D or Intel’s Core i9-14900K.

Of the two ASRock AIOs, I would recommend the Steel Legend 360 LCD for users who want the best thermal performance possible (and a lower price tag). It might lack the thicker 32 mm radiator included with the Phantom Gaming 360 LCD, but its included fans are stronger, and as a result provide lower CPU temperatures and quieter noise levels in common scenarios. Still, at around $160, the Steel Legend is far from the most affordable AIO with a display, and it’s only available in white.

Nowadays, storage devices for consumer and data center applications differ rather dramatically, as do approaches to product design as well as go-to-market strategies. Therefore, to get a more or less comprehensive overview of the storage market in general, you must observe both ends of the spectrum. To complement our interview with Nelson Duann at Computex, we also sat down with his colleague Alex Chou, who is in charge of Silicon Motion’s enterprise storage business.

Alex Chou is an interesting person to talk to. Before joining Silicon Motion, he spent some 18 years at Broadcom, where he led the wireless connectivity business, also initiating the Enterprise Switch, PoE, and 10-G Base-T PHY business with a product marketing focus. Before that, he worked at UMC Capital, ARK Logic, and Western Digital, where he developed graphics accelerators. He deeply understands the industry and uses his knowledge to expand SMI's business into the data center segment. As he is the first general manager of Silicon Motion's enterprise business unit, it is safe to say that all the success that the company has faced in the new segment so far can be attributed to Alex Chou.

Anton Shilov: Can you introduce yourself to our readers, please?

Alex Chou: My name is Alex Chou. As you know, Silicon Motion has two business units: the client business and the enterprise business. I am responsible for the enterprise business unit. My responsibilities include defining new products, leading development teams, bringing products to market, and working with OEMs, cloud service providers, and other customers to promote our technology and differentiation.

Getting into enterprise SSD business

Historically, Silicon Motion was focused on NAND controllers for client applications as well as embedded graphics processors and USB display controllers. Following the restructuring in the early 2020s, SMI formed a separate business unit to offer enterprise-grade SSD controllers, though it took the company some time to land its first tangible orders. By now, the company has yet to grab a 10% market share, yet it has clients among cloud service providers (CSPs), hyperscalers, and OEMs, significant achievements given Silicon Motion is a relatively new market entrant.

Anton Shilov: It has been a challenging year for much of the industry, particularly for memory-related segments. Yet Silicon Motion reported first-quarter revenue of $342.1 million, up 23% sequentially and 105% year-over-year, while SSD controller sales increased by roughly 40% to 45%. Can you explain what drove those results, particularly on the enterprise side?

Alex Chou: It depends on how you define a difficult year. If you look at the results, I would argue that this has actually been one of the best years the storage industry has seen.

Silicon Motion is fundamentally a controller company. We build controllers that work with NAND from all major memory suppliers. On the enterprise side, we are still relatively new compared to some established competitors, but we have secured a number of new projects and have started delivering products to customers.

We have invested heavily in PCIe Gen5, Gen6, and Gen7 enterprise SSD controllers. Today, our Gen5 products are beginning to ramp into volume production with multiple OEM customers. That ramp is contributing to our growth.

Anton Shilov: Do you have an estimate of your market share in the enterprise SSD controller market?

Alex Chou: That depends on how you define the market. Some people measure market share by unit shipments, while others look at exabytes shipped because SSD capacities continue to increase.

We have only recently begun shipping enterprise products in volume. If you listened to our CEO's comments during the earnings call, we expect enterprise shipments to increase significantly in the second half of the year. We are still in the early stages of our ramp, but we are making good progress with several key customers.

If you look beyond the initial ramp and think about the full-year run rate, I believe we can build from there and target a much stronger position next year. Longer term, our goal is to exceed 10% market share in the $4B enterprise SSD controller market, but this year is really about getting through qualification, customer testing, and the early production ramp in 2 half of this year.

Our goal is to continue expanding our share. We are only beginning the ramp [of our data center-grade SSD controllers] today, but we expect our share to increase meaningfully as deployments grow.

Anton Shilov: Who are your primary customers? SSD manufacturers, OEMs, or hyperscalers?

Alex Chou: We primarily work with OEMs. We sell controllers and firmware solutions to SSD manufacturers and OEMs. Some customers use our complete controller-and-firmware solution, while others develop their own firmware.

At the same time, we work directly with hyperscalers and cloud service providers to explain the advantages of our products and ensure they understand our technology roadmap.

Enterprise SSDs are used in several different segments. Traditional compute servers represent one market. High-density storage systems used for AI and large-scale data storage are another. We also see growing interest in storage systems located near GPUs, where latency becomes particularly important.

One area where we differentiate ourselves is quality of service. We have developed a patented traffic-shaping engine that helps maintain latency consistency under heavy workloads and multi-tenant environments. That capability is particularly attractive to hyperscalers and cloud service providers.

Anton Shilov: Do you see the enterprise SSD market splitting into different categories depending on workload?

Alex Chou: Yes. We see at least three major categories emerging.

The first is traditional compute-attached enterprise SSDs, which are used in conventional servers and storage systems. The second is very high-density storage for AI and hyperscale environments, where capacity, throughput, and cost efficiency are critical. The third is storage located closer to GPUs, where the requirements are very different because latency and quality of service become much more important.

That third category is particularly interesting. In AI systems, the storage subsystem is no longer just feeding CPUs. It increasingly has to support GPUs directly, especially for workloads involving very large datasets or KV-cache offload. In those environments, low latency and predictable performance matter much more than they did in traditional storage deployments.

Storage Next, PCIe 6 and PCIe 7 SSD controllers

Anton Shilov: Is that where Nvidia's Storage Next vision comes in?

Alex Chou: Yes. Storage Next is one of the major industry developments we are watching very closely.

The idea is that storage will move closer to the GPU and become part of a much more tightly integrated data path. In some cases, the goal is not just to maximize bandwidth, but to ensure that latency remains low and deterministic enough for AI workloads that continuously move data between accelerators, system memory, and storage.

This is one of the reasons we have invested heavily in QoS and latency control. Through our traffic-shaping technology, we can manage access patterns and reduce latency spikes when multiple tenants or applications share the same SSD. In a cloud environment or an AI storage environment, that becomes very important.

Anton Shilov: So, the challenge is no longer just raw throughput, but how predictably the SSD behaves under load?

Alex Chou: Exactly. Bandwidth still matters, but in many enterprise and AI environments, consistency matters just as much.

When multiple applications, multiple VMs, or multiple users share the same storage device, you need to control latency and quality of service carefully. If performance becomes unpredictable, it can affect the entire system.

That is why we have focused on a traffic-shaping mechanism that can prioritize and isolate workloads more effectively. We believe that kind of latency management will become a key differentiator for enterprise SSD controllers going forward.

Anton Shilov: How does that affect your roadmap for future controllers?

Alex Chou: It affects it quite a bit. Our upcoming controllers are not designed only for higher sequential bandwidth. They are also being designed for newer enterprise requirements such as OCP 2.7 compliance, stronger security, better QoS, and support for more advanced deployment models.

Anton Shilov: Are you already sampling your PCIe 6.x controllers?

Alex Chou: On the Gen6 side, our controller design is essentially complete; we have an FPGA [emulating algorithms], and we expect tape-out very soon. If everything goes according to plan, we expect first silicon back in the second half of 2026.

That controller not only supports a faster host interface, but also supports new features and requirements we see from AI infrastructure and hyperscale customers.

Anton Shilov: So, the PCIe Gen6 SSD platform is not just a speed upgrade for Silicon Motion?

Alex Chou: Correct. PCIe Gen6 obviously provides more bandwidth, but for us the more important part is that the surrounding system requirements are changing as well. Security, QoS, cloud deployment models, and AI storage architectures are all evolving at the same time, so the controller has to evolve with them.

Anton Shilov: Let us talk about the roadmap in more detail. You said the PCIe Gen6 enterprise controller is close to tape-out. What comes after that?

Alex Chou: PCIe Gen6 is the next major step for us, and the design is essentially complete. We expect to tape out very soon and, assuming [everything works correctly], receive first silicon in the second half of 2026.

But internally, we are already working beyond PCIe Gen6. PCIe Gen7 development has already started. In fact, the overall architecture for our Gen7 enterprise controller platform has already been defined. That means we are not just planning the interface speed increase; we are also defining the surrounding architecture, feature set, and deployment model that will be needed in the next generation of enterprise and AI systems.

Anton Shilov: So, SMI's PCIe Gen7 controller is no longer just a concept?

Alex Chou: Correct. PCIe Gen7 is already in active development. The current plan is to have internal samples in 2H, 2027 and to move toward production in that same general timeframe.

As controller development becomes more complex, you cannot wait until the market is ready before starting work. By the time a new interface reaches the market, the controller has to be nearly finished already. So, we are always working at least one generation ahead, and in practice often two.

Anton Shilov: As NAND becomes denser and more complex, error correction also becomes a bigger issue?

Alex Chou: That is a major part of controller development now. As NAND moves to higher layer counts and denser cell structures, the controller has to do more work to maintain reliability, endurance, and data integrity.

One of the areas we are working on is stronger LDPC. On the enterprise side, LDPC with a 16KB collaborative codeword is already used with SM8466, SMI’s first Enterprise PCIe Gen6 controller, and it is part of the roadmap because future NAND will require more robust error correction. That is one of the reasons enterprise controller architecture keeps becoming more complex generation after generation. You are no longer designing only for interface speed. You are also designing for signal integrity, power, security, QoS, error correction, and support for future NAND generations that may behave very differently from today's devices.

Anton Shilov: Will LDPC with 16KB collaborative codeword be enough for next generations of 3D NAND with hundreds of active layers?

Alex Chou: A 16KB LDPC engine already consumes a significant amount of silicon area and is quite sophisticated. For PCIe Gen7 controllers, our goal is to optimize and improve that engine from multiple angles rather than simply keep expanding it. We still need our architects to make the final call on exactly which improvements we will implement, but at this point we are more likely to refine and enhance the current design than to move beyond 16KB LDPC.

SSD controller development strategy

Anton Shilov: Speaking more generally, SSD controllers are increasingly becoming full platforms rather than just controllers, because integration matters so much. Do you expect close collaboration between controller vendors, NAND makers, and SSD manufacturers to become even more important as the industry moves to next-generation storage devices?

Alex Chou: I may not fully understand your question, but let me explain how we approach it.

At Silicon Motion, we design the controller architecture and build the firmware stack with a rich feature set. For example, we have developed our own [PerformaShape] traffic-shaping engine to improve QoS. That is the foundation of the platform.

From there, we have to look at how NAND evolves from one generation to the next. As we move from PCIe Gen5 to Gen6 to Gen7, controller performance has to scale accordingly. If you want to saturate the PCIe interface and deliver, say, 7 million IOPS today and much higher performance in future generations, you have to understand exactly where NAND is going.

That is why my team meets regularly with Samsung, SK hynix, SanDisk, Kioxia, and all other NAND vendors to review their roadmaps. Silicon Motion is part of that ecosystem, and because of those relationships, we usually get early visibility into future NAND generations and often receive early samples so we can bring up our controllers and make sure they take advantage of new NAND as quickly as possible.

That matters even more in the current supply environment. Because we work with all NAND suppliers, hyperscalers and cloud service providers can come to us and ask for a solution that is not tied to a single memory vendor. A company like Samsung naturally builds around its own NAND, but we have the advantage of being able to support multiple suppliers. That gives customers much more flexibility when supply is tight.

So yes, we have a core controller architecture and a common firmware base, but one of our strengths is that we work very closely with NAND vendors on future generations and make sure our platform can take advantage of faster interfaces, higher die counts, and new NAND capabilities as they arrive.

XL-Flash and storage-class memory

Anton Shilov: What about storage-class memory? Are there any developments there? As far as I can tell, adoption of Kioxia’s XL-Flash has been limited.

Alex Chou: That’s a very good question. I am actually going to visit Kioxia, so I should have a better sense of their plans after that. At the moment, Kioxia is essentially the only company still pushing XL-Flash, so they are trying to build something around it.

The challenge is that it is not just about the technology itself. You need a broader ecosystem to support it, and that is what makes the situation more complicated. We are watching it closely and trying to understand whether it is something we really need to support, but at this point I do not have a definitive answer. We are still evaluating it.

Anton Shilov: Have you heard anything similar from other suppliers? Quite a few memory makers used to talk about storage-class memory or similar technologies in their roadmaps.

Alex Chou: Based on what we know, not really. If you look back at last year’s Flash Memory Summit, several NAND makers were talking about higher-performance flash and storage-class-memory-like concepts. That created a lot of buzz at the time, and we looked into it, just as we have looked into XL-Flash, to understand whether there was a real ecosystem forming around it.

But there is much less discussion around those ideas now. One reason is simple: memory vendors do not really need those products at the moment because they can sell conventional NAND at very high prices and still generate strong returns.

Anton Shilov: In other words, they can just sell QLC 3D NAND and be perfectly happy.

Alex Chou: Exactly.

Anton Shilov: On the other hand, Nvidia wants storage devices capable of 100 million IOPS.

Alex Chou: Yes, that is where Storage Next comes in.

Anton Shilov: Has anyone actually come close to 100 million IOPS yet?

Alex Chou: I would say Storage Next gains many attentions. XL-Flash could be one possible approach to address that kind of requirement. But these are other options aiming to address high-performance and low latency needs.

What matters more is that Storage Next has a much stronger ecosystem behind it because Nvidia is actively driving it. There are regular meetings around it, and our architect has been involved from the very beginning. We have been tracking it closely and trying to make sure our future controller architecture can support it if and when the market materializes.

At the same time, Nvidia itself appears to recognize that 100 million or 200 million IOPS may not be realistic in the near term. The target seems to be moving closer to something like 50 million IOPS, which is more achievable. So yes, we are watching it very closely, and we are building in the flexibility to support it if needed.

In storage, having a technically interesting idea is not enough. The industry has to agree on how to use it, how to deploy it, and how to integrate it into systems. Storage Next currently has more momentum because the ecosystem behind it is much stronger.

Anton Shilov: So, you see Storage Next as more commercially relevant than storage-class memory, at least for now?

Alex Chou: Yes. At least today, Storage Next looks more immediate and more actionable.

We are already participating in those discussions and thinking about what future controller requirements will look like in that environment. That includes not only bandwidth, but also latency behavior, QoS, and the role storage plays in systems where GPUs are increasingly central to the data path.

That does not mean other technologies disappear. It just means that if you ask where the market is actively moving right now, the answer is much more on the Storage Next side than on the storage-class-memory side.

Anton Shilov: So, in practice, you make sure your controller works with all relevant NAND types, while the memory vendor mainly has to make sure the media itself complies with the interface requirements?

Alex Chou: When we design a controller, we already cooperate closely with NAND suppliers. Our architects look at all of the major vendors to understand whether there are any special requirements we need to account for. Then we handle another layer of optimization in firmware to make sure we can support all of those devices properly.

If you look deeper into enterprise NAND, most products also use interface chips internally to connect large numbers of dies. Those interface chips can differ from vendor to vendor, so we need to understand their configurations as well, including die counts, planes, and other architectural details. The goal is to make sure the controller and firmware together can support all of those different combinations.

So far, our architecture has been able to support NAND from SanDisk, Kioxia, SK hynix, and the other major vendors. Even if the interface chips differ, we try to keep the overall hardware design as flexible as possible.

There are really three elements involved: the controller itself, the hardware board, and the firmware. Ideally, you do not want a completely different board design for every NAND supplier. Fortunately, the industry has standardized a lot of the pinouts and module interfaces, which makes it possible to use a common hardware design and swap in NAND from different suppliers with the right firmware support.

We spend a lot of time making sure we can support all of those different combinations.

Anton Shilov: So you are effectively building controllers with a fairly clear view of what future NAND generations will look like.

Alex Chou: Exactly. We want to make sure that when the next generation of NAND arrives, we are ready to support it as broadly as possible.

Nvidia has just relaunched its five-year-old graphics card, the GeForce RTX 3060, in order to combat the component scarcity driven by AI. This resurrection has seen a staggered release, with companies like Gigabyte and Manli silently listing their renewed variants in different parts of the world. Today, Palit joined the list with an official announcement for its RTX 3060 Infinity 2 OC, the first official indication of Ampere's return.

If we take a look at the specs, the card is identical to the original RTX 3060 we saw in 2021 — it has 3,584 CUDA cores paired with 12GB of GDDR6 VRAM saturated across a 192-bit-wide bus. Since this is an overclocked variant, it can boost up to 1,792 MHz, which is less than 1% higher than the base 1,777 MHz boost that Nvidia already mandates. Palit will also release a non-OC variant of the Infinity 2 RTX 3060.

The card features a relatively simple design characterized by the typical black aesthetic we see on budget GPUs. There's no zero-RPM tech here, but Palit claims 0dB noise levels and says there's a "protective backplate" on the card that prevents PCB flex. When you're buying a GPU like this, its looks are probably the least of your concern; the main selling point is, of course, that 12GB memory pool.

Late last year, the PC hardware industry entered one of its most turbulent eras, characterized by production inadequacies created by the AI boom. Artificial intelligence demands a lot of memory and storage, and thus, commodity silicon has skyrocketed in price overnight with no signs of slowing down. After evading the crisis initially, GPUs eventually got wrapped up in the price hikes as well.

Nvidia's latest Blackwell family uses cutting-edge GDDR7 memory, which is even more expensive, and since vendors are busy producing HBM for fatter margins instead, the "solution" to this dilemma had to be creative. The idea for reviving older generation cards was actually floated by our very own Paul Alcorn at a Q&A at CES 2026, where Nvidia CEO Jensen Huang replied, saying he'd "go back and take a look at this."

Palit hasn't provided a price for the Infinity 2 OC yet, and we didn't see it listed on retailers yet, but we can infer it'll cost around $329 given similar variants have also been popping up for that price. To be clear, the RTX 3060 is a great value GPU that we praised even back when it launched. But in the face of the RTX 50-series, it's not exactly something you should consider first, especially when buying new.

You can get an RTX 5060 Ti for just $369 right now on Newegg, which is a significantly faster card with support for DLSS 4.5 and multi-frame gen, not to mention the better efficiency. It only has 8GB of VRAM, unfortunately, which hurts performance at high resolutions and if you like to play with ray tracing enabled. Still, unless you're going up to 4K, the 5060 Ti (and the regular 5060) will perform much better than a 3060 no matter what, as you can see in our GPU benchmark hierarchy.

Ultimately, rebooting the RTX 3060 makes sense from a manufacturer's point of view given the better yields of Samsung's older 8nm process compared to TSMC's more expensive N5 node used by Ada and Blackwell. But as a consumer, you should definitely stick with the RTX 50-series or try to find a used RTX 40-series GPU instead.

There’s a new remake of the legendary Gravis Ultrasound ISA soundcard on the block with the arrival of the open-source Beavis Ultrasound project. Developer schlae shared details of this amusingly named mid-90s-cultural phenomenon portmanteau, Beavis Ultrasound PnP ISA Sound Card Replica, on GitHub on Monday. The repository includes complete KiCad schematics, PCB layout, sample ROM, reverse‑engineered GAL logic (for an operational IDE CD-ROM interface), assembly notes, and more. You’ll still need to source an old AMD AM78C201 InterWave chip to complete this DIY project, though.

The appeal of the new Beavis Ultrasound is nicely summed up by schlae, as they explain that “unlike other clones, this design includes the entire schematic as well as the reverse-engineered source code of the GAL.” This GAL provides transparent and reproducible logic and is key to this project being able to handle IDE connectivity, like original Gravis Ultrasound (GUS) PnP cards. And, yes, this is not a GUS Classic or MAX clone, but caters to enthusiasts wanting a clone of the more complex and advanced GUS PnP.

A particular strength of the Beavis Ultrasound is its authenticity. It could be described as a faithful hardware‑level reproduction rather than a functional approximation. No microcontrollers take the place of real hardware here; there’s no emulation software, and features like the aforementioned GAL logic and IDE interface aren’t swerved by the developer.

