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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Nvidia's DGX Spark and its GB10 SoC have set the template for what a purpose-built local AI developer sandbox should be. The combination of a standardized hardware platform with robust first-party software support and thorough documentation lets those curious about local AI get up and running faster than buying a bare-metal box and building everything up from scratch, especially in the rapidly evolving AI space.

AMD's Ryzen AI Max+ 395, aka Strix Halo, SoC, is the best x86 spoiler for GB10 so far. It has the same 128GB of unified memory, a powerful 16C/32T Zen 5 CPU, and a Radeon 8060S integrated GPU with 2560 RDNA 3.5 stream processors. It also has an AMD XDNA 2 NPU for those who want to experiment with that accelerator in addition to the general-purpose Radeon GPU. And it can run Windows and Windows apps natively, whereas GB10 boxes are Linux-only for now.

AMD's partners have been building around this hardware for about a year and a half, and it's a well-known quantity at this point. But once you have that hardware in hand, setting it up for AI workloads involves digging through scattered GitHub pages, Reddit threads, and AMD official documentation to get all the software pieces lined up right for the best performance and compatibility.

AMD is trying to change all that today with the launch of the Ryzen AI Halo, a first-party, turn-key Strix Halo mini-PC that puts local AI first. This system can be had with Windows or Linux, and at least in the Linux form we're testing today, it comes preloaded with the full AMD ROCm software stack and an assortment of applications you need to immediately start generating tokens with your preferred model.

And on the support side, AMD has taken a page directly out of Nvidia’s book and cooked up an entire set of its own playbooks that cover various local AI applications and usage scenarios with the AI Halo (and Strix Halo systems more generally) to serve as a springboard for local AI explorers.

The grand tour

The AI Halo comes wrapped in a plastic shell with a subtly color-shifting finish. It's got a large light bar ringing its front and sides that indicates system status. White means it's awake, while a pulsing blue indicates that it's asleep, assuming you allow it to suspend at all. Red indicates a fault. If you find the LED strip distracting, you can just turn it off using the preinstalled AI Developer Center app.

The AI Halo has air intakes on its top and sides, and AMD cautions that you shouldn't block any of these intakes. If you're running by the book, that means this system is less flexible than it could be for space-constrained or multi-node home lab setups, where turning the unit on its side would allow for valuable space savings.

Enterprising community members will likely design and share 3D-printed spacers and risers to get around these limitations, but for a device that is presumably meant to be used in home labs and production environments, the lack of flexibility in orientation is a small but annoying oversight.

Around back, the AI Halo has the same trio of USB Type-C ports you'll find on Nvidia GB10 boxes, plus one more for power input with the included 240W brick. The port closest to the power plug runs at “USB 3.2” speeds, while ports 3 and 4 are higher-speed USB 4. These ports are all DisplayPort Alt Mode compatible, or you can use the HDMI 2.1 port for display output if you prefer.

For wired networking, the AI Halo offers a 10 Gigabit Ethernet port. That’s certainly fast, and AMD has written a clustering playbook for multiple AI Halos using that interface, but it’s in a whole other league compared to the 200Gbps ConnectX-7 NIC on the DGX Spark and its ilk.

We didn't want to strip our AI Halo all the way down to its guts, but each of the four rubber feet on the bottom of the system is secured with a pair of tiny magnets, and they conceal the four screws you presumably need to remove to get further inside.

Here’s a quick look at this system’s specs:

Amid the ongoing RAMpocalypse and NANDpocalyse, no Ryzen AI Max+ 395 system with 128GB of RAM and a large SSD is cheap, assuming you can find a 128GB config in stock anywhere.

Even against that backdrop, the $3999 price tag for the AI Halo that we’re testing today is a pricey proposition. That sticker puts it at the low end of Nvidia GB10 systems like the Asus Ascent GX10 (albeit in its 1TB config).

Our past testing of Strix Halo versus GB10 for local AI workloads has decisively put Nvidia’s platform on top, so this is a potentially awkward place for the AI Halo to land. Let’s dig in and find out if anything has changed.

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I was hoping to expand both the set of inference engines and AI models tested for this review, but I quickly ran into issues. The Ryzen AI Halo ships with a version of vLLM pre-installed, but it wasn't compatible with Qwen 3.6-35B-A3B when I tried to launch it, so I fell back to the old reliable llama.cpp.

We tested three models using llama.cpp: Qwen 3.6-35B-A3B, a relatively lightweight mixture-of-experts model that's been extremely popular of late, Google's Gemma 4 12B, another recent and relatively lightweight but dense model that activates all of its parameters per token, and gpt-oss-120B, a larger mixture-of-experts model that's been available for quite some time now. We used Unsloth's GGUF versions of these models in their Q4_K_M quantizations.

This time around, we're using llama-benchy as our benchmark harness. llama-benchy lets us get llama-bench-like performance results out of any model runner that can present us with an OpenAI-compatible endpoint, not just llama.cpp. That’s quite handy for comparing performance across inference engines.

First up, we'll look at latency and throughput performance with Qwen 3.6-35B-A3B:

And with the dense Gemma 4 12B:

And finally, with gpt-oss-120B:

At least with llama.cpp, the AI Halo's relative performance in single-user LLM serving versus GB10 isn't any different than what we saw several months ago when we took the Corsair AI Workstation 300 through its paces. While its tokens-per-second throughput is fine, albeit still slower than the Dell Pro Max GB10, its time-to-first-token latency falls far behind GB10 as context length grows.

In a real-world scenario where llama.cpp can use (and is configured to use) its prompt caching features, these differences might not be as pronounced, but it's still important to note this worst-case behavior, especially for long-running coding workflows where context lengths can quickly grow.

Overall, the Ryzen AI Halo doesn't work any magic for Strix Halo inference performance compared to other implementations of this platform we've tested. While its tokens-per-second throughput is acceptable, its time-to-first-token latency can quickly rise to non-interactive levels with long contexts.

At the extremes of our testing, waiting two to four minutes for a model to start responding might be disruptive to an interactive workload like a coding assistant, even if the rate at which tokens flow is tolerable once they do start rolling.

I also ran the same check-in on ComfyUI image generation performance using the same basic Flux.2 Klein test we ran back in February, as well, and the same gulf that we saw in time-to-completion for ComfyUI work remains now. The GB10 GPU's larger shader complement chews through image generation far quicker than the Radeon 8086S.

Finally, we checked in on CPU performance with Geekbench 6. The AI Halo’s 16-core, 32-thread Zen 5 CPU holds an edge on the GB10’s 20-core Arm CPU complex in both single-threaded and multi-threaded performance, so tasks like code compilation could potentially be faster on the AI Halo. But that victory shouldn’t cause us to lose sight of the GB10’s all-around better AI performance.

Thermal performance and noise levels

We didn't want to tear down our Ryzen AI Halo to reveal its cooling system, but as we discussed at the beginning of this review, the system has vents on its front, top, and sides to allow for plenty of airflow, and you can see a decently sized copper heatsink through its rear vents.

Logging system temperatures on Linux is more difficult than it is on Windows, but we didn't see CPU or GPU temperatures higher than the mid-50 °C range when running the AI Halo through our typical workloads. All that suggests that this box is more than up to the task of cooling the chip inside.

As for noise, the Ryzen AI Halo runs its twin blower fans audibly even at idle, so it's always adding some amount of noise to a room. And under a ComfyUI generative workload, it gets significantly louder than the Dell Pro Max GB10 box we're using to represent that platform.

The noise signature of those fans is also a bit less refined than those in the GB10 boxes I’ve used. They have a notable high-pitched whine that's difficult to acclimate to when the system is placed on a desktop, whereas the GB10 systems I've used all just sound like moving air and are easy to ignore.

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Given its performance deficit versus Nvidia's GB10 platform, the next question for the AI Halo is whether AMD's included software and library of documentation adds substantial value versus other Strix Halo boxes that ship with nothing more than an OS.

I started my exploration of AMD's preinstalled software and playbooks with Lemonade, a heavily AMD-backed and AMD-optimized sort of software Swiss army knife for AI inference that makes it easy to play with a range of models, inference engines, and modalities, all in one unified interface.

While I didn't dig too deep into its capabilities, I was able to quickly combine Qwen 3.6-35B-A3B with the llama.cpp backed and start chatting with it, all with performance similar to what we saw in our directed testing with llama.cpp. This is the kind of smooth, straightforward experience that you want from a product like this. But Lemonade is available for a wide range of AMD systems, not just AI Halo, so you don’t have to buy one of these boxes if you want to try it out.

Other included apps have a few more wrinkles. When you first boot the Linux AI Halo we tested, the system launches a centralized management interface called the Ryzen AI Developer Center (AIDC for short) that aims to put key system information, settings, and software updates in one easy-to-access spot.

The AIDC app exposes some handy settings that Strix Halo users will want at their fingertips. Most notably, it lets you adjust how much of the AI Halo's 128GB memory pool is split between the CPU and GPU graphically instead of through the command line.

While we didn't have time to test their impact on performance, you can also select from three power profiles to balance noise, power consumption, and performance. And if the built-in LED light bar on this box is annoying you for any reason, you can turn it off through this interface.