However, this authenticity could also be an Achilles heel, as you’ll need to source an old AMD AM78C201 InterWave chip to complete a Beavis Ultrasound build and enjoy once again its marvelous sound. Actually, there’s another point to note before following schlae’s plans. There are no tried and tested footsteps to follow at the time of writing, as the dev admits they “have not actually fabricated the board and tested it for functionality,” so interested parties are instructed to “build this board at your own risk.”

If you aren't an open-source or hardware-only purist

In recent weeks, we also reported on the return of the Orpheus II ISA soundcard due to “popular demand.” This device includes some GUS functionality but is a commercial, non-open-source proprietary product. Probably the most popular DIY-able solution around would be the PicoGUS, built around a Raspberry Pi Pico (RP2040) microcontroller, which handles all its GUS‑compatible audio playback in software – eschewing the need for rare vintage components like the AMD Interwave.

ChangXin Memory Technologies (CXMT), China's largest DRAM maker, is on track to match Micron's production capacity in 2026, if Citrini Research's forecasting models are correct. If this happens, China will become the world's second-largest DRAM production base in the coming years.

The bottom-up model estimates that CXMT will finish 2026 with approximately 350,000 wafer starts per month (WSPM) of DRAM capacity, which is just 25,000 WPM less than Micron. According to the analysis, the federal government is pushing CXMT to share its DRAM technology with JHICC, Swaysure, and YMTC's subsidiary XMC to ease domestic shortages. All three companies have either built DRAM capacity already, or will do so in the short-term future, the report claims.

Swaysure has completed construction of a 140,000-WSPM fab in Shenzhen, while JHICC's Jinjiang complex contains enough cleanroom space for 120,000 WSPM, and the initial 60,000-WSPM phase is expected to receive equipment by the end of 2026. YMTC is also projected to operate about 50,000 WSPM of DRAM production at Wuhan Fab 3. If all these facilities initiate operations in the coming years, then China will have a total DRAM capacity of 600,000 WSPM (not counting Samsung's and SK hynix's fabs in China), which is dramatically lower compared to South Korea, but ahead of Japan, Taiwan, and the U.S. combined.

But China is not going to stop developing its DRAM industry, and by 2030, its total capacity will increase to around 1.41 million WSPM, according to Citrini. CXMT alone is projected to build new production capacities in Beijing, Hefei, and Shanghai, to expand its production capability to 950,000 WSPM in 2030, assuming everything goes as planned.

The supply model assumes that about 400,000 WSPM of CXMT output will remain on D1a, another 400,000 WSPM will migrate to D1b, and roughly 150,000 WPM will produce D1c devices.

Enough fab tools?

Citrini admits that producing China's outlook is considerably more difficult than predicting the development of established DRAM makers. On the one hand, there is rapidly expanding fabrication infrastructure in China, abundant state-backed financing, and government-directed technology transfers. On the other hand, among the key near-term limitations remains lithography equipment availability, particularly if the proposed MATCH Act restricts sales of advanced immersion DUV tools to select Chinese companies.

However, the author expects SMEE's domestic immersion DUV scanners to enter volume production around late 2026 or early 2027 following beta testing, as well as SiCarrier/Yuliangsheng introduce its own production-ready DUV platform in 2028. Perhaps a bit optimistically, the analysts predict that availability of lithography tools is not expected to constrain Chinese production beyond 2028, at least for mature logic and DRAM nodes. Yet, for obvious reasons, if the MATCH Act works as planned and disrupts supply of advanced immersion DUV tools to DRAM makers, production capacity expansions will not occur in the next couple of years, the report suggests.

Still, both SMEE and SiCarrier will need time to ramp up production of their lithography systems, whereas DRAM makers must learn how to use them efficiently, so we would not be as optimistic as the authors and would not expect Chinese tools to produce meaningful DRAM volumes before the early 2030s. Still, the key takeaway here is that China is on track to become a major DRAM maker rather sooner than later.

Unprecedented demand

Citrini Research projects total DRAM demand to reach 157.5 exabytes (EB) per year by 2030, including 75 EB of commodity DRAM for agentic AI CPUs, 25 EB of commodity DRAM for conventional cloud servers, 20 EB of commodity DRAM for client devices, and 37.5 EB of HBM4E as well as HBM5 for AI accelerators (15 EB and 22.5 EB, respectively).

Meanwhile, Citrini expects the whole industry to only produce around 37.5 EB of HBM4E/HBM4 memory (mostly by Micron, Samsung, and SK hynix) as well as 91.3 EB of commodity DRAM (including output in China) in 2030, leaving a deficit of 28.7 EB, or roughly 25%.

That said, the rapid expansion of DRAM production in China could be the industry's best hope to maintain relatively low prices of memory, something that will be particularly beneficial for the market of consumer devices that are sensitive to memory prices, analysts from Citrini believe. Yet, the author argues that most of this new capacity would satisfy China's own demand rather than eliminate the global shortage. Furthermore, even if companies like CXMT can expand their fabs faster, that additional capacity will mostly be consumed by domestic needs, according to Citrini.

It should be noted that to make more memory, DRAM makers need more fab tools, primarily 193nm immersion scanners. Yet, companies like ASML, Canon, and Nikon cannot increase output of immersion DUV systems quickly as these are extremely complex machines containing tens of thousands of parts. While Chinese memory companies certainly pin their hopes on local producers like SMEE and SiCarrier, neither has delivered a single commercial immersion system, and after they do, it will take them years to ramp up production of such tools.

Samsung is back with another solid-state drive, and this time it's something a little bit different. The 990 is a QLC-based 990 EVO Plus, positioned as a budget drive that can still push a lot of bandwidth. It’s a little late to the game and not quite what was rumored for the 990 QVO, but it does bring some new technology to the table. We’re always interested in seeing what Samsung puts out, and this time is no different. It should not be confused as being part of Samsung’s Pro line or, for that matter, the EVO line, so keep that in mind.

The drive has its ups and downs, but in this challenging market, and for a budget drive, that’s to be expected. Samsung is still well-regarded for its name and reliable hardware, even as there has been a massive push towards enterprise, away from the consumer side. Samsung has, in fact, given some ground in the SSD space for many years, even as it produces some of the most common OEM drives. So while this is not a Crucial situation, it’s best to jump into this review with the right expectations about what this drive is and isn’t. It’s a budget drive with full Gen 4 throughput that hits the most common capacities with sufficient performance and power efficiency. It’s not meant to be a throne-taker.

It’s also thankfully not another 990 EVO situation – that drive felt somewhat underwhelming by the time it arrived, even when pitted against budget drives – but the 990 is also not a QLC rallying call. It’s a competent drive that mostly hits the right notes, as intended. Given how scarce Samsung QLC drives have been, and how much demand its QLC flash surely has elsewhere, it can feel like Samsung is throwing consumers a bone, though it would be crass to put it that way. We instead think this is smart positioning by the company as it knows the future is with QLC and the technologies used in this flash (even if first shown two years ago at ISSCC) point firmly at an ambitious future. The 990 just lets you own a piece of that.

Samsung 990 Specifications

The Samsung 990 is only available at 1TB and 2TB capacities, with MSRPs of $269.99 and $529.99, respectively. These prices are very high, as you can get competing drives like the Crucial P310 for substantially less, and in fact even the TLC-based WD Black SN7100 costs less. But Samsung has historically launched with MSRPs well above actual market price. You should be able to get the drive at significantly lower prices after launch, but the “Samsung tax” may still apply. We’ll get into what that means throughout the review.

This limited capacity range is unfortunate, but enables Samsung to pack the flash into just one package, which reduces PCB space so that any OEM variant can be used in multiple M.2 form factors and will always be single-sided. Less than 1TB is also not enough for these denser dies if you want good performance. That leaves 1TB and 2TB as the target capacities, which also makes sense in a market where 4TB+ is getting exceptionally expensive. We’ll eventually see 2Tb dies to make single-package 4TB a reality, but that’s further along in Samsung’s roadmap.

The drive can reach 7,250 / 6,450 MB/s for sequential reads and writes and up to 850K / 1,200K random read and write IOPS. Peak performance is attained at 2TB, where you have the optimal amount of interleaving or parallelization: Sixteen 1Tb dies means four dies for each of four flash channels, the typical ceiling. However, as these are four-plane dies, you still get 32-way interleaving at 1TB with eight dies, which is enough to get good performance with just two dies per channel. Less than that is much less ideal, and more than that introduces additional overhead, especially for budget controllers. The math changes with six-plane and 2TB dies, but for this flash, 1TB is the reasonable minimum, with 2TB offering the best performance.

The drive is rated for approximately 4W of power draw across the two capacities, when looking at both reads and writes. Check our power results below to see how accurate that is. The drive is rated for 400TB of writes per TB capacity, which is high for QLC flash – we would typically see maybe 300TB, which is one-half of the TLC standard – but also indicates a very high drive writes per day (DWPD) rating. This is due to the warranty only covering three years rather than the normal five, so the amount of writes per year is significantly higher. This is atypical, so requires further explanation.

For those who live for TBW and write endurance, this illustrates why TBW often looks better on paper. Spreading 400TB over three years works out to roughly double the daily write allowance of a typical 300TBW / five-year QLC drive. Most people will never approach either number, and they will live with the shorter coverage window. However, if you intend to hammer the drive with writes to the point of exceeding TBW within the three-year warranty period, then this could be good. Although you really shouldn't use a budget DRAM-less QLC-based drive for that type of workload. However, that option exists and is rarely the case with a QLC-based drive. As a final note, the drive does support TCG Opal 2.0 for encryption.

Samsung 990 Software and Accessories

Samsung’s Magician software is the gold standard for consumer SSDs. This is an SSD toolbox with all the features you need. It displays system and drive health information, including SMART, and checks whether your drive is legitimate. You can also benchmark your drive and use any optional features, such as encryption. The software is also essential for keeping the drive’s firmware up to date, although you can also download that from the first link.

Samsung 990: A Closer Look

The 990 has an SSD controller, a single NAND flash package, and power management circuitry. There is no DRAM package present. This is a single-sided drive, which is ideal for compatibility and cooling. There is a lot of free space on the PCB, and by putting distance between the controller and flash, there is separation to mitigate component heat generation. This would also help if a heatspreader or heatsink were to be added. Without this space, the drive could be sold in a shorter form factor, which is particularly useful for OEM drives.

The label has information about the drive, such as the date of manufacture (DOM), model, serial, the PSID, and the power rating. We always caution that you not take certain drive information as being conclusive about the hardware. For example, you should not assume TLC or QLC flash from a drive’s TBW. Likewise, you shouldn’t rely on the labeled power rating – and this is done more often on M.2 2230 drives for portable devices – as any indication of drive power efficiency. Here we have 3.3V / 1.85A, which indicates potential power draw over 6W. Now, the power ratings given on spec sheets will often be average and not peak, and will be separated as read or write rather than mixed. In fact, this drive’s load power states can reach a peak of 5.90W via SMART, which is much above the rated average ~4W. We track both peak and average in our testing.

We always enjoy reviewing Samsung drives with a focus on the technicals, as the manufacturer remains a leader in many ways. The 990, in particular, requires some extra description to be fully appreciated. Simply looking at the benchmark results might make the technology seem underwhelming – to be honest, this is very much a budget drive, even taken in the best light – but that doesn’t mean Samsung phoned this one in. In fact, there are signs of deliberate design here, and some of the decisions could help sell this drive. Samsung still has to get the pricing right, of course, but what else is new?

Let’s start with the controller. The 990 is using the PiccoloQ, which is the QLC flash version of the Piccolo. The Piccolo is utilized on the 990 EVO and 990 EVO Plus, two TLC-based drives. In all cases, it’s a four-channel, DRAM-less design, which limits performance and capacity. In both cases, the controller takes up to 2,400 MT/s flash – this is more than enough to saturate PCIe 4.0 – and the interior design is the same. This means it’s a Samsung 5nm part with multiple ARM Cortex-R8 cores and a single R5 core. If the Piccolo stands out in any way, it’s that it offers a PCIe 5.0 x2 option in addition to the standard 4.0 x4 interface. This option or mode has limited usefulness, though, and nothing in the 990 would change that if enabled for the PiccoloQ.

So, not much new on the controller front, but the use of this controller at the 990’s rated speeds does give us some more information. Namely, we know the 990 EVO runs more slowly because it’s using flash slower than 2,400 MT/s, 1,600 MT/s Samsung V6P TLC, to be precise. If we look at Samsung’s V7 QLC flash, it can run at that same speed. This is why the originally speculated 990 QVO with that flash was targeted at the same speeds as the 990 EVO. Things have changed since then. This drive could have been the 990 QVO, but with the EVO and EVO Plus lines going DRAM-less this generation, we suspect the QVO tier was “promoted” to the plain 990 name, and the 990 now targets the 990 EVO Plus's specs

The evidence to back this up, which also supports the loose 990 QVO rumor, is that Samsung does have a V7 QLC OEM drive: the BM9C1. This is the cousin to the PM9C1 line with OEM 990 EVO and 990 EVO Plus (PM9C1b) variants. The BM9C1 is available down to M.2 2230 and uses the same PiccoloQ as the 990 (the QLC version of the 990 EVO/EVO Plus’s Piccolo). It’s just limited to the same speeds as the 990 EVO, as it’s running at 1,600 MT/s. We have to be careful here, though, as Samsung’s V9 QLC press release indicates a 60% I/O improvement, which, with the V9 being 3,200 MT/s, suggests a 2,000 MT/s ceiling for the V7 QLC. Since there is an OEM TLC-based drive in between the 990 EVO and 990 EVO Plus (the PM9C1a) at 2,000 MT/s, the possibility for a ~6 GB/s 990 or 990 QVO with V7 QLC existed.

Before we dive more deeply into the flash, since we haven’t seen the new Samsung QLC in a while and there is some neat tech here, let’s decode the module. “K9” tells us it’s Samsung NAND flash memory. “YYG” indicates it’s a QLC flash package with sixteen dies (HDP) in a 2TB configuration, which confirms 1Tb dies. “Y8” means it’s 8-bit, J tells us the voltage, “5” tells us the number of chips enabled and ready/busy signals, and “D” tells us the generation. With V7 being “C” and V8 skipped, this suggests V9. The second part of the code tells us how the flash is packaged and that it’s commercial / consumer-grade. While you aren’t expected to know how to read codes on your SSD, knowing how it works can be useful, especially with Samsung drives, even if it’s just a matter of trying to figure out if you have a counterfeit product.

So let’s talk about the flash. This is a 286-Layer part, technically, but is sold as 280-Layer once accounting for source/ground and dummy lines. Dummy lines are usually at stack edges, as the physics of flash can make these lines otherwise unusable. A higher layer count – Samsung’s V7 is only 176-Layer, although technically 191 layers – generally means higher bit density. Bit density is key to scaling NAND flash, which is acting as capacious, non-volatile storage media. This can be disappointing to some because it means you don’t always see any real performance scaling as the layer count progresses.

Fitting more flash into the same space can mean less room for charge in each cell, which makes it harder to optimize for performance if you’re trying to maintain the same endurance level. That is certainly the case with this flash, as the performance only manages to match that of last-generation 176-Layer QLC flash from competitors, which is why we want to go out of our way to point out Samsung’s design decisions and why it leans innovative in ways you won’t see in, say, your game load times.

For one, when we talk about the layer count difference – reported versus actual – you also get an efficiency number that is the ratio between usable and total word lines. Samsung is a leader here, with high layer efficiency. Samsung also has held off using three decks or stacks of flash and is still at two, due to having superior channel etching – it’s able to drill down more layers with a higher aspect ratio. It’s also possible to run lines through the flash itself rather than rely largely on masked steps, which sets the stage for Samsung scaling to extremely high layer counts. One issue with high layer counts is that you start losing uniformity from layer to layer, and Samsung accounts for this with optimized word line spacing, too. So, as we’ve said in the past, it often feels like Samsung is falling behind on layer count, but in reality it has a very focused strategy and the best technology in the business, and we can see this with the 990’s flash.

For the consumer, though, the 990 is a little bit weird. This is presumably 3,200 MT/s flash that is being “wasted” with a 2,400 MT/s controller. This flash has amazing bit density, but having a single sixteen-die package at 2TB is nothing new. What about performance? Samsung has made optimizations to improve performance on this flash, but nothing amazing. This QLC is only comparable to the competition in performance terms, particularly at 2,400 MT/s. Samsung is playing catch-up, but we also think this is a case of designing for enterprise rather than consumer.

QLC flash is now highly sought after in enterprise for its density, and Samsung’s optimizations all benefit that kind of environment. In fact, from a consumer’s perspective you could look at this V9 QLC as being focused on higher bit density – but no 2Tb dies – and you would largely be correct. Samsung’s V9 QLC is 86% more dense generationally and about 94% more dense than the competition’s 176-Layer QLC flash.

We’ll take a look at one new technology in the V9 QLC flash to illustrate. One important consideration is flash power interruption leading to data loss, which, without power loss protection (PLP) means you are looking at protecting data at rest. This is on the non-volatile media or flash, not the volatile memory like DRAM. When folding from the pSLC cache to the native flash, data loss is not an issue because you don’t invalidate the original pSLC copy until the write has been verified. However, when writing to native QLC, you are writing multiple pages where the upper pages will require higher levels of sensitivity for proper reading. There are different methods of writing to QLC flash, but generally multi-bit flash has multiple write passes that go from fuzzy (coarse) to precise (fine), and lower pages write faster and may be complete first. Therefore, it’s important not to ruin existing lower-page data if you lose power while still adjusting voltage for the upper pages.

Micron has a unique way of dealing with this using a differential engine that can predict values from partial shifts, but a more common method is simply to back up or buffer the values in nonvolatile flash. QLC stores four bits per cell, so a full backup means writing four bits of pSLC per cell. pSLC is used because its writes are fast, whereas QLC's upper-page writes, in particular, are an order of magnitude slower. Samsung reduces the buffer to a single parity bit by using an odd/even algorithm, creating a sensing window that’s more like TLC (8-state) than QLC (16-state). This improves performance, endurance, and bit density. Some of that performance is still lost for higher bit density. For consumers, the direct benefit is higher TBW, but we speculate the higher density is aimed more at enterprise and future flash generation products. This is in part a response to Solidigm’s floating-gate design, a different technology than charge trap, with tighter charge placement.

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Comparison Products

The Samsung 990 enters a crowded market with a lot of good options, at least in theory. If we’re looking at QLC-based drives, this means the Crucial P310 and Sandisk WD Blue SN5100 at the very top. Both of these drives perform incredibly well. Below that, we have the older wave of drives represented by the TeamGroup MP44Q. That drive in particular remains a budget favorite with a fast controller and good QLC flash.

We would put the rest below that, even though the hardware is not always worse. This would include the Biwin M350, the Kingston NV3, and the Seagate FireCuda X1070. These drives are using alternative controllers – SMI, SMI, and TenaFe, respectively – that are roughly comparable, and the flash is not particularly old, either. However, these drives tend to be more budget-focused with reduced performance and (ideally) reduced cost.

We’ve also thrown in Samsung’s 990 EVO and 990 EVO Plus for comparison. The 990 should be closer to the latter, but with QLC flash, it would be okay landing somewhere in between. On the whole, we would expect the drive also to be between the two main categories of drives – that is, above the budget ones, below the two fastest, and closer to the middle MP44Q and its MAP1602-equipped alternatives, but with Samsung’s name recognition. The technology is here to make this a reliable drive, which is also a factor to consider, but being this late to the game puts the 990 at a general disadvantage.

Trace Testing — 3DMark Storage Benchmark

Built for gamers, 3DMark’s Storage Benchmark focuses on real-world gaming performance. Each round in this benchmark stresses storage based on gaming activities including loading games, saving progress, installing game files, and recording gameplay video streams. Future gaming benchmarks will be DirectStorage-inclusive and an evaluation for future-proofing is included where applicable.

We start by looking at 3DMark because, frankly, QLC-based drives make a lot of sense for gaming. Aside from large installs and updates, you’re mostly doing reads, which do not favor TLC drives as much. While it’s true that QLC flash is still slower, often-accessed data might be left in the pSLC cache – if you leave enough space free – and QLC is also optimized for random reads. Games do involve a lot of sequential reads and often at larger block sizes than you’d expect, but as long as the drive has sufficient interleaving (it’s sufficiently large) you are going to get pretty good performance.

For 3DMark, which is a synthetic test, we might expect the drives to perform as they do under ideal, cached circumstances. This means the 990 should perform closely to the 990 EVO Plus and better than the 990 EVO, even though both of those latter two are TLC-based. It does. The 990 gets pretty close to the P310, which is one of the best QLC drives out there, aside from the Blue SN5100. We tend to look at ~45µs as a good cutoff point for all-around performance – gaming doesn’t need to be super responsive – which is roughly around the popular budget NV3. The 990 is significantly faster than that, which is all you could ask for here.

Trace Testing — PCMark 10 Storage Benchmark

PCMark 10 is an industry standard trace-based benchmark that uses a wide-ranging set of real-world traces from popular applications and everyday tasks to measure the performance of storage devices. The results are particularly useful when analyzing drives for their use as primary/boot storage devices and in work environments.

PCMark 10 performance usually, but not always, follows 3DMark. There is speculation that some drives or firmware may be optimized for benchmarks like PCMark 10, but taken within a greater suite of tests it’s still useful to get a feel for application performance. For us, that means for a primary drive – your boot or OS drive where your apps live – or for your everything drive, if you work and game on a single drive in your system. This isn’t too unusual with laptops where M.2 slots are limited.

The 990 again ends up roughly where we’d expect – above the 990 EVO, and close to the 990 EVO Plus. It’s not on the level of the P310 or Blue SN5100, but it’s clearly above the budget drives. This is a strong result with good latency. For instance, we would take the 990 over the NV3 any day, every day. On the other hand, the P310 and Blue SN5100 are frankly better drives. These two drives are better optimized and performance-oriented. The 990 is more of a gap filler that’s late to the scene.

We have to say, though, that we’re glad Samsung didn’t push out a 990 QVO that was more like the 990 EVO, even if it would have arrived earlier. Such a drive would have used older QLC flash and performed more slowly simply due to the lower interface speed.And frankly we’d rather have density-optimized flash that can run at the 990 EVO Plus level. That’s what the 990 delivers, even if it feels a little underwhelming. However, it makes perfect sense given the current market, enterprise demand, OEM demand, etc. The drive is still very fast and of a superior quality to a great many budget drives out there, and that makes it worthwhile.

Console Testing — PlayStation 5 Transfers

The PlayStation 5 is capable of taking one additional PCIe 4.0 or faster SSD for extra game storage. While any 4.0 drive will technically work, Sony recommends drives that can deliver at least 5,500 MB/s of sequential read bandwidth for optimal performance. Based on our extensive testing, PCIe 5.0 SSDs don’t bring much to the table and generally shouldn’t be used in the PS5, especially as they may require additional cooling. Check our Best PS5 SSDs article for more information.

Our testing utilizes the PS5’s internal storage test and manual read/write tests with over 192GB of data, both from and to the internal storage. Throttling is prevented where possible to see how each drive operates under ideal conditions. While game load times should not deviate much from drive to drive, our results can indicate which drives may be more responsive in long-term use.

You know our PlayStation 5 line by now: just about any drive will do. The 990 can push more bandwidth than the 990 EVO, which arguably makes it a better pick. It’s on par with, or better than, most budget drives out there. At least, for the things you will usually be doing on the PS5. It’s clear from our one bandwidth test that the drive ran out of cache, and it has the typical slow QLC flash write state. This is not indicative of real-world performance if you do normal installs/updates with mostly reads. If you are freshly installing the drive and moving a ton of games onto it, then yes, this could be an issue, but the QLC write speeds are still significantly faster than 1GbE if you’re intending only to download a ton of games at once. Otherwise, you can check the cache size in the relevant testing section.

Transfer Rates — DiskBench

We use the DiskBench storage benchmarking tool to test file transfer performance with a custom 50GB dataset. We write 31,227 files of various types, such as pictures, PDFs, and videos to the test drive, then make a copy of that data to a new folder, and follow up with a reading test of a newly-written 6.5GB zip file. This is a real-world type workload that fits into the cache of most drives.

We also see some write performance issues in DiskBench. This is dependent on cache size and speed, but for the most part should be limited by the interface speed. However, there are cases where copy speed will simply be slower, whether due to the controller or other optimization trade-offs. We can see that the 990 EVO, with TLC flash, is not exactly doing great here, and the 990 EVO Plus does much better. However, the 990 lags behind, and is very far behind the P310 and Blue SN5100.

So, we can put some of this slow speed on the Piccolo/PiccoloQ controller. To avoid getting too technical on this, we suspect it is partially architectural. This is reflected in power efficiency, as both the P310 and Blue SN5100 – with the Phison E27T and a proprietary Sandisk controller, respectively – are significantly more power-efficient than the 990 EVO, 990 EVO Plus, and as we’ll discover, the 990 as well. We also know that Samsung’s V9 QLC flash is not particularly inefficient.

As for the controller, there are reasons to design it differently. Reliability is one reason, especially if you sell a lot of OEM and enterprise drives that share the technology. Scaling is another, as you may use similar technology across your stack. You might want to optimize for a different sort of performance baseline; you may have unique endurance requirements, and you also might have to keep capacity in mind – enterprise drives, in particular, could make better use of this flash’s interface speed when scaling for capacity. Therefore, DiskBench results for our specific testing may not really be what Samsung is optimizing for, in which case the 990’s performance more or less hits expectations based on the 990 EVO and 990 EVO Plus. It just disappoints against drives like the NV3, which are otherwise inferior.

And to put a cap on it, yes, this is a consumer drive, but if you go back and read our 990 EVO review – and other recent Samsung SSD reviews, for that matter – you will see we underlined the idea that Samsung has been late to the party with less-than-leading performance recently. The fact is, Samsung has and has had bigger fish to fry, and its technology is sound but no longer looks amazing on the standard consumer benchmarks. That makes its products less relevant if you just want the fastest drive, although we’d argue there are secondary effects like drive reliability that still keep Samsung in the fight, certainly as an OEM option. It’s also true that consumer use has a lower bar – any halfway-decent NVMe drive is fast enough for daily driving – which means, sometimes you’re just buying the Samsung name.

Synthetic Testing — ATTO / CrystalDiskMark

ATTO and CrystalDiskMark (CDM) are free and easy-to-use storage benchmarking tools that SSD vendors commonly use to assign performance specifications to their products. Both of these tools give us insight into how each device handles different file sizes and at different queue depths for both sequential and random workloads.

ATTO gives us a clear image of how a drive performs over a range of block sizes. This can relate to different file sizes, for example, you probably have many files at or below 4KiB in size for various things but larger files, archives, and media files will usually be in units of MiB. Depending on what you’re using the drive for you may want to pay attention to how a drive performs within a certain range. For the quickest comparison, we show the results on a logarithmic scale and, there, the 990 shows significant dips for reads between 64KiB and 1MiB.

What you need to know is that flash is interleaved to improve performance, which means that larger I/O sizes will show higher throughput. A single, four-plane die, with modern 16KiB pages, can interleave up to 64KiB internally. If you have one die per each of four channels, that’s 256KiB. If you parallelize that over four dies per channel – which is the ideal amount and what we have with the 2TB 990 – then you reach 1MiB. While alignment here can impact performance, for example we sometimes look at six-plane flash these days, in general you will see a gradual throughput increase as you go. You’ll see this beyond 1MiB as data can and will be cached in volatile memory, either system-side or in a small cache on the drive. If you’re looking at higher queue depths, which we do with CrystalDiskMark, performance saturates even further as the controller is able to optimize data placement and retrieval with knowledge of what’s coming.

What this usually means is that QD8 is enough to get drives close together, while there will be more disparity at QD1. QD1 is much closer to real-world, as most operations will be at low queue depth, the vast majority at our below QD4 and the majority at QD1 or QD2.

We see that the 990 matches the P310 with QD1 reads, while some drives, like the X1070, do surprisingly well. We can assume that the controller plays at least a partial role here. The X1070 is a good example because, let’s be real, it’s not a drive a lot of reviewers liked. Yet, it has pretty good performance in this instance, indicating it could be a solid secondary storage drive. Fair enough. The 990 just doesn’t really have the response we like to see for that, but it’s fast enough to remain relevant. We got the impression in our X1070 review that its controller was chosen for cost savings and that was plenty for daily use, but we don’t think Samsung cheaped out on the PiccoloQ. Rather, Samsung is looking at the bigger picture, as it also sells drives with the Piccolo controller, including its OEM offerings.

Random latency seems much more important to a lot of people. We generally find that sub-50µs is one bar and another is sub-45µs. The 990 manages the former, which puts it above last-gen drives and some earlier Gen 4 drives, and budget drives like the X1070. It’s in the same ballpark as the NV3, too. It’s sufficiently far behind more popular budget drives, though, to draw our interest. In most cases you won’t notice it, but if you’re using this as your only drive and are sensitive to that, it’s not your best option. On the other hand, we think you have to balance that against pricing and some management of expectations. Any modern SSD is going to be very fast, and with current pricing it might be worth putting more weight on reliability, for example.

Sustained Write Performance and Cache Recovery

Official write specifications are only part of the performance picture. Most SSDs implement a write cache, which is a fast area of pseudo-SLC (single-bit) programmed flash that absorbs incoming data. Sustained write speeds can suffer tremendously once the workload spills outside of the cache and into the "native" TLC (three-bit) or QLC (four-bit) flash. Performance can suffer even more if the drive is forced to fold, the process of migrating data out of the cache in order to free up space for further incoming data.

We use Iometer to hammer the SSD with sequential writes for 15 minutes to measure both the size of the write cache and performance after the cache is saturated. We also monitor cache recovery via multiple idle rounds. This process shows the performance of the drive in various states including the steady state write performance.

Samsung’s TurboWrite 2.0 caching technology utilizes a fixed, static portion of pSLC combined with a much larger dynamic portion. These two zones have unique characteristics which, when taken together, ideally keep the drive feeling fast across a variety of workloads. The static portion ensures the drive always has some cache for random writes, while the dynamic portion varies with drive usage so that you always have ample cache. While the 990 EVO had 108GB total regardless of capacity, it’s more typical for Samsung to increase both caches in absolute terms as capacity goes up. This is the case with the 990 EVO Plus, which has a 216GB cache at 2TB. But we know from our 9100 Pro review that Samsung is quite capable of going with a larger cache. The general trend for consumer SSDs has been to go that way, especially for QLC-based and DRAM-less SSDs, as it better hides weak performance states.

Therefore, it’s not too surprising that the 990’s cache is pretty large. In its fastest state, it writes at almost 6.1 GB/s for over 57 seconds, for a cache in excess of 350GB. This is larger than the 2TB 990 EVO Plus’s but smaller than the 2TB 9100 Pro’s. Our suspicion is that the 990 follows the newer, larger scheme, but we’re dealing with QLC rather than TLC flash. QLC flash to pSLC is 4 bits to 1, while TLC is 3 bits to 1, so in relative terms the 990 lines up with the 9100 Pro. That’s all fine and good. As for how fast it writes, Samsung markets the 990 as having over 50% faster write performance than the 990 EVO, which is accurate simply because we’re moving from 1,600 to 2,400 MT/s, with newer flash and firmware.

Once the cache is exhausted, the drive has to write to the native QLC flash directly or fold data over from pSLC to QLC. The latter is slower but can reduce wear in some cases – folding uses predictable, sequential writes – and reduces the likelihood of errors in transmission. Considering the technology we mentioned above and how Samsung avoids problems with power loss, it makes sense that going slower is by design. In fact, given we know the expected speed of the flash – rated at 41 MB/s per die – we can reasonably assume the firmware wants this outcome. It’s not that the flash can’t handle higher speeds, even at the risk of endurance. It’s simply that for a consumer drive of this type, the response is reasonable and measured. Going faster would require reducing the cache size potentially, which tends not to be a good trade-off for this type of drive.

One interesting thing about the V9 flash is that it can operate in a pTLC caching mode. We don’t see that here. Honestly, that’s not too surprising: Solidigm’s 5-bit PLC flash effectively was designed to run as QLC/pQLC for enterprise, so it’s possible this pTLC mode was for cases where you might need that higher level of performance or endurance. After all, this is extremely dense flash even in such a mode, which points more at enterprise use.

We’ve seen QLC flash from Kioxia also optionally have this mode – and for that matter, Solidigm’s PLC can do pTLC, too – in the past, but that mode doesn’t appear to be designed for consumer use. There may be other reasons for not using it in a consumer product, such as power optimization, as consumer workloads probably benefit more from a straight pSLC and native/QLC hybrid.

Power Consumption and Temperature

We use the Quarch HD Programmable Power Module to gain a deeper understanding of power characteristics. Idle power consumption is an important aspect to consider, especially if you're looking for a laptop upgrade as even the best ultrabooks can have mediocre stock storage in terms of capacity and performance. Desktops are often more performance-oriented with less support for power-saving features so we show the worst-case for idle.

Some SSDs can consume watts of power at idle while better-suited ones sip just milliwatts. Average workload power consumption and max consumption are two other aspects of power consumption but performance-per-watt, or efficiency, is more important. A drive might consume more power during any given workload but accomplishing a task faster allows the drive to drop into an idle state more quickly, ultimately saving energy.

For temperature recording we currently poll the drive’s primary composite sensor during testing with a ~22°C ambient. Our testing is rigorous enough to heat the drive to a realistic ceiling temperature but real-world temperatures will vary due to the environment and workload factors.

Is the 990 power-efficient? Samsung markets the drive as being 38% more efficient than the 990 EVO – or that it cuts power consumption by 38% – which, technically, works with our numbers. It’s not a huge bar to hit as the 990 EVO was not very power-efficient. Even the X1070 is significantly more efficient! The 990, unfortunately, really doesn’t do well against other drives in its class, regardless of flash. We can’t chalk this up as being fully due to the controller because the 990 EVO Plus does well enough for itself.

This is actually expected since, for example, the Blue SN5100, which is using BiCS8 QLC, is less efficient than its BiCS8 TLC sibling, the Black SN7100. QLC and TLC flash of the same generation often have significant differences. TLC flash saw six planes first while QLC tends to be optimized for density. While it’s true that pSLC performance between the two is often comparable, behind the scenes the drive still has to deal with wear-leveling, garbage collection, and other maintenance with block granularity. QLC is slower, with larger blocks and pSLC taking more bits. So all else being equal, TLC often outshines it in power efficiency.

Our impression here, as is the case elsewhere in the review, is that this flash is basically V7 QLC with twice the density. Samsung uses impressive tricks to get it there; the flash is technically a bit faster and more efficient, and it has some neat changes that mostly apply to enterprise. This means you can have the 990 doing worse than the 990 EVO Plus with its V8 TLC. This is not perplexing. QLC flash is made for bit density, and Samsung intends to scale flash for a very long time. It also skipped V8 QLC for a reason. This doesn’t endear it to people wanting to buy this drive for laptops, although we assure you that this does use some cutting-edge technology, and we do think it should be very reliable. It’s just not going to be as efficient as you might expect.

Samsung is cognizant that its drives will end up with OEM variants in laptops and in many cases, shorter form factors. The 990 EVO wasn’t a great laptop drive due to its heat generation, but it works. The 990 is significantly better, so it, too, will work as a laptop drive. We think this drive deserves a heatsink in a desktop or PS5, and probably should have heatspreading of some sort anywhere else, if at all possible.

The question is, will it overheat? In our testing, we found that it got closer than we prefer to that point. Our maximum reported controller temperature was high relative to the initial throttling temperature, but a true composite value would be lower. Even so, the controller did get warm. On the other hand, our Iometer testing is far from real-world. We push our drives hard. This is not the sort of drive for a desktop replacement or high-end laptop in our opinion, although we think with typical workloads it’s perfectly fine. After all, the results here are better than the SK hynix Gold P31, which is a laptop staple. By all means, in a Gen 3 slot this thing will fly. If you’re hammering it at Gen 4 speeds, though, yeah, it’s not the coolest drive in town.

Test Bench and Testing Notes

We use an Alder Lake platform with most background applications, such as indexing, Windows updates, and anti-virus, disabled in the OS to reduce run-to-run variability. Each SSD is prefilled to 50% capacity and tested as a secondary device. Unless noted, we use active cooling for all SSDs.

Samsung 990 Bottom Line

The Samsung 990 is bound to be underwhelming for some, but none of our results should surprise. We know what this technology is and we’ve seen Samsung’s entries in recent years with the 990 EVO, the 990 EVO Plus, and the 9100 Pro. You could even put the 980 and 990 Pros into that mix. The move away from DRAM on the EVO Plus series, in particular, was a sign of the times. It’s not surprising to see the raw 990 – the 980 was TLC-based – go to QLC without the “QVO” addendum. The original speculation of the 990 QVO being a QLC 990 EVO, with the EVO itself being a surprisingly “slow” drive, was probably correct given the OEM evidence, and the 990 being a step up lets it command the 990 name by itself. To reiterate, this is exactly what we expected.

Skipping over the 990 QVO and V7 QLC flash is only sidestepping, and that’s likely because the market has changed so much over the last year or two. Bringing out a QLC-based 990 EVO equivalent just wouldn’t sell and might even make the brand look bad. It could certainly be done, and even still done, as an affordable SKU with better yields. But any 990 was going to be exactly what we got, instead. You need the faster flash to saturate PCIe 4.0 with a DRAM-less drive, and this was always going to be DRAM-less. Using a new or licensed controller with TLC flash would be weird, as it’d be going up against the existing 990 EVO Plus. Frankly, the 990 is a good 990 EVO replacement from retail and OEM perspectives, with one caveat: endurance. Samsung saves itself some headaches by reducing the warranty to three years, and as this flash is robust, it can just nudge up the TBW as a distraction.

We think that’s an important part of the message here. This flash seems designed for enterprise and has technological changes to back that up, with the main consumer benefits being the potential for increased reliability. But memory is still in high demand, and this has to be a budget part, so here comes the three-year warranty. Performance is not bad – it certainly beats earlier Gen 4 QLC-based drives and would beat the rumored 990 QVO as well. It’s just not really performance-focused. It’s also a much more efficient design, but that’s in comparison to Samsung’s own hardware. It’s merely mediocre there in the current landscape. Samsung seems to be building for the future with higher layer counts and bit density, so this lays the groundwork. A client drive seems almost like an afterthought. Users shouldn’t take that personally, but also shouldn’t underestimate this drive as it’s more than effective enough for its purpose.

In fact, in the era of Gen 3 drives returning and so many “box of chocolates” SSDs with random names and hardware, a reliable Samsung SSD is a nice option. Even with QLC flash. If you only need a budget drive to throw into a build or to upgrade an old PC, you get Gen 4 performance and a TLC-like experience for most things. We also feel this drive should be reliable and, although it runs hotter than we’d like, it’s not going to be molten like some other drives. It’s just a polished design by Samsung that fills a micro niche, and clearly it thought a response was needed. It’s not a lot different than our reaction has been to Samsung’s last few new drives, which have all been competent but largely never the strtong leader. That’s okay with us, as we can tell the manufacturer has a longer-term perspective; it just means a little less awe when you finish a build using a Samsung drive.

If you really want the best experience with a QLC-based drive, we still recommend the Crucial P310 – which is going away – or the Sandisk WD Blue SN5100. These offer incredible performance for QLC flash. Otherwise, there are some MP44Q-like drives out there that continue to be budget leaders. The 990 fits somewhere along there as a known-brand alternative. If you’re looking for Gen 5, DRAM, or TLC, then you’re also looking at a higher price tag. Frankly, QLC costs more than it should, in part due to enterprise demand. On the other hand, a modern QLC drive will provide an equivalent experience 99% of the time. The priorities are up to you. For us, the 990 is a fine primary drive for normal builds and OK for laptops, although we’d go cheaper for the PS5 and higher-end for an enthusiast machine.