Outside of those functions, the AI Developer Center has some good ideas that don't feel fully baked. For example, model management is one of the most common tasks when I'm setting up or mucking around on a local AI box. The AIDC app will show you what models you have downloaded across the system for use with AMD's pre-installed apps. But you can't open or otherwise reveal their containing folders so that you can add to or manage the data within them directly.

That's a pain, because if you do want to extend the usefulness of preinstalled apps like ComfyUI by adding new models in support of different workflows, that task is harder than it should be. As far as I can tell, the preinstalled ComfyUI lives in a Podman container (presumably for ease of updating), so its traditional directory structure (which would normally end up under /home//) is obscured.

ComfyUI can be configured to look for additional model directories beyond its defaults using a separate .yaml file. But with AMD’s configuration, those directories live in /var/cache/, which on the AI Halo’s Debian image is owned by root, not the user, so you can't just drop new models into those alternate directories at will without some chmod work that I didn't want to mess with for fear of breaking something.

And this directory location isn't documented in the related ComfyUI playbook that AMD provides (but is discussed in the overall user guide for the system).

AMD says the preinstalled software and models on the AI Halo are only meant to support its playbooks, and that users are free to go about installing and configuring the same apps to their own taste. But to me, the next logical step for learning after running through those playbooks is extending the functionality of those workflows, and if the process for doing so is neither straightforward nor transferable to the natively installed version of the application, then is the knowledge being conferred even useful?

For another example of some minor documentation hassles, the preinstalled version of vLLM on this system has a launch script that provides a lightweight wrapper that presents status information and checks the health of the vLLM instance. AMD encourages running different models with vLLM by changing the model string in this script, but the path to it is again not documented anywhere in the accompanying playbook. So I had to go digging. I eventually found it in /usr/bin/ by dumb luck, but this is the kind of very basic information that documentation exists to chronicle.

AMD also provides a direct competitor to the useful Nvidia Sync remote access app called AMD Sync. Sync allows you to connect to the AI Halo using SSH, and you can get versions of it for Windows and Linux alike (but not for macOS, so far, an option that Nvidia supports.)

The basic idea of AMD Sync is that you can run workloads that need the resources of the AI Halo on that system while working remotely on your preferred device. For just a couple examples, you can get a terminal session, run a remote instance of VS Code, or work in JupyterLab, all powered by the AI Halo. Check out AMD’s playbook for more examples of what Sync can do.

Overall, the pre-installed software on the AI Halo will get you started if you have no prior local AI experience and are working from AMD's playbooks to learn the basics, but I feel like the configuration decisions that AMD made to include those apps could be more flexible and better documented.

From the playbooks I tried, I also think AMD could stand to have a few more rounds of QA to ensure that these docs fully cover everything beginners need to know in order to get the most out of the platform.

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AMD's Ryzen AI Halo is the company's attempt to put forth a complete, turn-key, first-party hardware and software package for AI developers, backed by direct software support and an extensive library of documentation for running local AI tasks on the Strix Halo platform. This effort unsurprisingly resembles the hardware, software, and documentation ecosystem that Nvidia has built around the DGX Spark.

Despite those lofty goals, the included software configuration on the AI Halo doesn't necessarily put the best foot forward for this platform yet. On the upside, the included Lemonade local AI sandbox, which is the focus of a lot of AMD optimization for local AI workflows, is easy enough to get started with, has a polished user interface, and performs well. Of all the beginner-friendly experiences on this box, Lemonade is perhaps the most polished. And the AMD Sync application gives you handy remote access to this system’s processing power from anywhere you can tunnel into it.

We also appreciate the handy AI Developer Center hub for its one-stop system management options, but we wish it allowed us to dig into tasks like managing local models. AMD's configuration choices for preinstalled apps like ComfyUI also made it harder for us to work with them as shipped versus simply downloading and installing them ourselves.

So even if you are truly starting from zero local AI knowledge and need a completely on-rails experience, you're likely to find yourself chafing at AMD's configuration choices sooner or later. And while the provided playbooks are broadly useful, they're sometimes missing key information, like folder paths, that makes deeper exploration of the concepts within difficult.

In any event, you don't need an AI Halo to access AMD's playbooks, so if you're curious about the quality of this documentation, you can review it independently before you buy - or use it with any other compatible Strix Halo box.

All this is important because the AI Halo is a significant investment. At a list price of $3999, the AI Halo is about 16% cheaper than the DGX Spark as of this writing. AMD touts this lower price as a cost-per-token advantage, and that might be appealing for the well-heeled hobbyist or enthusiast who just wants to play in a local AI sandbox.

But if you're a developer for whom time and tokens are money, you can get into an Asus Ascent GX10 GB10 system with a 1TB SSD and 128GB of RAM for the same $3999 as the AI Halo. And even the $4700-ish price tag of a DGX Spark with its 4TB SSD will pay for itself in fairly short order simply because it keeps you waiting less.

Especially if you're trying to learn the ropes of local AI work, the quality of Nvidia's accompanying documentation and the breadth of its application support is still better than what AMD has shown so far for the AI Halo, so you’re more likely to have a smooth ride.

All told, our verdict for the AI Halo is mixed. This is certainly the most turn-key Strix Halo box available for local AI work, and if you’re all-in on the AMD AI ecosystem, want a direct line from AMD for software support and documentation, highly value the ability to boot both Windows and Linux, potentially need to play with AMD's XDNA 2 NPU, and don't mind lower performance than a DGX Spark in exchange for all of those options, then maybe the AI Halo is for you.

But there's no two ways about it: this box is still generally slower and less agile as an AI development platform than a GB10 system, and until AMD is ready to ship a next-gen SoC in the architectural shape of Strix Halo with RDNA 4 graphics or some other future GPU IP, that value proposition looks like it’s going to be very difficult to shift.

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Update 7/6/2026 4:10pm PT: An Nvidia representative responded with a short statement to Tom's Hardware: "Our roadmap is intact." Nvidia provided no further details in response to our follow-up questions. As such, it is unclear if Nvidia's statement refers to its original roadmap, planned delivery schedules, and hardware, or if those particulars had already been changed and the statement refers to a newly updated roadmap.

Original Story:

Nvidia reportedly won't ship its Kyber NVL144 rack until 2028, a delay of more than 12 months that pushes the cabinet meant for 2027's Rubin Ultra GPUs into the following year, according to a SemiAnalysis thread on X. The holdup is ostensibly being caused by manufacturing challenges with a PCB midplane that connects eight Oberon racks between the NVSwitches, which Nvidia calls the orthogonal backplane. Nvidia is also understood to have killed NVL72x2, a stopgap rack designed to tide customers over, and that no proven alternative is now available to widen Rubin Ultra's scale-up in 2027.

The orthogonal backplane sits between Kyber's vertically mounted compute trays and the switch trays behind them, replacing the cable harnesses of earlier racks with a rigid board that carries the all-copper NVLink fabric. Kyber runs liquid cooling by default and stacks 144 Rubin Ultra packages, double the 72 packages in a current Oberon NVL72 rack. Every GPU-to-GPU link inside the cabinet runs through that board, and copper traces lose signal integrity as layer counts increase, alongside power delivery and thermal design challenges. Jensen Huang held up the gray backplane on stage at GTC back in March.

Trade analyses of the board describe three 26-layer sections laminated into one 78-layer stack close to a square meter in area, with trace spacing at or below 25μm and impedance held within a tolerance of 5% to keep 448 Gb/s-class signaling intact. A cabled version of the same interconnect would need upward of 20,000 discrete cables, which is why Nvidia is moving the wiring onto a single passive board.

NVL72x2 would have bolted two Oberon racks back-to-back to reach Kyber-class density over copper NVLink, per SemiAnalysis, which said Nvidia abandoned the stopgap after its largest customers balked at running two linked cabinets as a single unit. NVL576, a separate configuration tying eight racks together through co-packaged optics, is likely to slip too or ship in low volume until that optical technology matures.

These cancellations leave Nvidia with "no proven solution to expand the scale-up world size for Rubin Ultra," meaning the largest single Rubin Ultra domain in 2027 could match, but not exceed, what Oberon already delivers.

Nvidia dropped the quad-chiplet Rubin Ultra GPU for a dual-chiplet part last week over manufacturing execution concerns, halving the accelerator's per-package compute. SemiAnalysis has also placed a fully production-ready co-packaged optics NVSwitch no earlier than the Feynman generation that follows Rubin, which leaves copper as the only near-term solution for linking Rubin Ultra at rack scale and thereby puts even more weight on the PCB midplane.

The delay only applies only to the Rubin Ultra phase and its Kyber rack. Nvidia's 2026 Rubin GPUs, which reuse the current Oberon rack, aren't part of the reported delay. We've reached out to Nvidia for comment.

A Chinese reviewer on Bilibili by the name of 杰某 (Jie Mou) got his hands on a special RTX 4080 graphics card that uses a mobile core instead of a desktop one. These GPUs emerged after the Trump admin banned the sale of RTX 4090s in the region, which forced local sellers to resort to strange alternatives, one of which is the supposed "RTX 4080M." It's a custom, modded GPU that doesn't come with a warranty or official drivers, and the benchmarks show it doesn't offer world-beating value either.