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Intel this week announced that it will invest €5 billion ($5.7 billion) to expand and modernize its manufacturing operations at the company's facility near Leixlip, Ireland. The project is intended to increase production capacity for Intel Xeon 6 processors and next-generation Intel Xeon products built using the Intel 3 fabrication process (3nm-class), as well as advanced research and development (R&D) activities at the site.

The upgrade of the facility will involve installation of new tools presumably at Fab 34 as well as extensive infrastructure improvements designed to increase manufacturing efficiency. One of the key elements of the project is the expansion of the campus' automated material transport network, which will connect separate manufacturing modules into a single high-speed production system. Meanwhile, the modernization will not involve cleanroom expansion. Intel expects the upgrade to enable the Leixlip site to produce larger volumes of Intel 3-based products and make better use of the existing cleanroom capacity.

Intel opened its Fab 34 near Leixlip, Ireland, in 2023 and has been making various chips — including Core Ultra 100-series using Intel 4 and Xeon 6 using Intel 3 production node — using its process technologies that rely on EUV lithography at the site. At present, Intel's Fab 34 is Europe's only high-volume semiconductor production facility that uses EUV tools.

In mid-2024, Intel announced the €10.1 billion sale of a 49% stake in Fab 34 with Apollo Global Management as it badly needed money. This April, the company announced that it would repurchase the 49% stake in Fab 34 for $14.2 billion, which opened doors to the current expansion and investment. Intel claims that it kicked off execution of the project earlier this year, though it did not disclose when the upgrades will be completed.

"By investing in our existing fabs with state-of-the-art technology and installing cutting-edge tools, we are not just increasing output of critical products like Xeon 6 and next gen Intel Xeon processors built on Intel 3, we are ensuring that Ireland remains at the forefront of the world's most advanced manufacturing ecosystems, while strengthening the region’s role in the global technology landscape," said Naga Chandrasekaran, Executive Vice President, Chief Technology and Operations Officer and General Manager of Intel Foundry.

Among other things, Intel says that the investment will strengthen Europe's semiconductor supply chain and support the European Union's technology sovereignty objectives by increasing domestic production of leading-edge CPUs. There is a catch about that claim, though. All the silicon produced in Ireland is transported back to the U.S. for testing and assembly, as well as makes the end products, such as Core Ultra or Xeon 6, 'made in America.'

A stylish new product encourages the repurposing of old IDE optical drives as standalone audio players. Boutique South Korean electronic device maker das_POD has launched the CD-ROM PLAYER 01 (ships worldwide), and it has some distinct Teenage Engineering-a-like design flair. Any similarity to genuine TE products is purely accidental, we’re sure. The new self-assembly and bring-your-own optical drive enclosure costs from $190.

This das_POD product is “designed to be assembled, repaired, and owned,” says the maker. In contrast to a conventional hi-fi CD music player, the CD-ROM PLAYER 01 is supplied as a project that lets owners repurpose their old, unused, or discarded optical drives. The artsy assertion of das_POD is that “the project explores ownership, reparability, and the physical experience of music.”

As we stressed in the intro, the kit is supplied without any IDE optical drive, something required to complete the project. “Compatible IDE drives can often be found in old computers, second-hand markets, recycling centers, or forgotten boxes in storage,” points out das_POD, just in case you have never heard of eBay. “Every drive carries its own history. Every player becomes unique,” it adds, attempting to add mystique to a simple recycling/upcycling project.

We looked through the das_POD store and noticed that it sells some very reasonably priced IDE drives that can be used to facilitate a complete CD-ROM PLAYER 01 delivered in one package. Several refurb opticals are priced at just $5, for example. But you can also pick through multiple drives at $10, $15, $20… all the way up to $40. Something about the $35 DRIVE_24 from Samsung with its blue logo bar and tarnished beige faceplate (Grade: Output: A+, Sound Quality: A, Condition: C) grabbed my attention.

There are two CD-ROM PLAYER 01 colorways to choose from right now. das_POD sells a model in an anodized semi-gloss white for $220. A model in TE-a-like powder-coated orange is priced at $190.

The maker boasts that the kit supplied needs no soldering. But we also learn on the respective product pages that an AUX cable and 12V power adapter are (also) not included. Circling back to the firm’s online store, it looks like purchasing these items will add $25 to $30 to your checkout total.

A cheaper Aliexpress + DIY alternative for makers?

As some social media commenters say, besides the case, another key component of this product appears to be a CD/DVD-ROM optical drive controller, much like one available from Aliexpress for $30. That leaves the das_POD power board PCB as the sole missing essential, preventing makers with 3D printers, laser cutters, and/or CNCs from crafting their own CD-ROM PLAYER 01-type kits.

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MSI Afterburner’s solo developer is working on a new update that provides a heatmap of the most-used voltage/frequency points a GPU is operating at within Afterburner’s voltage/frequency curve chart. The update is designed to help enthusiasts and overclockers better understand the boosting behavior of their GPU and adjust their GPU’s overclock accordingly. Unwinder, Afterburner’s developer, reported on the Guru3D forums that this update will be released with 4.6.7 beta4 for users to test. An official (non-beta) release with the heatmap has not been announced yet.

The new heatmap generates yellow dots within Afterburner’s existing V/F curve editor, making it easy to compare the GPU’s existing V/F curve against where the GPU is boosting in real workloads. For instance, Unwinder shared a screenshot of the heatmap being used with an RTX 5090, showing the GPU operating primarily at 800mv at 1200MHz, and 1000- 1055 mV at around 2.6 to 2.8GHz. The former relates to the GPU’s behavior at idle/low-load workloads and the latter at maximum load.

Unwinder revealed that one interesting perk of the new heatmap system is its ability to identify the differences in boosting behavior between Nvidia’s RTX 40-series and older GPUs, and RTX 50-series GPUs. Improvements in Blackwell’s DVFS, or Dynamic Voltage Frequency Scaling, make the GPU behave very differently compared to RTX 40-series GPUs or older. Unwinder shared an additional screenshot of an RTX 4090 running the heatmap, showing yellow dots only around the lower and upper ranges of the V/F curve. By contrast, the heatmap of the RTX 5090 shows yellow dots across the entire V/F curve, revealing that the RTX 5090 is spending more time in the middle range of the curve than its predecessor.

MSI Afterburner’s new heatmap aims to help overclockers more accurately adjust their overclocks according to what voltage/frequency points the GPU is prioritizing in real workloads. For the uninitiated, V/F curve overclocking manipulates the GPU’s boosting algorithm by changing the shape of its V/F curve. If you're able to sustain the same clock speed at a lower voltage, that should mean a higher voltage can push a higher clock speed, which is the idea behind undervolting with a V/F curve before overclocking with an offset.

AMD is reportedly testing FSR Multi Frame Generation for existing Radeon GPUs, with ratios of up to 8x. According to a screenshot shared on the Chiphell forums, AMD's latest Adrenalin Edition 26.6.2 driver includes support for Multi Frame Generation, as hidden experimental settings were discovered in RadeonTuner, a third-party open-source alternative to AMD Adrenalin Software. In addition to a new Multi Frame Generation Ratio setting, RadeonTuner also includes override options for FSR Ray Regeneration Denoiser and FSR Neural Radiance Caching.

This suggests that AMD is potentially testing FSR Multi Frame Generation, with options ranging from 1x to 8x. In theory, that could boost a base frame rate of 60 FPS to as high as 480 FPS, which is around 2x higher than what Nvidia currently offers on its RTX 50 series GPUs. That said, these settings are non-functional, and there is no confirmation whether AMD has plans to roll out an 8x Multi Frame Generation mode.

The discovery has also prompted a response from the developer of RadeonTuner on GitHub, where they explained that AMD occasionally adds the names of upcoming settings to its drivers months before the actual functionality is implemented. The developer also clarified that the newly listed Multi Frame Generation ratios of up to 8x are placeholders that have been added for testing purposes, meaning that it may or may not align with the final implementation that AMD ends up supporting eventually.

Interestingly, during Microsoft's recent unveiling of its upcoming Xbox platform codenamed Project Helix, the company confirmed that the console will feature FSR Diamond (previously called FSR Next). This was touted as an AI-powered rendering suite that would include machine learning-based upscaling, ray regeneration, and Multi Frame Generation. AMD's graphics chief, Jack Huynh, later described FSR Diamond as the result of a multi-year engineering collaboration with Microsoft.

While there is no indication that the hidden driver settings are directly tied to FSR Diamond, the presence of experimental options for Multi Frame Generation, Ray Regeneration, and Neural Radiance Caching suggests AMD is laying the groundwork for its next-generation FSR technologies across the Radeon ecosystem.

We're enduring a particularly hot summer in the northern hemisphere, so it is understandable if powerful, pint-sized PCs are getting relatively toasty during long gaming sessions. However, Valve has confirmed that the Steam Machine's red light bar warning is bugged and being triggered prematurely. Redditor Pure-Outcome-5977 shared a Steam Support message that appears to confirm that a BIOS fix is on the way to raise the temperature and throttling red light warning threshold for the CPU/GPU from 95/90 to 100/100 degrees Celsius.

Update Regarding Red Light During Gameplay from r/steammachine

There appears to be a little miscommunication going on between the Redditor and Steam Support. Pure-Outcome-5977’s red warning light was coming on with system monitor tools showing the CPU was at 81°C and the GPU at 71°C. So the red light bar warning trigger temperatures of 95/90°C seem to be bugged. Thus, they got an answer to a slightly different issue than the one they raised.

“After discussing with our engineers, there is a known issue with the current BIOS that results in the red LED lights displaying much earlier than they should,” admits the Steam Support person in the message screenshot. “The issue is just with when the lights are set to come on. The Steam Machine itself is within normal operating temperature for the CPU/GPU, which they confirmed from your screenshots. For your awareness, the Steam machine will start throttling performance at 100C for CPU/GPU and will shut down to protect itself if temperatures rise past that.”

Importantly, this premature red warning light is just a temporary wrinkle that will be fixed soon via a BIOS update, adds Steam / Valve. After the update, red light warnings will only be seen after hitting a threshold of “100/100C for CPU/GPU instead of 95/90 for CPU/GPU that is currently happening,” concluded the official support message.

The nearest desktop alternative to the Steam Machine’s CPU, something like the Ryzen 5 7500F, has a TDP of 65W and a max operating temperature of 95°C. However, Valve uses a custom mobile-tuned 30W CPU, which is configured to throttle at 100°C and self-protect shutdown if temperatures continue to rise, hitting 105°C.

We don’t have a set date for the arrival of the new Steam Machine BIOS, but “soon” should be good enough for most users.

The Steam Machine’s light bar has previously been in media focus, being central to stories about the device suffering from a ‘Red Line of Death’ (RLOD). Happily, the pronouncement of death in that case was also premature. RLOD Steam Machines can be reanimated Lazarus-like by following a simple and officially described CMOS reset procedure (read more via the above link).

Cooler Master occupies an unusual position in the power supply market. Founded in Taiwan in 1992 and best known for the cases and coolers that made its name, the company has spent more than two decades selling PSUs without ever being a PSU manufacturer in the strict sense. Like most brands in this space, it commissions platforms from numerous OEMs, and the quality of a given Cooler Master unit has historically tracked the quality of whoever built it. The MWE line sits at the volume end of the company's catalog: sensible, mainstream units aimed at builders who want a dependable supply without paying for a flagship badge. We take a closer look at the Cooler Master MWE Gold 750 V4 to see if it belongs among our list of the best power supplies in the market today.

The MWE Gold V4 series is the latest iteration of that formula, and it arrives with more substance than the mid-range positioning suggests. The platform was developed by Gospower in collaboration with Cooler Master, and it is currently dedicated to them - you will not find this design wearing another brand's sticker for the time being. The series is fully compliant with ATX 3.1 and PCIe 5.1, carries a native 12V-2x6 connector, and introduces Cooler Master's patent-pending GPU Shield current-monitoring feature alongside a digital control scheme for the PFC and LLC stages. The 750W model reviewed here targets the heart of the mainstream gaming market, backed by a ten-year warranty and a $119 MSRP.

Specifications and Design

In the Box

The MWE Gold 750 V4 ships in a cardboard box with a purple-blue sleeve wrapped around plain kraft board, a render of the unit on the front, and the important badges - ATX 3.1 with 12V-2x6, PCIe 5.1 readiness, the 80 PLUS Gold logo, and the ten-year warranty shield - laid out along the bottom edge. It is a clean, honest presentation for the class, with the GPU Shield feature called out in its own corner.

Inside, the supply is sandwiched between protective packaging. The bundle is basic: the AC power cord, a set of mounting screws, a handful of zip ties, and a few reusable Velcro straps, plus a leaflet explaining Cooler Master's recommended PCIe cable installation practices. There are no cable combs, no tester, and no storage pouch, which is a defensible economy at this price point, even if competitors occasionally throw in more.

The modular cables themselves are all-black, flat ribbon types. The 12V-2x6 cable uses the two-color connector design that the ATX 3.1 spec encourages, making an incompletely seated plug easy to spot, but we would argue that dark purple was not the best choice for this application. Wire gauges are appropriate throughout, and the flat design makes routing behind a motherboard tray painless.

External Appearance

At 140 x 150 x 86 mm, the MWE Gold 750 V4 is a compact ATX unit - 140 mm of depth is as short as modern PSUs practically get, and it will drop into any case that accepts an ATX supply at all, with room to spare for cable slack. The rhombille tiling fan grille stands out, framed by four exposed screws, with a thin gold pinstripe and gold MWE branding on the side panels, providing the only decoration on an otherwise all-black chassis. The finish deserves a mildly critical word. It is smooth and appealing - not a bad paint job by any means - it simply is not as special as the rest of the unit's feature sheet might lead you to expect.

The rear face carries the AC receptacle and a receded main rocker switch surrounded by a generous perforated exhaust area. There is no switch for the semi-passive fan mode - the Zero RPM behavior is automatic and not user-selectable, which some builders will not appreciate. The front face hosts the fully modular connector bay, clearly silkscreened, with a shared 8-pin socket group for the PCIe and CPU cables, the native 12V-2x6 socket, and a small indicator LED between them. The specifications sticker lies on the top face.

That small LED is the visible face of GPU Shield, Cooler Master's patent-pending current-management feature, and the marketing centerpiece of the V4 series. The circuit monitors the current flowing through the individual pins of the 12V-2x6 connector in real time, and if it detects an abnormal draw on any of them - the classic signature of a poorly seated or damaged connector - it intervenes and flags the fault through the LED. Given how much grief melting connectors have caused over the past few years, a per-pin watchdog on a $119 unit is a genuinely useful inclusion rather than a gimmick, even if we hope most owners never see the LED do anything at all.

Internal Design

Cooling is handled by a 120 mm Hong Hua HA1225H12F-Z fan, a hydrodynamic bearing (HDB) model rated for 2400 RPM at 0.58A. Hong Hua is a familiar name inside value-oriented and mid-range PSUs, and while it lacks the cachet of a premium Japanese fan, the HDB variant is a reasonable, durable choice at this tier, and its ceiling speed gives the platform plenty of thermal headroom to call on.

As noted in the introduction, the platform is a Gospower design produced in collaboration with Cooler Master and currently exclusive to them, so there is a clear answer to the perennial 'who really makes it' question. The layout is clean and modern, with sizable heatsinks for the power output, vertical daughterboards for the minor rails, and generous helpings of grey silicone glue securing the components.

The transient filtering stage begins on a small PCB behind the AC receptacle and continues on the main board, with two Y capacitors, two X capacitors, two filtering inductors, and a MOV - a basic but complete filter without omissions. A relay handles inrush current bypass duty alongside the usual NTC thermistor. Two bridge rectifiers are mounted on their own heatsink, feeding the APFC stage, whose boost components share the long heatsink with the primary inversion stage MOSFETs. A single 590 μF capacitor from TK (Toshin Kogyo), a renowned Japanese manufacturer.

The primary inversion stage uses a half-bridge LLC resonant topology, the mature and cost-effective arrangement that dominates this class, with Cooler Master claiming the digital tuning of the PFC and LLC stages is worth roughly three points of efficiency over the previous MWE generation - a dubious claim as the unit still lands on Gold-level efficiency class. On the secondary side, the 12V rail is generated by four MOSFETs arranged in synchronous rectification on the main PCB, while the 3.3V and 5V rails are derived from DC-to-DC converters on a vertical daughterboard. Secondary filtering leans heavily on CapXon capacitors.

Cold Test Results (25°C Ambient)

Cold Test Results (25°C Ambient)

For the testing of PSUs, we are using high precision electronic loads with a maximum power draw of 2700 Watts, a Rigol DS5042M 40 MHz oscilloscope, an Extech 380803 power analyzer, two high precision UNI-T UT-325 digital thermometers, an Extech HD600 SPL meter, a self-designed hotbox and various other bits and parts.

At 25°C ambient, the MWE Gold 750 V4 delivers exactly the efficiency profile its badge promises. It averaged 90.4% at 230 VAC and 89.3% at 115 VAC across the nominal load range, peaking at 92.6% (230 VAC) near 50% load and holding 90.2% even at a sustained 750W. The curve is not exactly flat, but there is no dramatic full-load sag. The figures sit comfortably within 80Plus Gold territory. What the unit does not yet have is a Cybenetics certification: at the time of writing, there is no entry for the MPM-75F4-AFG in the Cybenetics database.

Acoustically, the cold run is very good news. The Zero RPM mode keeps the fan completely stopped up to almost 40% load (roughly up to 300W), which covers desktop work and light gaming outright. The fan spins up at about 40% load, registering a whisper-quiet 31.6 dB(A), and ramps gently from there, crossing 39 dB(A) only past 80% load and topping out at 44.2 dB(A) at a sustained 750W. Thermal performance gives no cause for concern, with the primary and secondary heatsinks reaching just 64°C and 66°C, respectively, at full load.

Hot Test Results (~45°C Ambient)

Hot Test Results (~45°C Ambient)

Inside the hotbox at roughly 45°C ambient - slightly above the unit's own 40°C rating - efficiency drops by about two percentage points, averaging 88.4% at 230 VAC and 87.4% at 115 VAC, with full-load figures of 86.5% and 85.2% respectively. That degradation is significant but entirely ordinary for the temperature delta, especially considering a unit that is now operating beyond its rated envelope.

Noise is where the heat reshapes the unit's character. The fan abandons its passive mode sooner and climbs steadily to 47.8 dB(A) at full output - a level you will definitely hear, though short of the wind-tunnel territory some compact Gold units reach under the same conditions. Internal temperatures are the figures to watch: the primary heatsink reached about 104°C and the secondary about 105°C at full load. The platform held composure, and component ratings give some reassurance, but sustained full-load operation in a 45°C environment is clearly not this unit's design brief, nor should it be for any mainstream 750W supply.

PSU Quality and Bottom Line

Power Supply Quality

Voltage regulation is relatively solid for the class. Across the 20% to 100% load span, the 12V rail moved by 0.9%, the 3.3V rail by 1.1%, and the 5V rail by 1.4%. Nothing here approaches the sub-1% figures of premium digital platforms, but every rail stays comfortably tight, and the 12V line - the only one modern systems seriously stress - is well controlled at under 1% regulation.

Ripple suppression follows the same pattern of honest adequacy. The 12V rail peaked at 54 mV under full load and 50 mV under the 12V-focused cross-load test, while the 5V and 3.3V rails topped out at 32 mV and 30 mV. Against the 120 mV and 50 mV ATX design limits, these are comfortable passes with roughly 55% headroom on the critical rail, though enthusiast-class platforms routinely halve these numbers. For the components a 750W Gold unit will realistically feed, the filtering is more than sufficient.

During our thorough assessment, we evaluate the essential protection features of every power supply unit we review, including Over Current Protection (OCP), Over Voltage Protection (OVP), Over Power Protection (OPP), and Short Circuit Protection (SCP).

All protection mechanisms were verified and triggered correctly during testing. With the unit hot, OCP tripped at 134% on the 3.3V rail, 136% on the 5V rail, and 128% (80A) on the 12V rail, with OPP shutting the unit down at roughly 130% of rated output, or about 975W. These thresholds are on the generous side for a mainstream unit but not unexpectedly so.

Bottom Line

The MWE Gold 750 V4 is a well-judged mainstream power supply that knows exactly what it is trying to be. The Gospower-built platform - developed jointly with Cooler Master and currently dedicated to them - is modern where it matters: ATX 3.1 compliance with a native 12V-2x6 connector, digital control of the PFC and LLC stages, and the GPU Shield monitoring feature as a genuinely novel extra at this price. The engineering fundamentals are in noticeably better shape than the MWE badge historically implied, and the 12V-2x6 connector protection can bring sales from worried consumers.

The measurements back the badge without embarrassing it. Efficiency lands squarely and honestly in Gold territory with a predictable curve, and its 80Plus listing is real and verifiable. Regulation and ripple are comfortably within specification on every rail, with the 12V line particularly steady, even if neither metric threatens the enthusiast tier. Acoustics at normal ambient temperatures are a quiet strength, with a true fanless window covering 300W of load and restrained ramping beyond it.

The compromises are easy to enumerate and, mostly, easy to live with. The capacitor selection is almost entirely Taiwanese, leaning on CapXon polymers - fine parts, but the ten-year warranty is doing some load-bearing work there. The unit gets audible under sustained heavy load in hot environments, where the internal temperatures also climb higher than we would like. None of these is a genuine weakness at this price point - they are simply the fingerprints a $119 budget inevitably leaves somewhere.

At an MSRP of $119 and with retail pricing typically drifting below that figure, the value calculus is straightforward. There are quieter units, better-built units, and units with prestigious component sheets - all of them costing meaningfully more. For a mainstream ATX 3.1 build around a mid-range or upper-mid-range graphics card, the MWE Gold 750 V4 delivers verified Gold efficiency, current-generation connectivity, unusual protective touches, and a decade of warranty coverage at a price that undercuts most of the units it competes with. That is an easy recommendation, delivered with only minor reservations.

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When the RTX 50 series launched, reviewers quickly discovered that the hotspot temperature was being misreported in standard diagnostics tools such as HWiNFO or MSI Afterburner. Eventually, people realized that Nvidia had outright removed the option to monitor hotspot temps, but it seems like the hardware was never removed from the GPU. New testing by Brazilian repair specialist Paulo Gomes has revealed that the sensor is still present and readable with special tools.

In the video, the host shows a Gigabyte variant of the RTX 5070 Ti that was sent to him due to overheating issues. Within Windows, the monitoring tools showed no abnormal signs, as the "average" temperature was reported at 67 to 68 degrees Celsius. However, when diagnosed with a specialized tool called "MODS," the hotspot temperature reached 107 degrees Celsius almost immediately under load.

MODS stands for Modular Diagnostics Software, and it's an internal Nvidia tool used to test GPUs before they hit the shelves or during the RMA process. It's not available to the public and doesn't work on Windows because the OS keeps intercepting calls from the hardware monitoring APIs. You need a Linux distribution that boots directly into a command line, from where MODS (and MATS, for memory testing) can run as intended.

Some repair shops have been known to get access to MODS, such as in this case, which unlocks the hidden hotspot temperature sensor on Blackwell gaming GPUs. Keep in mind that Nvidia ships much more comprehensive diagnostic utilities for its server-grade and workstation GPUs that can actively monitor all aspects of the card. It's unknown why the company decided to keep some sensors locked out of gamers' reach.

Perhaps we can infer the rationale from last year, when Igor's Lab tested several RTX 50-series GPUs and found a "hotspot issue" affecting all of them. The reason was poor PCB manufacturing — not using heavy-duty materials to build the PCB layers, causing certain parts of the substrate to heat up even when the core was relatively cool. This was exacerbated by Nvidia's own guidelines, which told AIBs to compensate for ideal conditions instead of worst-case scenarios.

Anyhow, as Paulo Gomes and his team discovered, the RTX 5070 Ti's hotspot was hitting 107 degrees Celsius, and the card throttled and dropped its clock speeds right away. Nvidia mandates 107 degrees Celsius as the upper limit for RTX 50-series, so it was clear that the card was slowing down to prevent damage. To inspect what was actually wrong, they opened up the card and found poor thermal contact between the cooler and the componentry.

The TIM (thermal interface material) application was inadequate; the paste had accumulated around the perimeter of the core while the center was mostly dry. The repair personnel removed the old material and replaced it with SnowDog Husky paste, which was enough to drop the hotspot temperatures to 100 degrees Celsius. Now, it was within the safe operating range and no longer thermal throttling under load.

What would've been a simple fix on the consumer's end was turned into a repair job solely because Nvidia hid the GPU's hotspot temperature, literally misreporting the card's internal condition. Had this RTX 5070 Ti just run at 107 degrees Celsius continuously, the silicon would wear down incredibly fast, and the customer would never even know why. Not to mention some manufacturers' insistence on voiding warranty upon breaking the GPU's "seal," which is an illegal and unenforceable practice in the United States.

AMD’s formerly China-exclusive Radeon RX 9070 GRE, which rivals the best graphics cards, went global last month at a suggested MSRP of $549. The GPU has now seen its first price drop since its launch, with the Gigabyte Gaming Radeon RX 9070 GRE available for $499 at Newegg. While the listing shows $549, customers can use a $50 promo code by submitting their email address to reveal it.

The Radeon RX 9070 GRE is built on AMD’s RDNA 4 graphics architecture, and uses the same Navi 48 GPU as the Radeon RX 9070 and RX 9070 XT. However, it uses a cut-down version of that chip with 48 compute units. It also comes with 12GB of GDDR6 running at 18 Gbps on a 192-bit bus, offering 432 GB/s of raw memory bandwidth. Despite the scaled-down specifications, the RX 9070 GRE retains a TDP of 220W, similar to the standard Radeon RX 9070. Essentially, the card sits between the RX 9060 XT 16GB and the RX 9070, and AMD claims it delivers 21% higher average performance than the RTX 5060 Ti 16GB in 1440p gaming.

In our testing of the XFX Swift Radeon RX 9070 GRE, we found that the card averages 120 FPS at 1080p and 86.6 FPS at 1440p across our 11-game raster-only test suite. That makes it a solid choice for high-refresh-rate gaming at two of the most popular monitor resolutions, and it offers a comfortable position over the RX 9060 XT 16GB and RTX 5060 Ti 16GB.

Unfortunately, the RX 9070 GRE is not entirely impressive at 4K resolution as it struggles to maintain an average of 60 FPS. That said, enabling FSR 4 upscaling and frame generation in supported titles can significantly improve performance. Ray tracing performance remains a weaker area for the RX 9070 GRE. Gamers who prefer enabling RT effects will likely need to enable FSR 4 to offset the performance hit, particularly at higher resolutions.

At its discounted price, the RX 9070 GRE competes directly with Nvidia's RTX 5060 Ti 16GB, which currently sells for well over $500. If you are a gamer who prioritizes raw rasterized performance, the RX 9070 GRE is worth considering, especially if you're upgrading from an older GPU such as the RX 6700 XT or RTX 3070.

SK Hynix CEO Kwak Noh-jung says that 2027 will be the "worst year" for the ongoing memory shortage in comments shared with Reuters. The remark comes on the heels of SK Hynix successfully marking the largest-ever IPO for a foreign company on the U.S. stock market, raising $26.5 billion. Although Kwak points to next year being the worst for RAM shortages, the executive expects the memory crunch to last until 2030.

"We forecast that next year will be the worst year in the industry's history from the supply perspective," Kwan told Reuters. "We still forecast that customer demand will remain higher than our ​supply capacity even beyond 2030. But we are doing our best to solve the problem."

In March, SK Group chairman Chey Tae-won also suggested shortages would last until 2030, and the company has previously pointed to 2027 as a key shortage point, alongside Samsung. DRAM demand is largely driven by the HBM used in AI accelerators, which require far more sophisticated manufacturing and packaging processes compared to consumer DDR5. On top of advanced manufacturing, HBM also consumes more wafer capacity than DDR5, forcing major memory brands to reallocate supply and double down on an already sticky supply situation.

Forecasts like this are tricky. It's in SK Hynix's financial interest for memory shortages to continue, even well beyond 2030. SK Hynix has set a record for quarter-over-quarter revenue, and rival Micron has seen its stock value increase 213% this year, pushing its share price to around $990.

However, Kwan's remarks aren't just a bid to rally behind SK Hynix stock. Over the past few months, we've seen Micron and SK Hynix ink long-term supply agreements (LTAs). These agreements commit supply over multiple years to particular companies and define a price floor and ceiling during the agreement term. Although LTAs don't directly influence market prices, they secure demand, and we've seen a lot of LTAs over the past several months to bind DRAM supply.

Although memory (and NAND) prices will remain elevated for at least the next several months, we've seen some signs of the market cooling. Earlier this month, a TrendForce report showed DRAM contract prices up 15% to 18% quarter over quarter for Q3 2026. That's a large increase, but far lower than the QoQ increases we've seen previously.

We're nearing some semblance of stability in the memory market, just stability at vastly elevated prices. How long that lasts is anyone's guess. Although memory brands like SK Hynix have visibility into market trends, those can rapidly change. Just this year, we've seen a massive pivot toward AI spending going toward CPUs, pushing Intel's stock to record highs while shedding around $1 trillion in Nvidia's market cap; a year ago, that would've been almost impossible to predict.

Another day, another TeamGroup drive, right? Yet the G70 Pro surprises with some unusually good results, combining DRAM and newer flash into a powerful but affordable drive. We have some questions about the controller choice, but the drive as a whole is surprisingly good.

The devil, as they say, is in the details, as its performance quirks make it better for some use cases over others. It’s also not something you want to toss into your laptop – this is still a high-end drive with correspondingly high heat production – but could work in a pinch for pretty much anything else. In this market, it’s a welcome alternative.

TeamGroup G70 Pro Specifications

If you’re ever upset that a drive only comes in one or two capacities, then the TeamGroup G70 Pro might be for you. Not only does it come in both heatsinked and non-heatsinked versions, but it’s also available at 512GB, 1TB, 2TB, 4TB, and even 8TB. At the time of review, we could only find 1TB, 2TB, and 4TB models available, with pricing pretty close between the two types – go for the heatsink, if you can. We’re giving the lower prices at $197.99, $326.99, and $505.99. If you’re shooting for DRAM, these prices aren’t too bad, but we’d lean towards the Seagate FireCuda 530R instead at 1TB. The G70 Pro is more competitive at 2TB and 4TB against comparable drives.

The drive is capable of reaching up to 7,400 / 6,600 MB/s for sequential reads. Random read and write IOPS are not given, but we know this controller and flash are rated for at least 700K and can reach 1,000K or more. This is comparable to other drives in this class. We wouldn’t recommend the drive at 512GB as it can’t reach peak performance. Ideally, you would go for 2TB or 4TB for the best results. The drive is backed by a five-year warranty that covers 740TB of written data per TB, which is above average but not exceptional.

TeamGroup G70 Pro Software and Accessories

TeamGroup’s primary download for the G70 Pro is its SSD S.M.A.R.T. Tool. This all-in-one SSD toolbox displays drive and system information and allows for performance testing. While you can sometimes catch drive errors early with SMART, it’s best not to rely on it. For drive and data backup we continue to recommend MultiDrive for Windows and Clonezilla or Rescuezilla for everything else.

TeamGroup G70 Pro: A Closer Look

The 2TB TeamGroup G70 Pro is a double-sided drive and, judging by the specifications, always double-sided. We don’t have smaller SKUs to verify that, and we recommend the larger SKUs as the better value anyway. However, we’ve heard of single-sided G70 Pros at 1TB in the wild, so your mileage may vary.

Our drive uses a graphene label – which is useful for spreading heat from the controller, in particular – but there is also a version with a heatsink. We would recommend going with a heatsink, if possible. The rear of the drive states a power rating of ~8.25W, which is within expectations. In our testing, we would expect it to pull less and, in fact, that is what our numbers show.

The drive is adorned with an SSD controller, two DRAM packages, and four NAND flash packages. The controller is the InnoGrit IG5236, an eight-channel controller with DRAM that competes directly with the Silicon Motion SM2264 and Phison E18. These are at the top of the PCIe 4.0 product stack. The DRAM in question is SK hynix H5AN8G6NDJR-VKC, which, as the 8G indicates, is in an 8Gb or 1GB configuration. Two packages mean 2GB, which gives the normal 1GB:1TB DRAM:NAND ratio for optimal performance. The flash packages are 512GB each of YMTC 232-Layer TLC (X3-9070) with four 1Tb dies each. With a total of sixteen dies, or two per channel, performance is good at this capacity.

Let’s address the elephant in the room: the IG5236 controller. This controller was one of our favorites when it first came out, as it competed with the E18 – the first true non-proprietary high-end PCIe 4.0 controller – at a lower price point. Eventually, it saw some flash it didn’t like from YMTC, which caused some serious issues. Over time and with more feedback, the controller eventually gained a more general reputation for unreliability. Reliability reports were often unpredictable, which didn’t help matters. While, as a result, we do prefer the E18, our review of this G70 Pro sample has given indications that TeamGroup took some efforts to improve reliability. We’ll point these out as we go forward.

The bigger issue for the drive is probably that TeamGroup will likely not have one specific set of hardware for this drive, which means that, while we think you’re probably okay with the mix we got, we can’t guarantee this is the NAND and SSD controller configuration that you’ll receive.

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Comparison Products

If you’re looking at the G70 Pro, you’re probably also looking at TeamGroup’s A440 series – we have the A440 Pro for comparison – as well as the Inland Gaming Performance Plus or Performance Plus and the WD Black SN850X. These are all high-end Gen 4 drives with DRAM. If you’re willing to compromise on DRAM to save some money but still want high-end performance, there are some good options out there. These include the Addlink A93, the Acer Predator GM7, and the Biwin Black Opal NV7400. We’ve also thrown two newer drives into the mix, which are compelling: the Crucial P310, which uses QLC flash, and the WD Black SN7100, the power efficiency champion.

Trace Testing — 3DMark Storage Benchmark

Built for gamers, 3DMark’s Storage Benchmark focuses on real-world gaming performance. Each round in this benchmark stresses storage based on gaming activities including loading games, saving progress, installing game files, and recording gameplay video streams. Future gaming benchmarks will be DirectStorage-inclusive and an evaluation for future-proofing is included where applicable.

The G70 Pro falls right in the middle of the pack, which is actually right where it should be. 43µs for latency in 3DMark is quite good, ensuring a good experience with fast game loading times. Any of these drives would be great for games – and probably overkill – but we look for 45µs or less for the best level of responsiveness. The G70 Pro hits this target.

Trace Testing — PCMark 10 Storage Benchmark

PCMark 10 is an industry standard trace-based benchmark that uses a wide-ranging set of real-world traces from popular applications and everyday tasks to measure the performance of storage devices. The results are particularly useful when analyzing drives for their use as primary/boot storage devices and in work environments.

The G70 Pro does better in PCMark 10, coming in near the top with respectably high bandwidth and low latency. This is very good performance for applications, and the drive would be great as your primary drive even in a workstation. It makes use of the DRAM and eight flash channels to deliver relatively high performance, beating perennial favorites like the Black SN850X. This is likely due to the fact that it uses 232-Layer flash, which is newer than anything the slower drives have.

The Black SN7100 and P310 are DRAM-less with four channels, but they use newer flash of an equivalent generation with newer controllers than the G70 Pro. This goes to show that you don’t need a full-power controller to dominate here, but we caution that this does not reflect edge case performance with a fuller drive or in long-term use.

Console Testing — PlayStation 5 Transfers

The PlayStation 5 is capable of taking one additional PCIe 4.0 or faster SSD for extra game storage. While any 4.0 drive will technically work, Sony recommends drives that can deliver at least 5,500 MB/s of sequential read bandwidth for optimal performance. Based on our extensive testing, PCIe 5.0 SSDs don’t bring much to the table and generally shouldn’t be used in the PS5, especially as they may require additional cooling. Check our Best PS5 SSDs article for more information.

Our testing utilizes the PS5’s internal storage test and manual read/write tests with over 192GB of data, both from and to the internal storage. Throttling is prevented where possible to see how each drive operates under ideal conditions. While game load times should not deviate much from drive to drive, our results can indicate which drives may be more responsive in long-term use.

The G70 Pro performs admirably in the PS5. Would we recommend it? Yes, but with caveats. It’s not a bad choice at 2TB and 4TB, but we would recommend getting the version with a heatsink, if possible. The drive might run toasty without it. We also think you can get DRAM-less drives that will perform nearly the same at a lower cost, that won’t need a heatsink, so factor that into any purchase decision.

Transfer Rates — DiskBench

We use the DiskBench storage benchmarking tool to test file transfer performance with a custom 50GB dataset. We write 31,227 files of various types, such as pictures, PDFs, and videos to the test drive, then make a copy of that data to a new folder, and follow up with a reading test of a newly-written 6.5GB zip file. This is a real-world type workload that fits into the cache of most drives.

Taking a quick look at our DiskBench results, the G70 Pro exhibits no issues. Its copy performance is, in fact, quite good, coming close to the top. To be fair, some of the drives near it are DRAM-less, so they should be less expensive and more power-efficient in practice. That said, if you’re looking for the total package, then the G70 Pro will deliver. We would recommend checking our Write Saturation section to see how these drives measure up with longer transfers.

Synthetic Testing — ATTO / CrystalDiskMark

ATTO and CrystalDiskMark (CDM) are free and easy-to-use storage benchmarking tools that SSD vendors commonly use to assign performance specifications to their products. Both of these tools give us insight into how each device handles different file sizes and at different queue depths for both sequential and random workloads.

Looking at ATTO first, we see a disappointing dip most prominently at 512KiB reads with the G70 Pro. The question is: controller or flash? Possibly a bit of both, as we’ve seen weak performance in ATTO on this controller before, but not all drives have had issues. If we’re comparing the XS70, which uses 512Gb dies with four-plane flash, to the G70 Pro, which has 1Gb dies using six planes, then we consider that the superpage size – this would be the size of all pages open across all dies/planes with at least one per flash channel – is quite different.

Parallelization is necessary to reach the best performance with larger files, and the G70 Pro’s flash crosses a threshold between 512KiB and 1MiB, which might explain this dip. In fact, the flash on the 2TB model would prefer I/O larger than 1MiB. The older XS70, as reviewed, would be happier with less. This is an inevitable trade-off as newer flash technology targets larger dies to reduce price and more planes for higher bandwidth to match new interface speeds.

This difference is reflected to some extent in CDM, where QD1 sequential read for the G70 Pro performance is pretty meh. Give it QD8, though, and it’s on top. Unfortunately, low QD is much more common, especially for large file transfers. Of course, you need another drive to match the speed anyway, and if you’re doing heavier workloads, you might actually push more than QD1 where this drive proves to be quite fast. The bottom line is that some of these drives with less-dense flash – like the Black SN850X – or fewer channels – that would be the P310, Black SN7100, A93, Black Opal NV7400, and GM7 – can do better with QD1 reads. On the other hand, the G70 Pro’s newer flash makes it more responsive with QD1 writes, although this is less impressive for everyday workloads.

The good news is that the 4KB latencies are good, and the 4KB random read latency at QD1 is exceptional. This is a ridiculously responsive drive. It’s a bit strange to have a drive that superficially should push bandwidth turn around and give such excellent latency. The discrepancy, given our above explanation about parallelization, is due in part to the fact that a single 4KB operation is only going to hit one die and plane of flash. This could work in the drive’s favor if you are taking advantage of the right workloads. For random reads, everyday workloads, including games and apps, will be very responsive. For larger transfers, push this drive harder if you’re reading from it to better take advantage of its strengths, or alternatively, use it for random writes as you could do with caching.