The reviewer paid 2,000 RMB (~$300) for the tested card but remarks that it now costs close to 2,700-2,800 RMB (~$400) due to the ongoing component crisis caused by the AI rush. At that price, it's almost as expensive as AMD's RX 9070 GRE or Nvidia's RTX 5060 Ti in China, both of which will be brand new, warrantied cards. However, a similarly-modded RTX 4090M in China would cost an absurd 10,000 RMB (~$1,470).

Before we go over the benchmarks, the test bench used here was comprised of an Intel Core Ultra 270K Plus mounted on a Maxsun Z890-A motherboard alongside 32GB of DDR5-8200 RAM. In 3DMark TimeSpy, the 4080M scored 18,600 points, which is a respectable result in and of itself, but underwhelming when you take its price into account. Someone in the comments showed the same card netting 19,500 points as well.

During the benchmark, the card only pulled around 100W, which is significantly lower than even the mobile RTX 4080's TGP. The mobile core can be pushed up to 175W as per Nvidia's own spec and you'd expect that in a discrete GPU form factor, but it's likely that the custom BIOS or the drivers are holding it back. Speaking of which, the drivers can be easily configured with one-click installers developed by the community.

Moving toward gaming, the reviewer compared the 4080M against the aforementioned RX 9070 GRE because of their similar price brackets in China, and both come packing 12GB of VRAM. PUBG was the only game where the 4080M was clearly superior, achieving a 100 FPS lead over the AMD option at 1440p resolution with Ultra settings. In Delta Force at 1440p Ultra, both cards performed the same, but the 4080M did manage to net 10 more FPS at 4K.

The reviewer then tested AAA titles where the RX 9070 GRE basically smoked the 4080M as the resolution scaled upward. We'll add a table below so you can see the exact numbers, but the closest the 4080M came to dethroning the Red Team was in Shadow of the Tomb Raider. Running at 1440p with Low settings, the 4080M pushed 286 FPS on average, while the RX 9070 GRE still won with 274 FPS.

At the end, the verdict ultimately turns out to be boring: the RTX 4080M is not a sensible purchase at the current Chinese market prices because similarly-priced new GPUs outpace it with ease. However, since it only drew 100W in games, there's an argument to be made for SFF builds. There's limited thermal headroom in an ITX system and that's where the RTX 4080M could thrive.

Nvidia's rich driver suite and superior upscaling tech also add value to the proposition. At roughly $400 converted, perhaps the 4080M can power a DIY Steam Machine that truly undercuts Valve's pricing while delivering much better performance. After all, it's made from salvaged laptop GPUs and qualification samples that are cheaper to acquire, so a MacGyver-ed, console-busting rig is where it can meet its natural match.

F1 25 launched in May 2025, and in the year since release, the developers have delivered numerous patches addressing gameplay, visual quality, and performance and stability issues. EA has now rolled out the game’s largest update yet: the 2026 Season Pack DLC. This paid expansion brings the sweeping 2026 Formula 1 regulation changes into the game, fundamentally reshaping both the cars and the racing experience. With a year of updates behind it and a major overhaul now in place, this is the perfect opportunity to revisit F1 25 and see where performance stands in 2026 with a selection of both Nvidia and AMD GPUs.

The 2026 Season Pack DLC

The 2026 Season Pack DLC

So what exactly is included in the 2026 Season Pack DLC?

The DLC features two new teams – Audi, which took over for Sauber, and Cadillac, which is the first major American car manufacturer in F1. The DLC also brings the latest driver line-ups. Racing Bulls will now have Arvid Lindblad and Liam Lawson. Isack Hadjar will race alongside Max Verstappen at Oracle Red Bull Racing. Valtteri Bottas and Sergio Perez team up for Cadillac.

The paid expansion also includes a new circuit: MADRING. This 5.4 km hybrid street and purpose-built track has a mix of high-speed sections and more technical corners. It was specifically designed for the new season, so it can only be driven using 2026 cars.

The cars are lighter and more agile, reflecting their real-life counterparts in 2026. The idea is for the cars to be more nimble and harder to drive at the limit, which will put greater emphasis on driver skill. The cars also have less downforce and less drag, which should make it easier to follow more closely.

Active Aero is also available in the game with the paid DLC. The front and rear wings move in real-time, between straight line and corner mode, to give drivers more speed down the straights and to allow the car to be more responsive in the corners.

The new Overtake Mode provides a boost of nearly 500 horsepower when deployed. This mode replaces the old Drag Reduction System (DRS) Overtake Mode can be deployed when a driver is within one second of the car ahead. It can be used either all at once or spread across a lap.

Boost Mode is an energy deployment tool available through the use of the Energy Recovery System (ERS). This remains in place as it has for many years. The new regulations place a very high dependency on efficient battery management. Just as in real life, some people will enjoy this added strategic depth, while others will hate it.

So, how well are all of these new features implemented?

The cars genuinely feel different to drive – in a good way. The new handling characteristics require a different approach to attacking corners. The battery management might lead to more overtakes, but this is the most controversial aspect of the new regulations. The developers have done a good job of simulating how the battery management works in real-life.

There are two ways to jump into the 2026 F1 season. Existing F1 25 owners can purchase the F1 2026 Season Pack DLC, while new players can pick up F1 25: 2026 Season Edition, which includes the full F1 25 base game alongside all 2026 season content.

With that being said, our main focus today will be on visuals and performance.

Path Tracing vs Ray Tracing vs Rasterization Visuals

Path Tracing vs Ray Tracing vs Rasterization Visuals

F1 25 supported path tracing at launch in May 2025. Over the course of the past year, the game has received some patches to fix some minor issues with the path tracing implementation.

You can see from the images above just how significant the impact of path tracing is, even compared to standard ray tracing. It delivers noticeably more realistic lighting, shadows, and reflections, pushing the presentation closer to photorealism in certain scenes. Night races benefit the most from the upgrade, though under specific weather conditions, daytime races also see meaningful improvements.

We benchmarked the game on 7 different graphics cards. We tested rasterization performance, ray tracing performance, and path tracing performance. We did not use any upscaling. We used TAA. We performed the benchmarks at Monaco, which is one of the more demanding tracks in the game.

Test system

• Ryzen 7 9800X3D
• 64GB (2x32GB) G.SKILL Flare X5 DDR5 @6200 MHz CL30
• Crucial T700 Gen5 SSD
• ASUS ROG STRIX B850-F Gaming WiFi
• Corsair Nautilus 360 RS AIO Cooler
• MSI MPG Ai1600TS PCIE5 PSU
• HAGS enabled
• Windows 11 25H2 (Build 26200.8524)
• NVIDIA driver 610.47

Rasterization Performance

Rasterization Performance

Performance with ray tracing and path tracing disabled is excellent across nearly the entire GPU stack, with the RX 6500 XT being the lone major exception. It's limited 4GB frame buffer, which struggles heavily at max settings, while the RTX 5060 also begins to run into VRAM limitations at 4K with its 8GB allocation. Outside of those cases, however, the game delivers very high frame rates with fully maxed-out rasterized settings on most GPUs tested here.

We did want to see if the game would be playable on the 6500 XT at 1080p with lower settings. We tested the GPU using the Medium and Low presets.

The game is very playable with both presets. Image quality takes a hit, but the game still looks solid at these settings. Keep in mind that this is one of the more demanding circuits. The fact that the GPU can average over 70 FPS with low settings and nearly 60 FPS with medium settings means that it should achieve considerably better performance at other tracks.

Ray Tracing Performance

Ray Tracing Performance

Even with ray tracing enabled, most of the GPUs tested are capable of delivering around 60 FPS or better at 1080p. However, as resolution increases – particularly at native 4K – the RTX 5090 becomes the only GPU where enabling RT consistently makes practical sense without major compromises. Alternatively, players can still target a 4K output by using DLSS or FSR in Performance mode, allowing six of the tested GPUs to deliver playable frame rates with ray tracing enabled.

Path Tracing Performance

Path Tracing Performance

As expected, path tracing is reserved for the very high end of the GPU market. While the feature is genuinely transformative in this game, we would only recommend enabling it on GPUs in the RTX 5090, RTX 5080, or RTX 4090 class. Even with that level of hardware, DLSS Performance mode is still required to maintain consistently playable framerates across all circuits, though some tracks are light enough to allow the use of DLSS Quality mode.

The game runs smooth without any stuttering across all settings and resolutions we tested. Even when the average framerate is low on certain configurations, the frametime graph remains flat.

The Verdict

The Verdict

Codemasters has consistently delivered highly scalable F1 titles over the years, and F1 25: 2026 Season Edition continues that trend. With the right settings for your hardware, most players should have little trouble achieving 60 FPS or higher. Whether you are running an RTX 5090 and looking to push max settings with path tracing enabled, or using a lower-end GPU with limited VRAM, the game remains accessible across a wide range of GPUs.