Sustained Write Performance and Cache Recovery

Official write specifications are only part of the performance picture. Most SSDs implement a write cache, which is a fast area of pseudo-SLC (single-bit) programmed flash that absorbs incoming data. Sustained write speeds can suffer tremendously once the workload spills outside of the cache and into the "native" TLC (three-bit) or QLC (four-bit) flash. Performance can suffer even more if the drive is forced to fold, the process of migrating data out of the cache in order to free up space for further incoming data.

We use Iometer to hammer the SSD with sequential writes for 15 minutes to measure both the size of the write cache and performance after the cache is saturated. We also monitor cache recovery via multiple idle rounds. This process shows the performance of the drive in various states including the steady state write performance.

The G70 Pro has a small cache, coming in around 50GB with a pSLC write speed of 6.7 GB/s that writes for about 7.5s effectively. We’ve seen caches of this size before, usually chosen to improve “quality of service,” which is a fancy way of saying the manufacturer wants to avoid a performance cliff. 50GB is still relatively large for caching random writes, and random writes are what you want to cache the most, and the absolute size will vary a lot less with drive fill, as it’s not taking up a lot of native flash. This means more consistent write performance. A drive might also use a small cache to hide weak flash – weak as in lower endurance – as the highest-endurance portion of the flash can be used for the cache, if you’re doing big writes like we are here, doing writes straight to the native flash can actually induce less wear in some cases. However, we think TeamGroup is just aiming for consistent performance, with the secondary effect being that they can swap flash if needed.

The drive then writes to native flash at almost 2.8 GB/s for 16 seconds. This flash can write faster than this and, given that the drive is 2TB, it could absolutely write in this state – or the pSLC state, for that matter – for a significantly longer time. The 4TB model should be as fast or faster. Still, this is pretty speedy and matches the consistent write experience we would anticipate from the small cache. On the other hand, it does make us wonder why TeamGroup is being so conservative with it. This controller has had some issues in the past, and this might be a way to mitigate those. If so, we’re on board, as this type of performance profile matches the drive’s overall trend quite well.

This is especially true with folding performance at over 1.35 GB/s – quite fast for that state – and given how small the cache is and how short the drive writes even in native mode, the real steady state is closer to our native flash speed at 2.75 GB/s. This is a very good result and supports our earlier assertion that this drive would be great for certain workloads like caching. TeamGroup likely knows this, and if the drive is more reliable for it, all the better. We think that’s worth knowing if you’re a buyer because the IG5236 controller does carry a somewhat negative reputation under normal circumstances.

Power Consumption and Temperature

We use the Quarch HD Programmable Power Module to gain a deeper understanding of power characteristics. Idle power consumption is an important aspect to consider, especially if you're looking for a laptop upgrade as even the best ultrabooks can have mediocre stock storage in terms of capacity and performance. Desktops are often more performance-oriented with less support for power-saving features so we show the worst-case for idle.

Some SSDs can consume watts of power at idle while better-suited ones sip just milliwatts. Average workload power consumption and max consumption are two other aspects of power consumption but performance-per-watt, or efficiency, is more important. A drive might consume more power during any given workload but accomplishing a task faster allows the drive to drop into an idle state more quickly, ultimately saving energy.

For temperature recording we currently poll the drive’s primary composite sensor during testing with a ~22°C ambient. Our testing is rigorous enough to heat the drive to a realistic ceiling temperature but real-world temperatures will vary due to the environment and workload factors.

All this performance comes at a cost. The G70 Pro is not very efficient, although it’s better than the E18-based drive and comes awfully close to the Black SN850X. For a DRAM-equipped, eight-channel PCIe 4.0 drive, it does okay. If you are looking for a power-efficient drive, this isn’t it, although it could be worse.

The drive reports multiple temperatures, but the one we’re looking at is the highest. It hit a maximum of 71°C in our testing, which is surprisingly good, given that this controller starts to throttle at 90°C. That’s almost at our ideal 20°C of headroom. However, the drive is still putting out a lot of heat, and this is under good conditions with a graphene heatspreader. Running this drive naked in a laptop is inadvisable. We continue to recommend getting the G70 Pro with a heatsink or adding a heatsink to the graphene model – you can even put a heatsink over the graphene label, if necessary – to make for a cooler-running drive.

Test Bench and Testing Notes

We use an Alder Lake platform with most background applications, such as indexing, Windows updates, and anti-virus, disabled in the OS to reduce run-to-run variability. Each SSD is prefilled to 50% capacity and tested as a secondary device. Unless noted, we use active cooling for all SSDs.

TeamGroup G70 Pro Bottom Line

The TeamGroup G70 Pro promises a little bit of everything in a challenging SSD market. DRAM? Check. All the best drives have DRAM, or so people have been led to believe, and that simple inclusion puts the G70 Pro up a notch. Newer flash? Also, check for our sample, 232-Layer rather than 176-Layer, and TLC too. In practice, the difference is small, but if you can get newer flash, you should, and TLC is always preferable to QLC. Cooling? It comes with a graphene heatspreader by default, but has a heatsink SKU for those who want one less thing to worry about. With this combo, the drive delivers excellent random read latency, good potential throughput, and with a heatsink, it shouldn't overheat. Plus, it’s available in a wide range of capacities.

There are some caveats here, however. The drive is not power-efficient, so it is bound to run hot even if it doesn’t throttle. It has DRAM and newer flash, but the controller is the less desirable InnoGrit IG5236, one that’s known to be less reliable. The flash is also YMTC, which indicates to us that you might not always get the same hardware on this model. Performance is good, yes, but it’s not completely consistent across all of our tests. While we like that we can get this from 512GB to 8TB, in reality, you’re only going to find the middle SKUs. The drive is best at 2TB or 4TB, and its pricing at 1TB is average at best. We can live with this as 2TB and 4TB are good places to be, no matter what you use this drive for: primary for your operating system, secondary for games or storage, or in your PS5.

Speaking of what you use it for, the drive’s performance profile means it could make a good caching or NAS drive. We would definitely recommend a heatsink in that role. It’s not perfect for such a workload, but it’s probably going to be better than most of the DRAM-less options that are out there, and it should cost you less than the Black SN850X or 990 Pro. While reliability concerns linger with this controller, we feel like TeamGroup has optimized the firmware and pSLC cache towards a more consistent experience over hitting record numbers. This, in our mind, is a good thing and helps make this drive a potential diamond in the rough.

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A Reddit user shared the 16TB SSD they bought on eBay for less than $30 (EUR 25), which only contained a board and a microSD card hot-glued with some weights to make it feel like a legitimate drive. u/Hartkralle shared their find, saying that they buy from these suspicious listings when they come across them. Since eBay has a robust consumer protection policy, they get their money back while the seller loses their account.

16 TB SSD for only 25€? What could go wrong? from r/pcmasterrace

"I buy one, check if it's legit or not, and if not, [I] report the seller to eBay. I get my money back, and they (the seller) lose [their] account,” u/HarkKralle said in a comment. “If I couldn't ensure that the money would flow back, I wouldn't do it.”

Another Redditor said that they appreciate what the OP was doing, but they were “99.99% positive” that the scammer would have another account in an hour. The OP replied, saying, “Possible, but even that it's an hour they cannot use to scam people and proof/information for more people that scams like this exist.”

Scams like these have been around for decades now. One commenter even added that back in the ‘90s, they used high-quality 60-minute VHS tapes for their work, but one time received cheap, low-quality tapes that could only hold five minutes of footage instead. The sample that u/Hartkralle showed is also relatively low effort. Because of the ongoing memory and chip shortage, we’ve seen exceptionally good clones of Samsung 990 Pro SSDs, one of the best SSDs you can buy today. They have become so sophisticated that the most reliable way of spotting if they’re fake is to check them on CrystalDiskInfo.

One of the downsides of these fake drives is that you won’t get the read and write speeds that you’d expect from a modern SSD. But the bigger issue here is that using them could lead to complete data loss. For example, the fake drive that u/Hartkralle bought reports a capacity of 16TB, but the microSD card inside it is only 60GB. So, if an unsuspecting user transfers more than 60GB of data, they’d end up corrupting everything stored in the drive.

A 2TB Amazon Basics Portable SSD already costs almost $360, while an 8TB SSD from reputable brands like SanDisk, Crucial, or Lexar already hit $850. So, someone who doesn’t follow developments in the tech industry and stumbles across this cheap drive might think they’re getting a steal, when, in reality, they’re the ones being stolen from. Thankfully, eBay’s consumer protection allows people who were scammed, intentionally or otherwise, to get their money back — that is, if they know they were scammed in the first place.

We've seen a lot of dead GPUs around here, some of which have been brought back to life in the most fascinating ways possible — this one we found on the r/SerbiaGaming subreddit is no different. An unlucky gamer found himself a savior when their RTX 3070 died, and a repair shop demanded 12,000 Serbian Dinars, or roughly $120, to repair it. That savior was none other than the OP's own father, who fixed his dead GPU with a salvaged capacitor from an old radio, as you can see in the embedded post below. We reached out to the poster for additional details.

Stara škola električara - najbolja from r/SerbiaGaming

u/External_Length_8877 explained how their GPU died in the first place. It was a pretty easy deduction since they found a capacitor knocked out of place, between the card and the radiator. Fallen capacitors can't just be put back; you need a proper replacement, which in this case would be a 16V, 270 μF hard polymer capacitor, no longer than 3mm.

Since the actual capacitor is not that easy to find in the region, the OP's father came up with a temporary solution instead. His son tells us that, aged 55, Alexander has been working as an electrician and a welder for the past 35 years, so he carries a lifetime of experience with him. Today, he works as a brigadier maintaining power lines in Serbia. His son describes him as a "real family man" who knows how to work on pretty much anything. Apparently, that list includes highly delicate graphics cards as well.

Alexander used a different, cheaper, and larger capacitor to replace its fallen comrade. It sticks out from the card, yet it works. Some people in the comments even said it fits the Gigabyte's variant's futuristic aesthetic, but the capacitor itself isn't suited for long-term usage because of its higher resistance, which would let the clocks run unchecked.

Moreover, the Redditor's father also replaced the old thermal paste with a "special" one that is designed for the high-voltage lines he works on at his job. They replied to a few comments saying the GPU's peak temp during gaming doesn't exceed 80°C. That may sound high, but keep in mind that everyone has different ambient temps. As we mentioned, the new capacitor also has significantly higher resistance than the original one, so perhaps that contributes, too.

Oftentimes, we just have to look inward to find inspiration, and this story is surely serving as bonding material for the father-son duo. OP is still trying to find the right component, so this serves as only a temporary solution to what is a $120 problem otherwise.

AMD continues to squeeze more life out of its AM4 platform as a newly listed prebuilt gaming PC has been spotted powered by the Ryzen 7 4700LE. This OEM-exclusive CPU is based on AMD's Zen 2 (Renoir) architecture, all the way back from 2019, and was silently released by the company back in March 2026. The prebuilt gaming PC featuring the CPU is currently listed by Chinese system integrator Qehi on Amazon with a price tag of $799.99. It additionally comes with an Nvidia RTX 3050 8GB graphics card, 16GB of DDR4 memory, and a 512GB M.2 NVMe SSD in a fish-tank style chassis loaded with six RGB fans.

Glancing over the specifications, the Ryzen 7 4700LE comes with eight cores and 16 threads, along with a maximum boost clock speed of 4.2 GHz. The chip also packs 12MB of total cache and a rated TDP of 65W, meaning that it generates less heat and requires a less demanding cooling solution. This should make it suitable for small form factor builds, although one should note that it does not come with onboard graphics, thus relying on a discrete GPU.

In a similar move, AMD had announced the return of the Ryzen 7 5800X3D last month as a special 10th Anniversary Edition, giving its popular AM4 gaming processor a second lease on life. By doing so, the company not only offered gamers a potent yet affordable CPU amid rising component prices, but it also allowed existing AM4 users to upgrade their CPUs without switching to a whole new platform.

While it won't rival AMD's modern processors, the Ryzen 7 4700LE should still be capable of handling everyday workloads and potentially some modern games when paired with the right GPU. OEMs and system integrators additionally gain benefits by making use of existing AM4 motherboards and DDR4 memory inventory, allowing them to build systems at a much lower cost compared to AM5-based systems. The CPU could also help make entry-level gaming PCs more accessible by giving budget-conscious gamers another option at a time when pricing for components like RAM, SSD, and GPUs continues to rise, thanks to the AI boom.

Intel is working on a version of its Nova Lake-S processor platform codenamed Dunlow that will offer up to 28 cores and will target entry-level server and workstation applications, according to shipment manifests located in the NBD database by @x86deadandback.

Formally, Intel's codenamed Dunlow platform will succeed the company's Catlow platform with Xeon 6300P-series CPUs and will support Xeon E-class Nova Lake-S processors (presumably) with up to 28 cores that feature a dual-channel memory subsystem, come in an LGA1954 form-factor, and have a processor base power of 95W, according to shipments manifests at NBD data.

Intel's next-generation Core Ultra 400-series platforms for desktop computers, codenamed Nova Lake-S, allegedly feature up to 52 cores, which include up to 16 high-performance Coyote Cove cores and up to 32 energy-efficient Arctic Wolf cores in the compute tile, as well as four low-power Arctic Wolf cores presumably in the SoC tile. These Nova Lake-S CPUs are aimed at enthusiasts and reportedly pull up to 474W with a single purpose: to offer unbeatable performance and feature set to put Intel back on the map of enthusiast-grade platforms currently dominated by AMD.

By contrast, the Dunlow platform seems to be a completely different kind of animal. The CPU deliberately features 28 cores and up to 95W PBP (TDP). All Xeon processors except Xeon 6700E, Xeon 6+, and some Atom-based solutions for specialty applications released to date have only featured high-performance cores. Even Intel's Xeon 6300P-series 'Raptor Lake-E' based products feature up to 12 P-cores to offer higher sustained all-core frequencies. Therefore, unless Intel plans to offer energy-efficient cores in its next Xeon CPU aimed at entry-level servers and workstations, we may be dealing with a very special processor that features 28 P-cores that is designed to beat all desktop-grade platforms in demanding applications.

While, for now, 28 P-cores inside Nova Lake-S processors for the Dunlow platform is speculation, it should also be noted that 28 cores do not naturally derive from a 16P+32E desktop design and are impossible to derive from a notebook-grade 8P+16E design. Also, Intel typically does not create server/workstation products by fusing off nearly half a desktop die (it does not even matter whether it disables some P-cores and some E-cores, disabling 20 cores in a 48-core tile hardly makes a lot of sense).

A Nova Lake-S CPU for Dunlow featuring a compute tile with 28 P-cores would resemble the abandoned Raptor Lake-32C, which featured an all-P-core design aimed at workstations and entry servers before being canceled. It is also possible that this could be a derivative of a small Xeon die adapted to an LGA1954 packaging and dual-channel memory to reduce platform costs. At the end of the day, many server applications like storage or web hosting do not need extremely high memory bandwidth, so two DDR5 channels could be enough.

Another reason for Intel to release a Nova Lake-S CPU with up to 28 P-cores is to fill the gap between high-end enthusiast-grade desktops that feature up to 16 P-cores and expensive Xeon 6 server and workstation CPUs that may start at 16 cores, but feature an octa-channel memory subsystem that is costly and is an overkill for many applications. Also note that since Xeon 'Diamond Rapids' processors with an octa-channel memory subsystem have been canceled, the gap between desktop and high-end server CPUs just gets way too wide in 2028, making Nova Lake 28 P-core silicon a potentially viable option.

Nvidia is making a new set of cards, and no, they won't make it among the best graphics cards. The aptly-named GeForce Trading Cards Series 1 are a set of limited edition trading cards that feature graphics cards, games, and tech demos from Nvidia's history, and the company is giving out packs of them for free at upcoming events throughout the summer.

Nvidia shared a short teaser showing off some of the designs, which feature some iconic demos like Nvidia's Chameleon and Medusa demos, along with photos of iconic Nvidia GPUs like the NV 1 and GeForce 3. There are 11 designs in total, including one "checklist card" for keeping track of the cards you've gotten.

The cards feature a black, PCB-like design with a GeForce logo, and the cards are numbered on the front (one card shows 01/11, again pointing to 11 unique designs). On the face of the cards is a border reminiscent of a PCIe connector. Here are all of the designs:

• NV1
• GeForce 256
• GeForce 3
• GeForce 7800 GTX
• GeForce 10 Series
• Bubble, Chameleon, and Medusa demos
• 'The Way It's Meant To Be Played' card
• GeForce RTX 2080 Ti Cyberpunk 2077 Edition

Although there's plenty of money in collectible card games, Nvidia is giving away the GeForce Trading Cards for free. The company says they'll be available at upcoming live events, as well as giveaways throughout the Summer of RTX.

Calling the cards "Series 1" implies Nvidia plans on making more collectible cards in the future, likely as party favors during Summer of RTX, which has become a staple giveaway event over the past several years. There are certainly far more tech demos and GPUs to pull from than what are featured in this short teaser.

Nvidia has yet to update its event calendar on the Summer of RTX page, which is filled with events from the last month, like Computex and Summer Game Fest. Nvidia says it will be giving away packs at Bilibili World, QuakeCon, and Gamescom.

Outside of events, you can keep an eye on the GeForce X account, which has been posting giveaways (amongst plenty of direct GeForce promotions) over the summer. Currently, Nvidia is giving away 10 packs on the GeForce subreddit, as well.

AMD is expected to announce its next-gen mobile CPUs at CES 2027, but leaks have already started to pour in, giving us a decent idea of the performance we can expect. Codenamed "Medusa Point," the Red Team's upcoming lineup will likely be based on the Zen 6 microarchitecture, and one of the SKUs has just popped up on Geekbench. It scored much better than the previous leak, beating most of its contemporaries.

The part showed up as "AMD Eng Sample 100-000001713-33_N" and was marked under "AMD Plum-MDS1," which we know is the platform associated with Medusa Point. It's a 10-core (4+6) chip, with 20 threads, clocked at roughly 2.0 GHz, carrying 10MB of L2 cache and 32MB of L3 cache. The L3 cache and clock speeds might be misreported. Currently, AMD only makes two other 10-core mobile parts — Ryzen AI 9 365 and Ryzen AI 9 465, so we're most likely looking at a purported Ryzen AI 9 565 here.

Coming to the scores, the chip netted 3,174 points in the single-core test and 15,092 points in the multi-core test. Both of those numbers are higher than the Strix Point flagship APU, the Ryzen AI 9 HX 370. On average, that SKU sits around 2,600 single-core points, so the Medusa Point score is 22% higher. In multi-core, the AI 9 HX 370 gets 13,400 points, making our main contender 13% faster on average.

It even beats the Strix Halo flagship, the Ryzen AI 9 Max+ 395, by over 400 points in the single-core benchmark, but loses in the multi-core test. Of course, the onboard graphics is no comparison between the two. Compared to a prior leak also showcasing a 10-core Medusa Point APU, this new listing is significantly better. The previous one came in at only 2,300 single-core and 13,002 multi-core points.

It seems like Zen 6 offers a noticeable leap in performance based on architectural improvements, since the core count between the chips we compared is identical. It's too early to judge anything, though, since Medusa Point is months away at this point, and this is just one SKU from the lineup. The top-end parts almost carry a mandate to be faster than their direct predecessor to be even worth releasing; it's the midrange where the real value proposition lies.

After announcing it last month, the first AMD EXPO Ultra Low Latency (ULL) memory kits are finally available; and with up to an 80% jump over already inflated RAM prices in tow. HardwareLuxx was able to snag a kit of G.Skill's new Trident Z5 NeoX RGB memory to see how ULL performs, and the results don't quite justify the extra cost. At most, the publication found just a 4% improvement compared to non-ULL kits.

That aligns with AMD's original claims about ULL. When the company announced the initiative last month, it also cited a 4% improvement over standard EXPO. However, AMD claims that ULL offers a 4% improvement on average, while HardwareLuxx only found that large of an improvement in a single game: F1 25. AMD reached out following publication and noted that its 4% average was across a wide variety of titles, and that there are inconsistences between each game, with some titles showing little to no benefit.