It's always interesting to revisit an engineering sample for an older GPU as it allows us to analyze it with the benefit of hindsight. We've come across a card that appears to be an early prototype for AMD's RX 7900 XTX, which was purchased by Tiktoker Shav Tech on the secondhand market. The buyer thought they were ordering a regular 7900 XTX, but they got something else that's recognized as such in software but clearly differs at the hardware level.

Engineering Sample/Prototype RX 7900 XTX from r/pcmasterrace

As you can see above, this card is very red and we've seen AMD's engineering samples come with red-colored PCBs before, which further confirms what we're looking at. The poster said the GPU did not come with a backplate, as you can see from the second image. The third picture gives us a closer look at two extra connectors sticking out from the middle of the PCB that are not found on retail cards.

The blue connector is composed of I2C, PMBus, and JTAG headers across both rows. JTAG allows engineers to collect diagnostic data directly from the core or memory controller, bypassing all internal circuitry. On the other hand, I2C / PMBus are responsible for monitoring power draw and temps; the testers connect directly to the VRMs and telemetry sensors onboard via specialized USB adapters.

What's the most impressive launch of 2026 so far?

The shrouded black connector underneath is a logic analyzer meant for checking signal quality. Basically, engineers hook up an oscilloscope or logic analyzer ribbon cables here to capture clean, high-speed signal waves across the PCB trace lines. It helps test the die-to-die communication (since RDNA 3 GPUs employ an MCM design) before chips are sent for final production.

There are little dip switches at the bottom of the PCB as well that could be used to switch between PCIe generations to test the GPU on older motherboards. It's more likely that these serve as different boot configurations for recovery VBIOSes. Speaking of which, the buyer also confirmed that this unit comes with a custom VBIOS that is identified as "Navi 31" and the card refused to flash an RX 7900 GRE VBIOS entirely.

The reason the original poster even attempted that was because they thought this was a "spoofed RX 7900 GRE," as in, someone took the PCB from an RX 7900 GRE and just made it look like an RX 7900 XTX in software. GPU-Z screenshots somewhat corroborate this since the card is officially recognized as a 7900 XTX, but the specs don't line up at all. Instead of 24GB of GDRR6X VRAM, this GPU came with 16GB of GDDR6 memory.

That's exactly the same as an RX 7900 GRE. Moreover, the ROP and TMU count also match the RX 7900 GRE — 160 instead of 192 and 320 instead of 384, respectively. The bus width is marked as 256-bit, which is what the GRE has, while the 7900 XTX comes with a 384-bit wide bus. Other parameters such as the release date, die size, clock speeds indicate it's an RX 7900 XTX, so there's definitely some conflict here.

Realistically, we might be looking at a 7900 XTX prototype that ended up serving as proof-of-concept for a cut-down version of the Navi 31 silicon. This PCB even features 12 memory modules that would otherwise stack up to 24GB, but here it's limited to only 16GB. Not every Navi 31 die is binned perfectly, and some of the leftovers eventually became the RX 7900 GRE in China first, followed by a global release in 2023.

There's bittersweet news from the shore of the open-source Zluda project, a long-running effort to create a CUDA emulator for AMD GPUs. The project's latest blog post for version 6 shows off the fresh 32-bit PhysX support and improved Windows support. Additionally, there are a number of PyTorch-driven fixes. Unfortunately, the project has again lost commercial funding, and it's now back to being a hobby for developer Andrez Janik.

Zluda 6's 32-bit PhysX support is still in a pre-alpha stage, but the results are promising. Janik showed off multiple cloth and deformation demos running at speed, and even a screenshot showing a 3x performance uplift of 2010's Mafia II running with PhysX effects turned on. Given the pre-alpha nature, Janik notes that "fluid simulations can be glitchy, and the current method of loading ZLUDA into Steam games is poor." One of his goals is to have better support for Windows, and v6 includes a refreshed zluda.exe loader that now loads required performance libraries automatically.

Last but by no means least, Zluda v6 includes a host of PyTorch-driven enhancements, composed of compiler fixes and improvements to performance libraries. As a silver lining of sorts, Janik notes that since there's now no funding, the priorities for the project have shifted to things "[he] finds the most entertaining," justifying the addition of PhysX and the revamped Windows loader.

The project was initially started in 2020 to get CUDA running on Intel hardware, but has since then turned to AMD cards. After being abandoned in 2021, it was brought back from the dead around 2022 thanks to AMD pulling out the checkbook to make it happen — presumably because one of the main obstacles (if not the primary one) is that most all the AI software ecosystem revolves around Nvidia's GPUs.

Unfortunately, AMD also cut the funding to Zluda in 2024, and in August even forced Janik to rebuild the code the company paid for. He thankfully found an undisclosed sponsor in late 2024; likely an AI company to whom the translation layer would be valuable, letting them run CUDA AI workloads on Instinct cards. Said funding is now sadly gone once again, and Janik says Zluda is back to being a "weekend project."

For end users, it's nice to have a fully open-source drop-in replacement for CUDA binaries. As for large-scale conversion for AI usage, though, there are a number of alternative projects that look to accomplish the same end results via different means. These include AMD's HIP source code porting, Spectral Compute's Scale, and MooreThreads' Musify toolkit, to name a few.

Back at CES 2026, Nvidia CEO Jensen Huang said that "it's a good idea" to consider reintroducing older GeForce RTX graphics cards with GPUs from trailing-edge nodes to alleviate pricing and availability concerns around cutting-edge RTX 50-series products. It appears that the idea may now have become reality. After a hiatus that began late last year, RTX 3060 12GB cards (first launched in early 2021) are beginning to reappear as new stock at e-tailers.

We've spotted a Gigabyte RTX 3060 12GB card available direct from new stock at Newegg for $339.99, or just $10 above its MSRP from over five years ago. This Windforce card is a straightforward dual-fan model with no frills, but tellingly, it carries a rare Rev2.0 suffix, directly indicating a revision or new model of some kind. That revision number aside, it's identical (as far as we can tell) to the Rev1.0 card that presumably appeared nearer to the RTX 3060 12GB's launch.

It appears that different board partners are working to quietly bring back the RTX 3060 12GB worldwide, as ComputerBase notes the availability of an Asus Dual card in the European market. We wouldn't be surprised if that product makes its way Stateside, as well.

Gamers may have hoped that the reintroduction of an older product from a foundry and a process node that isn't capacity-constrained (namely Samsung 8nm), as well as an older memory technology, would have resulted in some pricing relief, but that doesn't appear to be the case.

The RTX 3060 12GB is reappearing for just a few bucks less than the far superior RTX 5060, which offers both stronger baseline performance and unfettered performance with the latest DLSS 4.5 upscaling tech. Heck, even the entry-level RTX 5050 outpaces the RTX 3060 in our most recent tests.

The 3060's extra 4GB of VRAM compared to those products only comes into play with settings and resolutions where its shader horsepower is already inadequate to produce playable frame rates, so it's more of a psychological advantage than a practical one.

So why this product and why now? As AI wafer demand on cutting-edge nodes only grows, it's possible that simple economics dictate that the opportunity cost of producing entry-level Blackwell GPUs for the desktop is simply too great compared to the revenue and margin opportunities of making data center Rubin GPUs for the countless Vera Rubin NVL72 racks that the company is doubtless planning to ship later this year.

In the event that Nvidia does prioritize datacenter products over consumer ones, the already elevated prices of entry-level RTX 50-series cards might give way to a situation where one simply can't buy these lower-priced, lower-margin products at any cost. And in that event, the aging RTX 3060 could be one of the few sub-$350 options available to gamers who need to build a new system or upgrade from an aging graphics card.

And frankly, that's a poor outcome for gamers, as the RTX 3060 can't run the latest DLSS 4.5 upscaling model at its full potential due to the lack of proper FP8 acceleration on older Turing and Ampere GPUs. And it can't run DLSS Frame Generation at all, leaving gamers to deal with cross-platform solutions like FSR and XeSS frame generation from other vendors. Those technologies are incredibly useful tools in getting the best experience out of modern games, and if they're only available on a smaller subset of more expensive GPUs, that further stratifies the already stratified modern PC gaming experience.

We've reached out to Gigabyte and Nvidia for comment on the reappearance of the RTX 3060 and will report what we learn if we hear back.

Chinese companies are paying as much as 600,000 Chinese Yuan ($82,000) for servers built around Nvidia's five-year-old A100 accelerator and modifying gaming GPUs to run AI workloads, as a U.S. smuggling crackdown and a Chinese customs freeze on legally approved chips choke off every other supply route at once, according to the Financial Times. The price of an A100 server has roughly tripled since late last year, while Nvidia's flagship DGX B300 system has doubled to more than 8 million ($1.1 million) on the black market over the past six months.

Servers built on the A100, a data-center GPU Nvidia launched in 2020, have climbed from about 200,000 Chinese Yuan ($22,300) to as much as 600,000 ($67,000) since late last year, the FT reported, citing chip traders. Demand has also pulled in gaming processors that can be modified to run inference.

Nvidia's restricted Blackwell hardware sits at the top of the same market: the RTX 6000 Pro workstation card has risen from roughly 50,000 Chinese Yuan ($5,580) at the start of the year to as much as 130,000 ($14,500), and the DGX B300, which retails in the U.S. for nearly $400,000, now trades above $1.1 million. Renting is no cheaper, with an FT survey finding that GPU rates inside China now match or exceed U.S. prices, reversing the discount that the abundant smuggled supply once provided.

Washington tightened enforcement at the end of last year, and in March, a Supermicro co-founder was charged over an alleged $2.5 billion scheme to route Nvidia AI servers to Chinese buyers. Authorities in Taiwan and Malaysia subsequently opened their own smuggling investigations, drying up the re-export routes traders had relied on. Building data centers from smuggled chips is a "dead-end," Nvidia told the outlet, adding that it provides no support or repairs for restricted products.

Beijing itself closed legal channels from the other side. After the Trump administration approved H200 exports to China, Chinese customs were instructed to block the chips at the border, and Commerce Secretary Howard Lutnick later confirmed that Nvidia hadn't sold a single H200 to a Chinese company months later. Both moves push buyers toward the same destination: Huawei, which has positioned its Ascend 950PR, launched in March, as the inference chip of choice for domestic firms.

It’s understood that the 950PR is currently undergoing testing at large data center clients in China, but output is still limited, and its native CANN software stack substantially trails Nvidia’s CUDA, so domestic supply can’t yet absorb the demand the import freeze has redirected.

Rising memory prices are only compounding all this, with one trader saying that moving away from Nvidia hardware had become harder as component costs climbed, a knock-on from the DRAM and HBM shortage now working through every tier of the AI hardware stack. Until Huawei scales the 950PR, which will take some time, or Beijing greenlights H200 imports, which is highly unlikely, prices for the remaining A100 inventory in China will continue to rise.

Nvidia's GeForce RTX 5070 Ti recently earned our pick as the best all-around enthusiast graphics card for gaming in 2026 thanks to its strong baseline performance for both raster and RT gaming at 1440p and 4K.

• Get this RTX 5070 Ti deal at Newegg

The one catch is that the price for that all-round excellence has been quite high of late. We found that you can expect to pay $1099 or so at the midpoint of RTX 5070 Ti prices during our recent research for our guide to the best graphics cards in 2026, as well as our work for the 2026 GPU Benchmarks Hierarchy.

But as Amazon Prime Day rolls around, both Best Buy and Newegg are making Asus' Prime RTX 5070 Ti available for just $900 — the cheapest we've seen one of these cards go for in a long time.

Update: This RTX 5070 Ti is sold out at Best Buy, but you can still get it at Newegg.

We use the OC Edition of this Asus card for our own testing in the Tom's Hardware labs, and its clean design, quiet triple-fan cooler, and full-length metal backplate all make for a fine example of the 5070 Ti. The base Prime 5070 Ti on sale here sacrifices only 45 MHz of stock clocks to the OC Edition—a difference you'll never notice in games.

But you'll definitely feel the extra $50 to $100 in your pocket compared to the next-cheapest 5070 Tis out there, and this Asus Prime card offers an all-around nicer build than most board partners' most attainable product lines.

Beyond its strong baseline performance and 16GB of GDDR7 memory, the RTX 5070 Ti's support for superior DLSS 4.5 upscaling and Multi Frame Generation makes it easy to achieve fluid, responsive gaming across a broad range of resolutions, target frame rates, and quality settings. Especially for cutting-edge path-traced games, you'll want DLSS 4.5 and MFG at your disposal for the best experience.

If you've been waiting for an RTX 5070 Ti upgrade to elevate your gaming PC and missed out on lower prices late last year, this Asus card is the best opportunity that we've seen so far during the Prime Day stretch. Don't wait.

If you're looking for more savings, check out our Best PC Hardware deals for a range of products, or dive deeper into our specialized SSD and Storage Deals, Hard Drive Deals, Gaming Monitor Deals, Graphics Card Deals, gaming chair, or CPU Deals pages.

Last month, AMD officially announced FSR 4.1 for older RDNA 2 and RDNA 3 hardware, with the RX 7000 series set to receive FSR 4.1 support in July. Well, Christmas has come early as FSR 4.1 is out now for RDNA 3 desktop GPUs, a few days before it was originally supposed to launch. It's available natively in over 300 games, and all you need to do is update your GPU drivers inside AMD Adrenaline software to unlock the latest upscaler.

• ASRock Challenger Radeon RX 9070 : was $639 now $599 at Newegg

FSR 4.1 for the RX 7000 series is based on INT8 code that differs from the FP8 instruction set that the RX 9000 series uses. Technically speaking, only RDNA 4 has the hardware required for FSR 4.1 to work optimally, while making it backwards compatible with previous generations requires a lot of tuning and falling back on older instructions that incur a slight performance loss in exchange for better visual quality.

AMD is confident that its in-house optimizations deliver better results than community efforts, as the video embedded above shows official FSR 4.1 achieving higher frame rates in Forza Horizon 6 and Crimson Desert versus FSR 4.0.2c. That version is built from leaked code that came out last year and has since served as the foundation of Optiscaler mods that force-inject FSR 4 by making the game think it's actually DLSS.

The biggest difference will still be seen against native rendering — playing Crimson Desert at 4K, an RX 7900 XTX only managed about 43 FPS on average, while FSR 4.1 bumped that up to 64 FPS. That's nearly a 50% improvement, while looking considerably better than FSR 3.1 and remarkably close to FSR 4.1 on the RX 9000 series. Sure, FSR 3.1 could probably net a few more FPS, but the image quality won't be as sharp.

AMD also confirmed it's working on "lightweight machine learning models" to bring FSR 4.1 to RDNA 3 APUs, which should extend support to a wide range of devices. For instance, the Z1 Extreme chip inside Valve's Steam Deck is based on RDNA 3 architecture. Phoenix Point and Hawk Point silicon, i.e., Ryzen 7040, Ryzen 8000(G), Ryzen 8040, and Ryzen 200 series, also rely on RDNA 3 graphics.

RDNA 3.5 is an extension of RDNA 3, and AMD pushed back against it, not receiving FSR 4.1 just this month. If we assume this announcement also counts RDNA 3.5, then expect FSR 4.1 to also come to Ryzen AI 300 and Ryzen AI 400 series, along with Ryzen AI Max processors. AMD's current-gen Ryzen Z2 family for handhelds is also based on RDNA 3.5. For now, though, FSR 4.1 seems limited strictly to RDNA 3 desktop GPUs.

Support for older RDNA 2-based graphics cards is expected in early 2027, even though the community has interchangeably used INT8 mods for both the RX 6000 and RX 7000 series. Expect a bigger performance tradeoff on RDNA 2 compared to RDNA 3, which is what the company is likely trying to minimize in the months leading up to its launch. Nonetheless, it's exciting to see AMD at least try to catch up to Nvidia in terms of its upscaler support.

One last thing to note is that FSR 4.1.1 INT8 leaked earlier today through Proton Experimental. There was a DLL file signed by AMD, intended to work on RDNA 3.5 silicon — so basically the Steam Machine. A few people got hold of the file before it was removed and got it to work on even RDNA 2 GPUs via Optiscaler. Since the cat was out of the bag, perhaps that's why AMD decided to officially release FSR 4.1 for the RX 7000 series earlier than expected.

The world is getting warmer every year due to worsening climate change. If you live in certain parts of the world affected by El Nino, you're likely seeing your devices overheat right now if you live without an air conditioner. So, what if you could devise a solution to keep your computer cool regardless of ambient temps? That's precisely what YouTuber TrashBench did by altering a standard countertop ice machine to work as a GPU cooler.

We've covered TrashBench's escapades before, such as that time they used car antifreeze to cool a GPU, or when they put the entire test bench inside a freezer, or even the video where they dunked the entire graphics card into transmission fluid. In this case, the idea of using an ice machine actually came from fellow modder MrYeester who already cooled a CPU with a smaller one — now, it was time to take the concept to another level.

The YouTuber began by disassembling an RTX 3060; he removed the stock cooler and mounted a custom retention frame over the die to fit the liquid-cooling tubes. He then put a submersible water pump inside the ice machine and simply filled it up with water to create the loop. The hot water from the GPU falls into the bucket where it should be cooled before being looped back to the card.

Just for the sake of it, the modder tested the GPU without turning the ice machine on and it actually achieved around 44°C in benchmarks. The temperature wouldn't stabilize because nothing is cooling the water, so he turns on the machine, and the temps actually fall by more than 10 degrees. However, the GPU is heating up faster than the water can cool it down because the ice machine is on a fixed clock cycle.

Basically, the compressor only runs for a few seconds at a time before turning back off once the ice has been discharged into the water. This interval is controlled by a thermostat that can't be adjusted, so it was time to rip it out entirely and replace it with another one. TrashBench luckily had another one that will bypass the internal logic and force the compressor to stay on perpetually.

But just running the compressor longer doesn't result in better cooling. The evaporator coils are responsible for facilitating the heat exchange and they weren't submerged enough in the water. To fix this, the YouTuber simply put a small plastic bowl under the coils to the point they were completely drowned. Hot water coming from the GPU will now hit the evaporator, which helps improve the cooling efficiency, while the new thermostat ensures the compressor doesn't turn off.