HardwareLuxx tested a 2 x 16GB kit at 6,000 MT/s with primary timings at 36-36-36-76. Compared to standard EXPO/XMP DIMMs, a lot of the optimization with ULL DIMMs comes from tuning the subtimings. The primary timings are largely the same as what you'll find on a standard EXPO kit, short of tWR (write recovery), which is lower on the EXPO ULL kit. Better binning of the memory ICs allows for more aggressive subtiming optimization, as HardwareLuxx notes, rather than relying on timings primarily concerned with stability.

In games, the ULL kit showed clear performance improvements, no matter how minor they were. In F1 25, the ULL kit outclassed a DDR5-6000 CL26-36-36-96 kit by 4.2%, and beat out JEDEC standards at 5600 MT/s by nearly 14%. Similarly, in Cyberpunk 2077, the ULL kit was around 3.7% faster than the standard EXPO kit, and 12.7% faster than JEDEC standards. The outlet also tested Arc Raiders, Baldur's Gate 3, and Counter-Strike 2; however, the ULL kit didn't offer a meaningful performance improvement in any of these titles.

The outlet also tested 7-Zip, though with only minor differences between ULL and non-ULL memory. The most interesting results are from the microbenchmarks available in AIDA64, which HardwareLuxx also ran. ULL showed largely similar copy and read throughput, but write throughput was 9.4% higher with ULL compared to stock EXPO.

Although there's a performance benefit, it's minor, and HardwareLuxx notes that "manual tuning still allows for the maximum possible optimization."

The particular kit that HardwareLuxx tested doesn't have the extreme ULL price increases we've seen elsewhere. It's currently available for sale for $530, which is only $20 more than a kit of G.Skill's Trident Z5 Neo RGB memory at DDR5-6000 CL36. It's actually gone down in price (it was originally listed at $550), while kits with more aggressive timings have increased in price.

The NeoX DDR5-6000 CL26 kit, for example, has jumped up $50 to $1,150 — yes, that's for a 2 x 16 GB kit still — while the CL28 kit has jumped up to $1,030 (a $30 price increase). Two weeks ago, we saw non-ULL kits selling at $560 and $700 for CL28 and CL26, respectively, creating a large delta in price between ULL and non-ULL kits. Now, those kits are selling for $700 and $900, respectively.

The introduction of ULL couldn't have come at a worse time, as the ongoing DRAM shortage continues to raise the cost of building a PC around the world. Adding a premium on top of those already inflated prices is tough to justify, even if that premium is modest — especially for mainstream CL36 and CL30 kits, the "ULL tax" is essentially null. The good news is that you can largely achieve what ULL offers on your own, at least given that you have the patience to sit through tuning your memory for single-digit gains.

JEDEC has released its new specification that aims to push down the pricing of the ultra-expensive HBM that powers the fastest AI processors. While the new standard will not help relieve the DRAM shortage as it uses large HBM4 DRAM devices, it can make high-bandwidth memory a bit cheaper as it enables attaching SPHBM4 memory stacks without advanced packaging and using inexpensive organic substrates.

The standard's body published the specification of SPHBM4, Standard Package High Bandwidth Memory (JESD330-4), that combines HBM4 DRAM ICs with standard packaging and a fast 'narrow' 512-bit interface. Here are the details.

HBM4 performance with a 512-bit wide interface

Although 1024-bit and 2048-bit interfaces used by HBM3 and HBM4 memory deliver unbeatable performance, their wide interfaces consume significant silicon area inside processors, they require expensive interposers, and advanced packaging technologies with limited capacity, such as TSMC’s CoWoS, for integration with host processors. The upcoming SPHBM4 memory continues to use the same HBM4 DRAM stacks as JESD270-4, but swaps the conventional HBM base die for a new SPHBM4 PHY/buffer die featuring a narrower 512-bit interface that enables mounting on standard organic substrates without using sophisticated packaging methods for integration. To offset the effect of the narrower interface, SPHBM4 supports considerably higher data transfer rates ranging from 22.4 GT/s to 46.0 GT/s.

Instead of connecting to the host processor using a 2048-bit memory interface like HBM4, SPHBM4 uses 32 independent 16-bit DDR channels organized into eight Quad Channels. Since 'Quad Channel' is a new term, let us explain how things work. Internally, an HBM4 stack contains 32 memory channels, each 64 bits wide, for a total external interface width of 2048 bits. SPHBM4 needs to 'convert' the 2048-bit internal I/O onto a 512-bit external interface, which is why it groups every four HBM4 channels into a Quad Channel. As a result, externally, a Quad Channel exposes 64 data pins (4 × 16 bits), which replace the 256 data pins (4 × 64 bits) that those four HBM4 channels would normally require. To preserve bandwidth, these 64 pins operate at four times the data rate of the original HBM4 interface.

While SPHBM4 dramatically increases I/O bandwidth, it does not make the DRAM array itself faster. The HBM4 memory core retains the same fundamental architecture and timings, including core frequency, row activation, precharge, and refresh operations, though the additional PHY is expected to introduce some latency. For example, the DRAM core runs at only one-quarter of the external interface frequency, which means 2 GHz in the case of SPHBM4 with a 32 GT/s speed bin.

The major change is the new base die, which implements a high-speed SerDes-like PHY that maps each 16-bit external channel to four conventional 64-bit HBM4 channels. As a result, SPHBM4 introduces equalization, lane training, BER requirements, and other high-speed signaling features that are unnecessary in HBM4’s slower, wide parallel interface. To support transfer rates of up to 46.0 GT/s/s per pin, each Quad Channel uses a shared command/address interface protected by forward error correction (FEC), while data transfers rely on dedicated differential write (WCK) and read (RCK) clocks, as well as ECC and error-reporting signals.

When it comes to capacity, SPHBM4 can use stacks containing 4, 8, 12, or 16 DRAM dies featuring 24 Gb or 32 Gb densities, so the largest standardized SPHBM4 configuration is a 64 GB memory stack built from sixteen 32 Gb DRAM dies, identical to the maximum capacity supported by HBM4E.

Cheap HBM at last?

The standard supports bump pitches greater than 90 µm and channel reaches up to 20 mm, which are two features that enable dropping the expensive interposer and using less-expensive organic substrate routing. However, getting rid of the interposer and CoWoS (or similar) packaging does not automatically make SPHBM4 inexpensive. SPHBM4 still requires massive HBM4 DRAM ICs, 2.5D packaging, a complex base die (which is likely costlier than the one used by conventional HBM4), and advanced package assembly with through-silicon vias. In addition, SPHBM4's narrow interface consumes significantly less die perimeter and silicon area inside processors, which makes it more attractive to companies that strive to install more compute capability and/or intend to install more memory stacks around their processors. However, we are still talking about a niche high-performance memory technology that will address select applications and will barely rival HBM4 directly.

When it comes to maximum performance, HBM4 moves the data at 8 GT/s (though most controllers and chips support higher data rates), so one HBM4 stack can offer bandwidth of 2 TB/s. HBM4E is set to up data transfer rate to 12 – 12.8 GT/s, therefore increasing peak bandwidth to 3 – 3.3 TB/s per stack. By contrast, one SPHBM4 with a 46 GT/s interface can hit 2.944 TB/s, though do not expect the initial versions of SPHBM4 to hit the maximum speed. Therefore, it is likely that HBM4, HBM4E, and C-HBM4E will maintain a performance lead in terms of bandwidth over SPHBM4 in the foreseeable future.

HBM4 latency will still probably have an edge over SPHBM4. HBM4 essentially connects to its host processor almost directly through a very simple interface. By contrast, SPHBM4 inserts a much more sophisticated PHY that performs serialization/deserialization, lane training, FEC handling, and other operations that can add a few nanoseconds of latency. This may not be a big problem for some applications, but inference benefits a lot from low latencies.

When it comes to power and voltages, HBM4 and SPHBM4 share the same DRAM core voltage because SPHBM4 reuses standard HBM4 DRAM stacks. However, I/O is different: HBM4 leaves the interface voltage up to memory vendors and allows implementations at 0.7V, 0.75V, 0.8V, or 0.9V, depending on the desired balance between power, speed, and signal integrity. By contrast, SPHBM4 standardizes the external I/O at 0.75V.

Also, HBM4 moves data over a very wide interface with many slow parallel links that tend to be very energy efficient. By contrast, SPHBM4 moves the same amount of data through one-quarter as many wires, which run roughly four times faster. High-speed data transfer tends to be less energy efficient than 'slow' data transfers over a wide interface. Keeping in mind SPHBM4's rather sophisticated PHY that converts a wide interface into a narrow interface, which is likely a power-hungry process. Nonetheless, the 4X lower number of drivers and receivers could tangibly reduce the power consumption of SPHBM4. That said, without implementation details from DRAM makers or a processor developer, it is impossible to conclude which memory type has lower power consumption.

Last but not least, SPHBM4 essentially trades manufacturing challenges that arise from using silicon interposers for an engineering challenge of developing an extremely sophisticated base die/PHY. Developing and manufacturing such a base die should not be a problem for foundries. However, it remains to be seen whether DRAM makers can design and produce SPHBM4 with decent power efficiency. After all, both Micron and SK hynix work with TSMC to build C-HBM4E and HBM4E base dies, whereas Samsung's memory division uses base dies produced by Samsung Foundry.

China factor

One interesting aspect of SPHBM4 is whether Chinese developers of AI accelerators can benefit from this technology. In theory, Chinese developers like Biren, Huawei, Moore Threads, and other blacklisted companies that cannot use TSMC's chip manufacturing or packaging services could become one of the biggest beneficiaries of SPHBM4, perhaps even more so than the U.S.

First up, a smaller shoreline directly benefits chips that are made using trailing nodes, as it enables packing more compute capability into them without sacrificing memory bandwidth or capacity. Secondly, Chinese OSATs currently do not offer CoWoS-like technologies, so eliminating the interposer and using advanced organic substrates is a benefit.

However, SPHBM4 still requires HBM4 DRAM stacks, and today, Samsung, SK hynix, and Micron are the only companies capable of producing them, while China-based CXMT can barely make HBM2E. Furthermore, building a 46 GT/s PHY is very hard and will likely be challenging for Chinese IC developers.

Nonetheless, assembling SPHBM4 packages on organic substrates is arguably more aligned with China's existing manufacturing base, so if local DRAM makers eventually develop competitive HBM4-class memory, SPHBM4 could substantially reduce one of the country's remaining infrastructure gaps.

Summary

JEDEC's SPHBM4 looks like a promising standard that can potentially address a broader range of applications than HBM4 itself due to lower integration cost. Still, HBM4, HBM4E, and C-HBM4E will maintain performance leadership, which will make them a preferable choice for flagship AI accelerators in the coming years.

Sipearl has been developing a custom CPU, especially designed for high-performance workloads, named 'Rhea', for over five years. In late May, it was finally announced that the company had received the CPU from the fab, initiating the bring-up process, which is a significant milestone. The HPC CPU sports over 80 cores, in addition to an innovative memory subsystem. We spoke directly with Craig Prunty, vice president of marketing and business development of SiPearl, to learn the fine-grained details.

The Rhea CPU is intended to reach markets by late 2026 or early 2027, and won't be the most performant HPC CPU on the market. Regardless, SiPearl told us at Computex that there is interest both towards Rhea and its successors from rather unexpected parties, so the company is in with a chance to become a successful CPU designer over time.

Rhea's long road toward reality

SiPearl's Rhea (or Rhea1, how the company prefers to call the unit these days) sports 80 Arm Neoverse V1 cores with two 256-bit Scalable Vector Extension (SVE) engines for fast vector computations in FP64, FP32, BF16, and INT8 formats; 1 MB of L2 per core; 80 MB system-level cache (SLC), and 104 PCIe 5.0 lanes. The CPU has a unique memory subsystem comprising four HBM2E interfaces for 64 GB of on-package HBM2E stacks for applications that require massive memory bandwidth (think supercomputer applications like fluid dynamics) and four DDR5 interfaces supporting two 256 GB DIMMs per channel, for up to 2 TB of memory per socket. Rhea comprises 61 billion transistors and is fabbed by TSMC using its N6 process technology.

SiPearl received the first samples of its Rhea processor in mid-May, and the CPU is currently in bring-up mode. So far, it looks like the very first silicon works just fine, so the company will not have to respin it, which means SiPearl has a good chance of shipping it to customers in the coming quarters.

"The Rhea1 CPU is in its 12-week bring-up process since May 13, and it works exactly as it was designed to do," said Craig Prunty, vice president of marketing and business development of SiPearl, in an interview with Tom's Hardware Premium. "The test version of Rhea1 will be available for testing by partners and EU collaborative projects at the end of the bring-up process. The general availability of Rhea1 is scheduled for end of 2026."

Getting the very first silicon to work correctly is a stroke of good luck, especially for the very first product from a startup that has never designed a complex CPU before. However, it has taken the company over five years to define and then develop its processor, an unacceptably long cycle. With Rhea, SiPearl not only built its processor, but it actually built the company, Craig Prunty admitted in an interview with Tom's Hardware. The company once tried to work with a contract chip designer, but eventually canceled the deal and formed five in-house development teams in Europe. Since these teams have never worked together before, the processor was delayed a number of times from 2023 to 2026. It, of course, gained eight additional cores in the meantime, but this hardly justifies a three-year delay.

"We have five development teams in Europe: Maisons Laffitte, Massy (both in the Paris region), Grenoble and Sofia Antipolis in France, Barcelona in Spain," Prunty said. "The Bologna team is currently being put together."

One of the reasons why SiPearl has so many locations is that it wants to shrink its development cycle to around 18 months to offer competitive CPUs.

Now, because it is 2026, HBM2E memory is extremely hard to get, which is why Rhea1 will be a limited-run processor only available to select clients and partners. In theory, this is not something that is going to happen to SiPearl's Athena processor for aerospace, defense, and government applications, which is essentially Rhea with 16, 32, 48, 64, or 80 Neoverse V1 cores and without onboard HBM2E, which will be sold based on market demand sometime in 2028. Though, do not expect Athena to have a very long lifespan. SiPearl hopes to tape out its 2^nd Generation Rhea (Rhea2) processor in 2027. That CPU will not have onboard HBM, so its derivatives for aerospace, defense, and government systems will probably follow shortly, making Athena1 obsolete.

Opening unexpected doors

To a large degree, the first-generation Rhea processor is more than just a product for SiPearl, as it is meant to put the company on the map of data center and supercomputer CPUs and proof that a European entity can develop a competitive processor. SiPearl originally intended to address European supercomputers and sovereign AI infrastructure with Rhea1. However, many commercial cloud providers in Europe and the Middle East plan to evaluate the platform and even deploy it (albeit not widely) as they want to ensure they have access to technology in the current geopolitical situation.

“Rhea1 is the unique European server CPU,” Prunty said. “We find that European sovereignty is exportable – customers not only in Europe, but also Middle East and Asia have expressed interest in our processor because it is designed in Europe. They like that we have full control of the source code. They want freedom from embargos, back-doors, kill switches."

While the CPU is the industry's third processor to use a hybrid memory subsystem comprising HBM2E and DDR5 (for which SiPearl deserves accolades), it is very late to market, so while it is natural that various sovereign AI and HPC deployments and Europe-funded supercomputers will deploy it, expecting commercial companies to deploy Neoverse V1-based machines in 2027 is pretty naïve. However, commercial companies will validate and test the platform, possibly do some software porting, and ensure that it works as intended. Some companies might even deploy Rhea1 in their data centers. As Craig Punty puts it, Rhea1 could open rather unexpected doors for SiPearl.

As it turns out, geopolitical tensions and export controls force big players to look for alternatives to American hardware, which is where SiPearl's processors could fit rather well. SiPearl is based in France, it has R&D centers around Europe, it licenses technologies from Arm, and produces its CPUs in Taiwan. The company cannot ship its CPUs to China due to export restrictions, but it can sell them to clients in Europe and the Middle East without restraint, which is its indisputable trump card. Assuming that SiPearl offers competitive performance, its CPUs are almost guaranteed to be adopted by sovereign AI and HPC deployments in Europe, which means guaranteed revenue.

One might argue that since SiPearl uses Arm's cores, it will inevitably compete against Arm's AGI processors eventually. Indeed, it will, once its CPUs address large CSPs. Which is why the company must stay ahead of Arm's own offerings in terms of performance and features, or at least be on par with them.

Seine reference server

For now, SiPearl is bringing up its Rhea1 processor in its labs. The company already has its Seine reference server design that is primarily designed for validation, testing, evaluation, and software porting. For AI and HPC deployments, Seine can be configured for one Rhea CPU and two accelerators; for more traditional supercomputer needs, two Seine motherboards can be installed into one chassis, then interconnected using PCIe cables with the CCIX protocol on top to get a classic 2-way server.

Speaking of the Seine motherboard, it should be noted that since SiPearl uses it for bringing up the CPU, it had to be made perfect so to exclude any possible problems on its side. To that end, it uses costly components and an ultra-expensive 26-layer printed circuit board to ensure signal integrity, reduce crosstalk, provide the best quality power possible, and ensure maximum mechanical stability.

The Seine server reference design will be used by Bull to build servers for the Jupiter supercomputer, according to Prunty. Other server suppliers may follow and adopt the same design to offer their servers based on Rhea1.

"We had also a partnership agreement signed with HPE to work together on European supercomputers tender offers," Prunty said. "Our CPUs will also equip other servers as part of European AI gigafactory project."

Sipearl's Rhea readies up

Developing a supercomputer-grade processor in Europe is already quite an achievement, but developing a CPU that works fine from the first silicon could indeed be considered a breakthrough for a startup. In addition, SiPearl tapes out its Rhea in a good time when potential customers may adopt it despite the fact that Neoverse V1 technology that powers the chip is outdated. As it turns out, export controls made not only sovereign AI and HPC deployments look in SiPearl's direction, but private CSPs in Europe and the Middle East also plan to evaluate its processors.

SiPearl admits that a five-year development cycle is too long for a modern CPU, though it remains to be seen whether it can indeed shrink it to 18 months. The company already has five development sites and is building another one, so it looks like it the company is on the right path. Yet, SiPearl must prove that it can develop Arm-based processors that are competitive against Arm's own AGI as well as other Arm-powered data center CPUs, something that will not be easy to do given the fact that SiPearl is a startup, whereas its potential rivals are billion-dollar companies.

Of course, SiPearl will always have a couple of trumps up its sleeve: the European Processor Initiative (EPI) as well as sovereign AI and HPC deployments that will always prefer locally developed CPUs no matter what. Whether such businesses are enough to build a world-class processor developer is something that remains to be seen, but at the very least, SiPearl will not vanish into oblivion like many other European CPUs makers.

What makes Cooler Master’s new V4 Alpha and V8 Ace 3DHP air coolers stand out against their competitors? Well, it’s in the name of the product – the company’s new 3DHP (3D heatpipe) technology represents a serious advancement in cooling.

Traditional copper heatpipes are typically formed in a “U” shape, and work well enough in most scenarios. But Cooler Master’s 3DHP heatpipes look more like a trident, with three ends instead of two. There’s more to the tech, which we will cover in more detail below.

Additionally, the V8 Ace 3DHP features two of the strongest fans we’ve ever tested from a Cooler Master product, with liquid crystal polymer blades and backed by a six-year warranty.

Let's take a look at the specifications and features of these coolers. Then we’ll go over thermal and noise benchmarks to decide if the V4 Alpha and V8 Ace 3DHP air coolers are good enough to make our list of the best CPU coolers we’ve tested.

Cooler specifications

Features of Cooler Master’s V4 Alpha and V8 Ace

▶️ Innovative 3DHP Heatpipes

Both the V4 Alpha and V8 Ace are powered by Cooler Master’s innovative 3DHP heatpipe technology. To simplify things somewhat, while most heatpipes are “U” shaped, with one prong of each heatpipe on the left and right sides of a heatsink, 3D heatpipes add a prong in the middle to give it more of a trident shape, enhancing the efficiency of thermal transfer.