Once everything was ready, TrashBench ran the numbers once again and the results were a success, to say the least. Before the modding began, the RTX 3060 was reaching around 60°C in Cyberpunk 2077. Now, it was casually chilling at 22-23°C, and it was stable. The GPU hot spot was sitting at 75°C before, while the modified ice machine brought it all the way down to just 34°C.

There were some leaks in the middle that the YouTuber dealt with, and the entire modding process was a bit too involved for a quick and fun experiment. Not to mention, messing with the internal componentry of an electrical device that's carrying water isn't exactly the safest thing to do. Still, the results speak for themselves, and we can only wonder how far you could take this RTX 3060 now with extreme overclocking.

NVK, the community-built open-source Vulkan driver for Nvidia GPUs in Mesa, has gained experimental DLSS support, with the code landing in Mesa 26.2-devel, as reported by Phoronix. The driver doesn’t reimplement the upscaler but instead loads Nvidia's own pre-compiled CUDA binaries and runs them, a workaround that keeps the feature behind an experimental flag and ties it to whether compatible bytecode exists for a given card. Nvidia's proprietary Linux driver has of course handled DLSS for years, so the change closes one of the bigger gaps between the closed driver and its open-source counterpart, rather than bringing the technology to Linux for the first time.

DLSS runs on NVK through VK_NVX_binary_import, a Vulkan extension that lets an application load Nvidia CuBIN files, the pre-baked CUDA binaries Nvidia, and loads them on the GPU. Autumn Ashton opened the original pull request for the extension last year, and Thomas Andersen revived it roughly two months ago to clear merge conflicts and finish the work, with the path sitting behind the NVK_EXPERIMENTAL=dlss environment variable because known bugs remain.

The catch is the reliance on pre-compiled binaries; NVK can only run DLSS where compatible bytecode already exists for the GPU in use. The proprietary Nvidia driver avoids that limit with a route that compiles PTX, Nvidia's intermediate assembly, down to GPU bytecode at runtime. NVK has no equivalent, because it can’t translate Nvidia PTX into NIR, which is the intermediate representation Mesa drivers compile from.

Support for DLSS across the broader Linux graphics stack has been uneven, to say the least. As of late last year, Nvidia's DLSS 4 was still unsupported in Valve's VKD3D-Proton translation layer, which converts DirectX 12 calls to Vulkan for games running through Proton.

NVK began in 2022 as a from-scratch Vulkan driver led by Collabora's Faith Ekstrand alongside Karol Herbst and Dave Airlie at Red Hat, and it supports Turing (RTX 20-series and GTX 16-series) and newer architectures. In late 2024, it became the first open-source Vulkan driver for Nvidia hardware to pass Khronos conformance, reaching Vulkan 1.4 provisional spec. It runs on the Nouveau kernel driver and is separate from Nvidia's own open-source kernel modules, which the company ships with its proprietary user-space software stack.

At the XDC2025 conference in November, Ekstrand said NVK runs at around 50% of the official Nvidia driver's speed in many titles, that ray tracing is still in progress, and that the team is "barely keeping the lights on" with current developer resources, according to Phoronix.

An extremely unfortunate PC builder is the latest to fall victim to Amazon's prolific returns scams, after the Nvidia RTX 5070 they received from the website turned out to be a DVD re-writer, a mousepad, and the busted logic board from an early 2000's Kenwood AV receiver.

what i got sent instead of a 5070 from r/pcmasterrace

The victim was gifted a brand new MSI Ventus 2X variant of the RTX 5070 from Amazon by a friend at a cost of 605 euros ($700). A few days later, when the package arrived, it weighed the same as the real thing, but it certainly did not have a graphics card inside. Instead, the customer received what appears to be a broken logic board from an old Kenwood AV receiver, a DVD rewriter, and what seems to be a mousepad.

"This was shipped and sold by Amazon," u/luutherr told Tom's Hardware. They also provided us with proof of purchase and confirmed the item was a gift from a friend, making the scam all the more galling. That means someone in the middle is the bad actor. In reality, what most likely happened was a scam-swap, where someone previously bought the item, emptied its real box contents, and filled it back up with junk that weighs the same. They then filed for a return, probably citing personal preference as the reason.

Since the box still carried the same weight and the product wasn't returned because of a defect, it ended up back on sale after passing some basic checks. Someone else buys it, and Amazon or the seller unknowingly sends that person the fake item, completing the circle. Believe it or not, this whole process actually used to be worse before Amazon ended its commingling program last year, which sellers exploited to avoid being traced.

In the end, the same system that delivered OP the wrong product should come in handy for delivering justice. A simple return request should get them their money back, but it will certainly erode the customer's trust in the platform. We would say this is a reminder to always stay vigilant when buying PC hardware with prices that seem lower than usual. But since this was bought from the official MSI store and sold directly by Amazon, it's simply a consequence of deceitful human nature.

We've seen a wide variety of fake GPUs end up on Tom's Hardware, including entirely hollow ones that don't have a die to begin with. Now, scammers have found a new trick to make the con more believable — they're selling graphics cards with dies made out of plastic. That's what happened with Brother Zhang, a well-known Chinese hardware shop owner, who came across a used, broken RTX 4090 purchased for roughly $222.

As expected, you're receiving a dud for that price, and it's usually a gamble these vendors are willing to take in order to repair the GPU and flip it for profit. Or, in this case, produce educational content for spreading awareness. At first, the PCB inside the graphics card looked normal, but upon closer inspection, the die already had irregular markings. It said it's an "AD102-300-A1" die, which is what the RTX 4090 actually uses.

However, the "TW 3043E2" above it indicates the card was somehow manufactured in 2030, which is not possible unless you're a time traveler. There was no QR code engraved at the corner of the die either. All the componentry surrounding the chip also didn't look authentic, as if it had been replaced. When the technician touched the core, it felt unusually smooth, and, sure enough, it turned out to be plastic; there was no silicon inside.

The VRAM wasn't made out of plastic, which is a real possibility, but all the chips were "scrap" and only put there to fill up the PCB. So, neither the GPU nor the GDDR6X memory was real. Brother Zhang essentially got a $200 paperweight that looks kind of cool if you're a hardware geek. Thankfully, this card didn't belong to any customer, and the fact that it ended up with a repair shop means it can serve as a precautionary tale.

Always remain vigilant when making secondhand purchases, especially for expensive parts like a graphics card. In this day and age, just benchmarking a GPU isn't enough because scammers have been known to swap RTX 4090 dies for RTX 3090 or 3080 silicon. If a deal looks too good to be true, it more than likely is. Unless you can open up the card to check its PCB, make sure to tally the benchmark results with the performance you see for it online.

Nvidia has just released a new update for RTX Remix, its modding platform designed to retrofit old games with modern lighting and materials. RTX Remix 1.5 brings a bunch of improvements, but the highlight feature is the improved RTX IO storage compression that can cut down on the size of modded games. The update also adds agentic AI in the form of RTX Remix Skills, along with Smooth Normals for more natural-looking geometry.

Let's start with RTX IO, which is by no means a new technology — it was introduced back in 2020 with the RTX 30 series — but it's now integrated in RTX Remix. Upgrading old games with fully ray-traced lighting, along with sharper textures, skyrockets their sizes. The original assets aren't replaced either since RTX Remix intercepts the game at runtime and simply injects the new assets on top while suppressing the older ones.

Now, thanks to new compression options in the packaging workflow, RTX IO can help reduce those ballooning file sizes considerably. Currently, Portal with RTX, Portal: Prelude RTX, and Half-Life 2 RTX demo support this feature. As such, the Half-Life 2 RTX demo has shrunk down from 80GB to just 50GB, constituting a 37.5% decrease, while Portal with RTX is now only 17GB instead of the 27GB it was previously.

RTX Remix 1.5 also brings a highly requested community feature called "Smooth Normals." Basically, once older geometry was upgraded with modern lighting, some elements would look blocky, almost as if anti-aliasing was turned off. Smooth Normals fixes this by making those assets look smoother and more lifelike. Traditionally, this is a manual process, but the new update now generates smooth normals automatically.

Lastly, RTX Remix Skills is now available in the modding platform, where you can use agents to help you accelerate your workflow. Nvidia pitches this as a lower barrier to entry for modding, even without coding skills or experience, and for remastering modern games that don't have fixed-function pipelines. Apparently, Dark Souls, Dragon Age: Origins, and Titanfall 2 are already in the process of being upgraded thanks to "this streamlined approach."

Today, RTX Remix is publicly available and open source, so you don't even need an Nvidia GPU to enjoy these modded games, and there's actually a pretty solid selection of them over at ModDB. You definitely, however, need an Nvidia GPU to develop/make the mods; you can grab RTX Remix right from the Nvidia App. The Remix agent instruction files for your preferred coding agent are available on GitHub.

Back in 2020, Intel first showed off its multi-tile data center GPU codenamed "Arctic Sound," part of the Xe-HP (High Performance) family. It was supposed to represent one part of to be the company's grand entry into the AI GPU market. Arctic Sound was ultimately limited to internal samples because it was cancelled as a commercial product. Today, one of those original engineering samples seems to have landed in the hands of Chips By Layers on X, who's pictured it in all its glory.

Intel was working on a single-tile, dual-tile and a quad-tile variant of Arctic Sound; the picture above shows two tiles flanked by four memory modules on either side, which are 8GB HBM2E chips, so 32GB of VRAM in total. A single Xe-HP tile had 512 Execution Units (EUs) in its original config, but they were cut down for actual samples. This dual-tile part has 480 EUs per tile, or 960 EUs combined, which comes out to 7,860 shader cores. Arctic Sound 2T also had a 300W TGP.

We can clearly see "Intel Confidential" marked on the IHS, along with "QVS8 1.00 GHz." Funnily enough, the OP actually ordered a Ponte Vecchio GPU but received this engineering sample instead. Ponte Vecchio is another fascinating product in Intel's graphics history. It was part of the Xe-HPC (High Performance Computing) family and the true halo-tier AI GPU from the company, stitching together a 47-tile matrix featuring Xe cores instead of conventional Execution Units.

Arctic Sound basically proved it was possible for EMIB to horizontally connect multiple GPU tiles, so Intel used that along with its Foveros 3D packaging tech to build Ponte Vecchio. Eventually, Arctic Sound was cancelled as a commercial product because it was simply too expensive to produce. The company reworked it into "Arctic Sound-M," which became the "Intel Data Center GPU Flex" series and it was moved to the Xe-HPG (High Performance Gaming) microarchitecture instead.

Next year, we expect to see Jaguar Shores, which can be looked at as a spiritual successor to both Ponte Vecchio and Arctic Sound since it scales the multi-tile concept to an unprecedented scale. Technically, though, it's more in-line with Ponte Vecchio since it's a flagship GPU, and that was already supposed to receive a direct successor in the form of Falcon Shores, but that lineup met the same fate as Arctic Sound last year.

The upcoming Cresent Island GPUs with LPRDR5X memory target a similar, cost-effective solution to data center compute that the original Arctic Sound tried to, so they're probably the closest in terms of a proper sequel.

No graphics card is safe from surging prices driven by the global memory shortage and the ongoing AI boom, whether it's one of the best graphics cards for gaming or workstations. Nvidia has quietly increased the price of the RTX Pro 6000, the flagship of its Blackwell workstation series, to a jaw-dropping $13,250, representing a 55% increase over its original launch price just one year ago.

Nvidia offers three different variants of the RTX Pro 6000 that cater to a wide range of consumers. The chipmaker designed the standard Workstation Edition and the more power-efficient Max-Q Workstation Edition for the professional segment. In contrast, the data center-oriented Server Edition targets large-scale enterprises.

Nvidia launched the RTX Pro 6000 Blackwell and RTX Pro 6000 Blackwell Max-Q in March 2025. With a launch price of $8,565, it was always a premium product. Nonetheless, many consumers sought out the RTX Pro 6000 for its impressive performance in professional workloads.

With Nvidia now asking $13,250 for the RTX Pro 6000, it has gone up by a whopping 55%. Nvidia lists the PNY RTX Pro 6000 Blackwell at $11,359.99, which is 14% less than the MSRP. However, it’s important to note that these prices are the official listings for the RTX Pro 6000 on Nvidia’s marketplace; while a good reference, they do not always reflect the lowest available prices.

Nvidia RTX Pro 6000 Blackwell Pricing

For instance, Newegg currently sells the RTX Pro 6000 Blackwell for $12,099.99, offering a 9% savings compared to Nvidia’s official marketplace price. When it comes to the other variants of the RTX Pro 6000, Nvidia’s marketplace offers lower prices than those found on Newegg or B&H Photo Video. Sometimes retailers are implementing significant markups, so it's more affordable to shop at Nvidia for certain models. While Nvidia doesn’t appear to offer the server variant directly to the general public, Newegg has it listed for a steep $14,999.

Some of these listings come from third-party sellers on Newegg, and others are marked as OEM units. OEM products are generally intended for system integrators or enterprise customers and are sold in bulk, so they typically don't come with the fancy retail packaging.

Realistically, we shouldn’t expect graphics card pricing, whether for consumer gaming cards or professional workstation models, to improve any time soon. The only consistent trend is that prices will continue to climb until the memory shortage ends. Prices vary significantly across different retailers and even official marketplaces like Nvidia's. The best approach is to look around before pulling the trigger on a graphics card purchase.

AMD’s Radeon RX 9070 XT graphics card has finally penetrated the Steam Survey video card user-share table. The complete set of new-generation RDNA 4 graphics cards data from AMD is now nestled within the Steam gamer popularity tables, with the performance-leading RX 9070 XT highest placed at position 25. AMD took the wraps off the RX 9070 XT and regular RX 9070 at a special event in Feb 2025, with availability starting from March 2025. The RX 9060 XT was a Computex 2025 (~end of May) launch. So the charting of the family has been a long time coming.

Valve doesn’t publicly state a minimum share threshold for inclusion in the results table, but whatever formula lies behind it, the numbers must have climbed sufficiently by May 2026 for the complete Radeon RX 9000 family to now make the grade. Notably, with its newfound data, the RX 9070 XT's 1.35% share sits just a shade behind the RTX 5080, which has 1.52%.

Green Team context and AMD’s leading mystery GPU

Nvidia dominates the Steam GPUs chart, as you may expect. The current leader of the Steam GPUs pack is the time-tested Nvidia GeForce RTX 3060 with a 4.02% share according to the newest survey. Positions two and three are the laptop (3.99%) and desktop (3.74%) versions of the RTX 4060, so some would call this Ada Lovelace GPU the real champion of champions.

Currently, the highest placed Red Team GPU is the nebulous ‘AMD Radeon Graphics’ at position 13 and 1.89% share. Some observers reckon this Steam entry impacts the tally of named models, as the Steam Client miscategorizes discrete models for some reason, perhaps due to some iGPU + GPU combos. There are also two other instances of ‘AMD Radeon(TM) Graphics’ in the table, muddying the waters.

At position 39, the RX 9060 XT has made its debut with a reported 0.72% share of Steam users gaming on this mid-ranger. The stats don’t differentiate between the 8GB and 16GB variants of this card.

We have to go all the way down to position 90 to see the Radeon RX 9070 non-XT graphics card. It has a user share of 0.18% according to the figures. For some reason, this efficiency king among GPUs has been present in the Steam Survey much longer than its brethren. We mentioned it popping up with just a 0.16% market share at the start of this year. The revised 0.18% figure doesn’t show spectacular growth, despite some of the praise heaped on this SKU. However, since the pricing of our current best-pick all-around enthusiast graphics card, the RX 9070 XT, can be so close, it’s probably not surprising that the non-XT is overshadowed.

AMD recently launched the RX 9070 GRE worldwide. This 12GB variant of the RX 9070 has been available for months in the Far East, but we aren’t surprised it hasn’t entered the Steam Survey yet (if it will ever make it).

The memory drought continues to affect manufacturers of the best graphics cards and everyday consumers hoping to upgrade their systems. However, it seems to have impacted some vendors more severely than others. Manli (via VideoCardz) has expanded its arsenal with two new custom GeForce RTX 3060 and GeForce RTX 3050 graphics cards. The silent launch comes six years after the debut of Nvidia's Ampere architecture.

It may be perplexing to some that graphics card manufacturers are re-releasing products that are two generations old. However, it makes a lot of sense if you look at it since Ampere comes from Samsung’s mature 8nm (8N) manufacturing process. The process node should now be producing excellent yields, making it far more cost-effective to produce Ampere silicon than to produce Ada Lovelace or Blackwell silicon.

The choice to pick the GeForce RTX 3060 and GeForce RTX 3050 for an Ampere revival isn't by chance, either. While everyone dreams of playing AAA games at 4K and maximum settings, mid-range graphics cards ultimately drive the majority of sales. If we look at Steam, the world's largest gaming platform by player count, the GeForce RTX 3060 still reigns as the most popular graphics card despite being five years old. You can say what you want about the GeForce RTX 3050, but it's still sitting comfortably in fourth place.

The memory shortage has disrupted the supply chain for graphics card manufacturers, making it challenging to secure memory inventory, especially the latest GDDR7, at reasonable prices. The fact that the GeForce RTX 3060 and GeForce RTX 3050 use slower-binned GDDR6 memory chips (15 Gbps and 14 Gbps, respectively) and sometimes fewer chips somewhat helps preserve the vendor's profit margins. They're more affordable to produce and move than a GeForce RTX 4060, which uses faster, more expensive 17 Gbps GDDR6 chips, or a GeForce RTX 5050 or GeForce RTX 5060, which use 20 Gbps GDDR6 and 28 Gbps GDDR7, respectively.

The Manli GeForce RTX 3050 6GB Nebula Twin and GeForce RTX 3060 (M2521+N630) are your typical no-frills Ampere graphics cards that target consumers who value affordability over flashy features. They stick to the old tried-and-true dual-slot design with a dual-fan cooler. They conform to Nvidia’s reference specifications, meaning these graphics cards do not feature any factory overclocks.