Traditional heatpipe setups don’t usually fully saturate the fins of a heatsink, only providing 70% fin utilization, according to Cooler Master. This makes sense, as you’ll often see that temperatures continue to rise in extended-length cooler testing as the fins become more fully saturated. Cooler Master claims that with its 3D heatpipes, fin utilization is increased to 95% or more. We’ll see how that plays out in our benchmark testing shortly.

▶️ RAM Clearance

RAM compatibility is excellent with both of these coolers. The V4 Alpha doesn’t overhang or interfere with RAM DIMMs at all, allowing for compatibility with all sizes of DDR4 or DDR5 DIMMs.

The V8 also has wide RAM compatibility. Its intake fan does overhang the DIMM slots, but if your RAM is particularly tall – like our T-Force Xtreem DDR5-7200 featured below – the sliding rail system allows you to easily adjust fan position, so things fit properly. We had to raise the fan by a few millimeters for proper clearance, but I think the sticks I’m using are about the tallest on the market, at 48.8mm height. Officially, RAM up to 45mm in height is supported.

▶️ 30mm thick Liquid Crystal Polymer fans

There’s more to a cooler than just the heatsink. The included fans have a direct impact on aesthetics, noise levels, and overall thermal performance. The fans on the V8 Ace 3DHP are made for longevity, built with liquid crystal polymer (LCP) blades and loop dynamic fan bearings.

They come pre-installed with a sliding rail system, allowing for simple installation and height adjustment.

▶️ Aesthetics

You might notice the top of the V8 Ace 3DHP looks like it has eight gigantic heatpipes – but note they’re not actually real heatpipes. Does that mean it’s only decorative, and serves no real purpose? I wouldn’t say that. The “fake” heatpipes here seem to be made from metal and are cold to the touch, indicating that they do have the ability to absorb heat.

I decided to take the cooler apart for a better look at this piece, and it appears the primary function is actually to prevent air leakage. If you look closely at the picture below, you’ll see the fans are slightly taller than the heatsink. If that’s not a concern for you and you prefer an “old-fashioned” look that shows the ends of the copper heatpipes, the cooler works just fine without the top, though you’ll lose a small amount of thermal efficiency.

▶️ Packaging

The outer packaging highlights the design of the product in a colorful but subtle way, incorporating a purple background on the top and black on the bottom.

Pulling on the purple tab in the front reveals the fanciest inner packaging I’ve ever seen for an air cooler, seemingly designed for store displays.

Intel and AMD-specific models

Cooler Master sells versions of these coolers labeled specifically for Intel or AMD CPUs. We tested the AMD model with our 9950X3D. Both versions do come with mounting hardware for platforms from both companies, so you could install, say, an Intel-specific version of this cooler on an AM4 or AM5 CPU / motherboard.

But a Cooler Master rep told us that the AMD version has a flatter IHS, while the Intel version is more convex, to make the best contact with CPUs from each platform. The V8 Ace reportedly also has different internal liquid volumes to best target heat on each platform. We're told both versions target the same performance metrics, but you should use the correct cooler for your platform for the best results – as we did when running our benchmarks, shown below.

Included with the package are:

• Mounting hardware for AMD and Intel platforms
• 120mm fans
• Cryofuze thermal paste
• Installation manual

▶️ V8 Ace 3DHP AM5 Installation

To begin putting things together, you’ll first need to remove the default AM4/5 retention bracket. Next, place the studs over the exposed holes.

Afterwards, take the mounting bars and secure them with the included screws.

It’s time to apply the thermal compound. If you’re not sure how to do that, we have a handy thermal paste application guide that covers the different methods you can use.

After thermal paste is applied, take the CPU block and press it against the mounting bars, using the built-in screws to secure it in place.

Finally, you’ll want to attach both fans by sliding them into the rail system built into the cooler, then connect their cables to the motherboard’s PWM header.

Real-world testing configuration – AMD AM5 platform

We’ve tested coolers with both the Ryzen 9950X3D and its non-V-Cache sibling, the 9950X in the past year. There are some differences in how the 9950X and 9950X3D CPUs are impacted by thermal events. While the heat output of the CCDs of AMD’s 9950X3D is relatively balanced, the 9950X I used has one CCD that runs much hotter than the other, with a difference of over 10 degrees Celsius in some scenarios, shown below.

For now we’ve returned to using a 9950X3D for cooler testing, as it has a more balanced heat profile, and is almost certainly a more widely adopted CPU. The benchmark results shared in these reviews may differ from others because I emphasize results that are comparable to real-world use. This means I generally test CPU coolers inside of a closed desktop case, which increases cooling difficulty compared to other testing methods.

Many reviewers test coolers on open test benches, which have a combination of lesser airflow needs and lowered ambient temperatures. This results in making weak coolers appear stronger than they really are. Some publications have also used generic thermal plates to test cooling solutions. I reject both of these methods because they don’t accurately reflect real-world cooler conditions.

Our latest testing setup uses the FLOVA F50 computer case from Tryx.

This case features a unique “crossflow” fan that pulls air from the side, which the company claims is more effective than traditional intake fans. For air cooling tests, we’ve added a single Noctua NF-A12 G2 intake fan.

PBO Performance and maximum noise levels

We’re going to start by focusing on a traditional maximum performance test, with the CPU cooler’s fans allowed to reach their fastest speeds, for the best cooling possible.

Turning on PBO allows AMD’s Ryzen 9 9950X3D to stretch its legs to an extent and consume over 260W. Enabling PBO enables high power consumption and heat output, when using MSI’s X870E Carbon Wifi motherboard the CPU will reach its TJ Max (peak temperature) of 95 degrees Celsius (203 Fahrenheit) and thermally throttle to some extent with most coolers. When this throttling occurs, I’ve measured the average power consumption to determine performance.

You’ll notice there are two results for Cooler Master’s V8 Ace 3DHP, one marked with an asterisk. I wanted to include a test to see if there’s any point to using stronger or more powerful fans. When we tested the first iteration of Cooler Master’s 3DHP technology in the Hyper 212 3DHP, replacing the default fans with Montech’s flagship E28 fans resulted in ~5% better thermal performance.

Fortunately, the fans included with the V8 are strong enough to extract the maximum thermal potential of the 3DHP technology – the results are basically on par with the best coolers on the market.

The included fans are also a bit different than your average 120x25mm PC fan, measuring 30mm thick. At 45.6 dBA, their maximum noise level is audible, but those who prefer silence will be satisfied with our noise-normalized results.

The V4 Alpha’s thermal performance might not seem impressive at first glance, until you consider its noise level. Measuring at a maximum of 38.9 dBA, it is the quietest cooler we’ve tested in over a year.

200W thermal benchmarks

For the next thermal test, I leave the motherboard settings at their defaults, which results in a power limit of 200W when running Cinebench R23.

Thermal results in this scenario were similar to our first test, with Cooler Master’s V8 Ace taking second place. The V4 Alpha’s results were on the low end of our charts, but that’s more or less to be expected with its quiet, low-power fans.

150W + GPU thermal results

Our next test runs Cinebench on the CPU with a 150W power limit, while also running Furmark on MSI’s RTX 4070 Ti Super Ventus 3x OC. This causes the GPU to consume ~295W of power. This test is designed to emulate the thermals of games, which primarily stress the CPU and GPU.

You’ll see there are two results for Cooler Master’s V8 Ace: the result in blue was obtained after pairing the heatsink with Montech’s flagship E28 fans, which are extremely strong. The result in red was testing performed with the default fans included.

This test highlights the one “weakness” of Cooler Master’s 3DHP lineup – the reduced fin area results in worse thermal results when the internal temperature of the computer case is higher, such as you’d see in warmer environments or when your GPU is being fully utilized (like in gaming.)

Noise-normalized testing

Most testing is performed with the cooler tied to the default fan curve of our MSI X870E Carbon motherboard, but some of y’all prefer to see tests when the noise levels of coolers are equalized. This is especially important to those of you who prefer silent computers. This next test has the CPU cooler noise-normalized to 38.9 dBA, with PBO enabled for the Ryzen 9 9950X3D CPU.

This test is especially difficult because in addition to the reduced noise from the CPU cooler, our current test bench’s system fans are configured to run extremely silently, below the floor of the noise meter I use to measure dBA.

Most coolers can’t keep the CPU from reaching its peak temperature (TJ Max) in this stress test. Cooler Master’s V8 Ace did especially well here, with the second-best result we’ve ever recorded. The V4 Alpha’s results aren’t as impressive at first glance, until you remember that it is powered by only two heatpipes – it outperforms other coolers with four to six heatpipes!

Karhu DDR5 RAM thermals testing!

Your CPU cooler does not operate in isolation. It has an impact on not just your CPU’s temperatures, but also the other components in your build, like your RAM and GPU. To that end, I’ve run the Karhu RAM stress test. This places a load of ~153W on the CPU and ensures system RAM (DDR5 in my case) is fully stable. In this type of scenario, most AIOs tend to produce worse results than air coolers.

Both of Cooler Master’s 3DHP coolers performed exceptionally well in this RAM thermal test. The V8 Ace outperformed all competing dual-tower air coolers, and the V4 Alpha tied with Arctic’s Freezer 36-S for the best results we’ve seen that don’t include a dedicated RAM fan!

Conclusion

Cooler Master’s V8 Ace is an engineering masterpiece, using two 3D heatpipes and four standard copper heatpipes, combined with a single-tower heatsink to deliver thermal performance that beats most dual-tower heatsinks with eight heatpipes. Installation is simple, and noise levels are reasonable.

There’s not much more you could want in a cooler – except for a lower price. But as with all new cutting-edge technology, there’s an early adopter tax with a price tag of $119.99 for the V8 Ace. If you’re looking for a similarly powerful cooler with a lower price tag, I’d recommend Thermalright’s Royal Pretor 130. Alternatively, if you want a less-powerful, more-affordable option that incorporates Cooler Master’s three-pronged heatpipe tech, the Hyper 212 3DHP also impressed us in testing, and costs around $25. And of course there's the middle-ground V4 Alpha, which we also tested here and found to be one of the quietest air coolers you can buy. That model has a list price of $49, but was selling for $44 at Amazon when this was published.

I look forward to testing future products as Cooler Master continues to refine and improve its 3DHP manufacturing processes. I can imagine a future iteration of this technology will empower an air cooler stronger than anything previously possible.

Only a little while back, Phoronix got the chance to test-drive one of Nvidia's upcoming Arm-based Vera CPUs. In certain approved workloads, the chip put up an impressive showing, nipping at the heels of its Xeon and Epyc x86 competitors. In specific single-threaded scenarios, Vera "absolutely dusted the competition" (our words). But AMD had some things to say about the Phoronix test, firing back with its own metrics of a 3.3x performance gain over Vera for the projected output of a 100 kW rack of its hardware.

And Nvidia is already thinking about this future. It revealed that its next-gen Rigel Arm v9.2 CPU core, shipping as part of its Rosa CPU, will deliver even higher per-core performance than Vera's Olympus core within the same silicon footprint via "better instruction delivery," more L2 cache, and better memory handling.

Now, Nvidia is reasserting Vera's advantage for AI work by describing it with a new product category: a "max single-threaded CPU at scale" rather than a parallel-processing beast. Instead of simply maximizing the core count per socket, Nvidia says Vera's monolithic 88-core design is meant to provide strong performance per core under load, enough memory bandwidth per core to keep active cores supplied with data, and predictable latency.

Nvidia describes AI inference workloads as being bound by single-thread speed. For example, a reasoning AI will run the model for one step, and will run the model again as many times as it takes until the answer is generated. Since each step needs the output from the previous one, no amount of parallelism will help — the speed at which one thread can run is most important. The situation is similar in agentic workloads, as agent B can't get its work started without knowing what happened with agent A.

Vera's design, then, appears to be one aimed at both having and eating the proverbial cake: high single-thread speed with a large number of available threads. Vera is an 88-core design with SMT support for 176 total threads. And to supply each of those cores with adequate bandwidth, Nvidia says Vera talks to LPDDR5X RAM at 1.2 TB/s, and that its monolithic compute die keeps cores well fed and avoids bottlenecks thanks to 3.4 TB/s of core-to-core bandwidth. The company says the latter figure is 3x that of "any other data center CPU."

There are many ways to measure inter-core bandwidth, so direct comparisons are tricky at best, but given the bespoke design of Vera for AI inference tasks, the claim is at least plausible.

The company's latest blog post about the new silicon reiterates this point, claiming its new silicon delivers 1.8x higher performance versus its x86 competition in "loaded CPU workloads that represent agentic execution," 1.5x higher perf in coding workflows, and 3x faster work in database analytics.

The numbers Nvidia touts purportedly come from real-world scenarios, starting with those from Perplexity, whose usage of Vera in coding agent work delivered a claimed 1.5x performance increase over x86, and a 1.9x speedup running concurrent sandboxes.

The claimed speed increases are wider still in database workloads, with Starburst (federated database firm) clocking a 3x uplift in large-scale SQL analytics, while Redpanda's real-time analytics saw a claimed 6x latency drop. According to Nvidia, all this purported performance is delivered by Vera's particular architecture, one that aims to deliver maximal single-thread performance with high thread counts.

We should note that vendor-approved benchmarks should always be taken with a bucket of salt, particularly those for hardware in a field that can shuffle trillions of dollars in a single day. The company doesn't say which precise x86 chips it tested Vera against, but it's a fair guess that they're mid- to high-end Intel Xeon and AMD Epyc models.

Nevertheless, in the blog post, Nvidia describes a conundrum that's familiar to most any server administrator: big-iron server chips can pack obscene amounts of cores, making them ideal for processing many tasks at once. However, the more cores you add, the slower they need to be to keep thermal performance and power draw in check. But that scale is an obstacle for tasks that need to be done now, parallelization be darned.

And the architectural decisions involved in using chiplets to scale to high core counts aren't free, either. Nvidia calls this "chiplet tax", and it says that scaling using chiplets creates memory access and performance inconsistencies that Vera's monolithic design is specifically meant to avoid.

We've long emphasized the importance of high single-threaded performance for a fast and responsive experience for client PCs, and it seems like AI agents are going to end up placing similar demands on hardware as they do their thing. If that's how the agentic AI future plays out, Nvidia's particular design optimizations for Vera make greater sense than prioritizing core count above all, as it might be for a general-purpose server chip meant to satisfy different economic and customer demands.

We'll have to see if Intel and AMD respond with "max single-threaded CPUs at scale" of their own.

The GeForce RTX 50-series desktop graphics lineup has remained unchanged for just over a year now (since the introduction of the RTX 5050), and none of the conversations we've had at major trade shows suggests that a mid-cycle Super refresh will occur any time soon. But there are still signs that such an update could still happen at some point, and the latest sign comes from Seasonic, which has listed an RTX 5080 Super, an RTX 5070 Ti Super, and RTX 5070 Ti Super in its PSU wattage calculator.

You can click through the calculator and assemble a hypothetical system with these unannounced products inside.

To be useful, this calculator also provides board power numbers for these as-yet-unreleased cards, and that gives us another bit of juicy info. Given that no official specifications for these GPUs exist, it's impossible to say whether these figures are accurate. But it does allow us to speculate a bit on how they might stack up to existing products.

*As listed in Seasonic PSU calculator. Unconfirmed by Nvidia.

Seasonic gives this purported RTX 5080 Super a board power of 415W in its calculator, or 15% higher than the existing RTX 5080's 360W envelope. That makes sense, because the RTX 5080's GB203 GPU is already fully enabled, so any Super version of that card would have to lean on higher power limits and more aggressive clock speeds to see any baseline performance benefit.

That figure could also partially account for slightly higher power usage from 8 GB more GDDR7 memory on such a card. Past RTX 50 Super-series rumors have suggested that Nvidia will boost VRAM capacity on those products by moving to higher-density GDDR7 modules with 3GB of capacity each. GDDR7's power consumption as part of the overall board picture is relatively small, but more of it will still matter.

If Seasonic's figures are accurate, we should also expect a similarly sized TGP increase out of the RTX 5070 Ti Super, whose 350W rating is 17% higher than that of the RTX 5070 Ti. The RTX 5070 Super, meanwhile, gets only a 10% TGP bump over the RTX 5070, from 250W to 275W. Both of these cards rely on GPUs that are slightly cut down from their full available resources, so it's possible that Nvidia could boost their performance through a balance of enabling more Streaming Multiprocessors (SMs) in addition to boosting clocks through higher power envelopes.

Beware of extrapolating performance improvements directly from these percentages, though. Our own testing has shown that any real-world performance benefits from these power limit increases are likely to be smaller than those figures would suggest.

As our review of the MSI RTX 5090 Lightning Z showed, the largest performance boosts from higher power limits are likely to be concentrated in ray-traced and path-traced games, whose computational intensity is significantly higher than pure raster titles and is more likely to run the GPU into its power limits.

In any event, we shouldn't expect to see these products any time soon. Nvidia has instead been focused on getting more out of existing Blackwell silicon with software improvements such as DLSS 4.5 upscaling and Multi-Frame Generation multipliers up to 6X.

These technologies enable higher output frame rates and image quality with lower input resolution than past DLSS technologies, and the boost to both performance and image quality from those technologies in tandem has certainly made existing Blackwell products more appealing than they were at launch.

But as monitor refresh rates continue to climb thanks to ongoing improvements to OLED and LCD panels, and next-generation HDMI 2.2 connectors looming over 2027, a hardware update of some kind that boosts baseline performance and potentially implements support for those standards seems practical at some point. Given these primarily consumer-focused improvements, an announcement at CES 2027 or Computex 2027 might make sense. As with any future product rumors, however, only time will truly tell.

When Intel switched to a hybrid architecture with its 12th-Gen Alder Lake PUs, it removed AVX-512 support from the lineup entirely because the E-cores didn't support it. Since then, every subsequent generation has shipped without it... until now. Just today, a new Linux patch pushed in the RAID optimized path has revealed that AVX-512 is finally returning to Intel CPUs with Nova Lake, present on both P-cores and E-cores.

Intel has been working toward a unified AVX solution for the past few years, as it was originally a champion of the SMID extensions before running into the hybrid hurdle with Alder Lake. Getting past that hurdle is AVX10, which Intel first detailed a few years back. With AVX10.2, 512-bit instructions will run on the P-cores, while either core type can handle converged 256-bit instructions.

As such, the E-cores would have their processing width capped at 256-bit, while the P-cores would be open to the full 512-bit wide pipelines. Any thread could swiftly move between either core type with AVX10 implemented. Previously, if the scheduler shifted a 512-bit task running on a P-core to an E-core, the application would crash instantly because those E-cores couldn't process the instruction.

However, the new patches suggest that Intel has now mandated native 512-bit execution across both P-cores and E-cores, no longer requiring the latter to step down and process the data a bit slower. This is a major development over the standard we originally expected Intel to adopt; the E-cores are apparently becoming just as performant as the P-cores when it comes to SIMD instructions with Nova Lake and later.

Intel's original announcement showed that it had already uncoupled the software improvements of AVX-512 from the physical width of the register, so the new instruction features could remain present for both 512-bit and 256-bit execution. This includes things like masking, embedded broadcast for rounding math operations, and doubling the number of the registers themselves from 16 to 32.

It remains unclear if we will ever see this version of AVX10 on client CPUs, as it seems Nova Lake is going purely for 512-bit execution across both core types. AMD's current-gen Zen 5 processors also have full 512-bit wide registers, while the previous Zen 4 architecture divided a single 512-bit task across two 256-bit execution units over two clock cycles. This ensured execution remained disruption-free even if it took longer.

The last time we saw native AVX-512 support on an Intel client family was Rocket Lake (11th Gen), right before the hybrid era ushered in by Alder Lake. For modern AI workloads and other compute-heavy tasks such as encoding or simulations, AVX-512 instructions bring a huge performance benefit that's foolish to be left on the table. Keep in mind that this is just a Linux patch at the moment and that Intel hasn't officially announced native AVX-512 support for Nova Lake yet.