Manli’s popularity is mainly in the Asian market, so it's highly unlikely these Ampere graphics cards will make their way to the U.S. market. Manli’s decision to re-launch two-generation-old Ampere models lends further credence to a recent rumor that Nvidia's board partners, including Asus, Colorful, Galax, and MSI, are reportedly restarting GeForce RTX 3060 production in July.

Overall, the return of the GeForce RTX 3060 and GeForce RTX 3050 to the market is not necessarily a bad thing, since these Ampere-powered graphics cards remain popular among gamers for their price-to-performance ratio. The true benefit lies with the pricing, though. Custom GeForce RTX 3060 and GeForce RTX 3050 graphics cards start at $299.99 and $239.99, respectively, which are close to their original MSRPs. Time will tell if the resurrection improves pricing on Ampere offerings.

Next-gen gaming GPUs from both AMD and Nvidia are expected to be announced sometime next year, following the (roughly) biennial release cadence of these cards. Tweakers, a Dutch publication present at Computex 2026, asked a few manufacturers at the show about RDNA 5 and got varying responses. In general, the AIB partners suggested that we should see new GPUs about a year from now, but some thought hardware may not hit the shelves until late 2027 or early 2028.

One manufacturer said it expects next-gen AMD graphics cards in the second or third quarter of 2027, while another said it could be pushed outside 2027 entirely and into early 2028. But there's still a chance for a late 2027 release. Keep in mind that the announcement and actual launch differ; AMD could introduce RDNA 5 in late 2027, but the GPUs might actually make it to market in early 2028, for example.

AMD showed off RDNA 4 for the first time at CES 2025, while the initial models — RX 9070 and RX 9070 XT — didn't ship until March. RDNA 3 was a bit better in this regard with a November 2022 announcement and December 2022 launch period. RDNA 5 is rumored to be a major upgrade for Team Red with features like dual-issue execution in the works, so the company wouldn't want to deliver an undercooked product hastily.

Nvidia debuted the RTX 50 series at CES 2025 as well and current rumors point to Rubin-based gaming GPUs coming in late 2027, with the same early 2028 murmurs heard for the RTX 60 series as well. If true, both GPU makers would be closely aligned in their launch schedules, but it's simply too early to tell. The PC hardware industry is going through a turbulent time, and the volatility caused by the AI boom means that gaming GPUs are the least of these companies' concerns right now.

While we're here, Intel is still in the business of making gaming-focused GPUs. It just launched the new Arc G3 family for handheld consoles featuring Panther Lake silicon, but, unfortunately, the future for dedicated graphics cards is looking a bit dire. On the console side, Xbox Helix and Sony's PS6 are still expected to at least be announced next year as, by then, it will have been seven years since the current generation launched. These systems will also be powered by next-gen AMD silicon.

Nvidia’s GeForce RTX 30 series (codenamed Ampere) firmly established itself among the best graphics cards of its time. Interestingly, it seems that Nvidia may have left some money on the table with Ampere. The latest photographs and benchmark results shared by hardware leaker Gok clearly show that the GeForce RTX 3050 Ti is real and has at least reached the prototype stage.

Nvidia did bring a GeForce RTX 3050 Ti to the market, but only for laptops, catering primarily to mobile gamers. What we're seeing today is the desktop version, which should not be confused with the GeForce RTX 3050 Ti Mobile or the GeForce RTX 3050 Ti Max-Q for laptops. Ampere was a popular and successful architecture for Nvidia. However, the downsides of Ampere's launch during the great graphics card shortage, first caused by the cryptocurrency mining boom and second by the COVID-19 pandemic, probably deterred Nvidia from releasing the GeForce RTX 3050 Ti.

The GeForce RTX 3050 Ti engineering sample, reportedly from a company named Robiny, leverages the PG190 SKU 40 design board. It employs the GA106 silicon, the same die utilized in other popular Ampere products, including the GeForce RTX 3050 and the GeForce RTX 3060. As you can tell from the model name, the GeForce RTX 3050 Ti slots in between the two aforementioned models. Once again, it's just an example of Nvidia's strategy to recycle high-end silicon to serve different market segments.

Nvidia GeForce RTX 3050 Ti Specifications

*Specifications are unconfirmed by Nvidia.

A perfect GA106 silicon has 30 Streaming Multiprocessors (SMs), but the GeForce RTX 3050 Ti has only 26 enabled, resulting in approximately 87% die utilization. With 26 SMs active, the Ampere-based graphics card features 3,328 CUDA cores, which is about 7% fewer than the GeForce RTX 3060, yet 30% more than the GeForce RTX 3050. The configuration puts the GeForce RTX 3050 Ti in a sweet spot, balancing performance and power efficiency.

The clock speeds for the GeForce RTX 3050 Ti fall well within expectations. The base and boost clocks are higher than those of the GeForce RTX 3060 because the GeForce RTX 3050 Ti has fewer CUDA cores. Conversely, the clock speeds are somewhat lower than those of the standard GeForce RTX 3050, which features even fewer CUDA cores.

On the contrary, the memory subsystem of the GeForce RTX 3050 Ti is a cross between those of the GeForce RTX 3050 and the GeForce RTX 3060. While it retains the 14 Gb/s GDDR6 memory modules found in the former, the memory operates over a wider 192-bit interface, similar to the latter's. As a result, the GeForce RTX 3050 Ti offers 50% higher memory bandwidth than the GeForce RTX 3050 but trails behind the GeForce RTX 3060 by 7%.

The GeForce RTX 3050 Ti's memory capacity raises some eyebrows. The graphics card appears to carry 6GB of GDDR6 memory, half of what's available on the GeForce RTX 3060 and 2GB less than a GeForce RTX 3050. For reference, we’re comparing the original models of the GeForce RTX 3060 and GeForce RTX 3050, which shipped with 12GB and 8GB of memory, respectively. Nvidia has introduced different memory configurations over time, including the GeForce RTX 3060 8GB, GeForce RTX 3050 6GB, and GeForce RTX 3050 4GB, as well as a couple of variations with different silicon revisions.

Gok shared a screenshot of the GeForce RTX 3050 Ti achieving a graphics score of 7,787 points in 3DMark's Time Spy benchmark. A quick search shows the GeForce RTX 3060 scoring between 8,200 and 9,000 points on the same benchmark. Meanwhile, the GeForce RTX 3050 scores range from 5,300 to 6,400. If we use the maximums for comparison, the GeForce RTX 3050 Ti could be up to 22% faster than the GeForce RTX 3050 or up to 13% slower than a GeForce RTX 3060.

The GeForce RTX 3050 and GeForce RTX 3060 launched at $249 and $329, respectively. The GeForce RTX 3050 Ti could easily have filled the gap at $289. Then again, Ampere was around during difficult times where MSRPs didn't mean anything. The GeForce RTX 3060 still reigns as the most popular graphics card on Steam even to this day. Sadly, we can't rewind time to see what would have happened if the GeForce RTX 3050 Ti had come out. In any event, the graphics card would have further strengthened Nvidia's hold in the mid-range segment. With custom GeForce RTX 3060 starting at $479 nowadays, budget gamers could use another alternative, and something like the GeForce RTX 3050 Ti could certainly fill that spot.

A potential "Super" refresh for Nvidia's Blackwell 50-series GPUs has been part of the news cycle for almost a year at this point, with the last substantial sighting coming from Seasonic's PSU calculator nine months ago. Since then, the rumor mill has been mostly silent due to an AI boom-sized component crisis that engulfed all production lines. But now, it seems like the RTX 50 Super series is "back on track," with leaker MEGAsizeGPU claiming that there's even a new SKU in the works.

We've already heard the RTX 5070 Super, RTX 5070 Ti Super, and RTX 5080 Super mentioned before, but this time, there's also an RTX 5060 Super in the mix. This rumored GPU could come with 12GB of GDDR7 RAM, according to the leak, possibly using 4x 3GB modules saturated across the same 128-bit bus that the regular RTX 5060 has. This card could also just be called RTX 5060 12GB, as Nvidia has named a few SKUs like that previously.

The leak doesn't mention other GPUs specifically, but through prior rumors, we can infer that the RTX 5070 Super might feature 18GB of VRAM, while both the RTX 5070 Ti Super and the RTX 5080 Super are suggested to rock 24GB pools — all enabled by 3GB GDDR7 chips. One of the replies in the post above claims that specs for these three SKUs apparently remain unchanged.

*= unconfirmed models based on leaks and rumors

We don't know when these GPUs will actually be released, but the leaker says he expects them to still launch in 2026. With DRAM being as expensive as it is right now, and GPU prices affected by the AI boom, these new RTX 50 Super SKUs may not exactly be good value. Back in November of last year, there were murmurs of these GPUs even being cancelled due to just how valuable 28Gbps GDDR7 modules had become.

To add fuel to the fire, Nvidia itself quashed rumors of an RTX 50 Super series announcement at CES 2026 earlier this year. Add to that the leaked RTX 5050 with 9GB of VRAM, highlighting the sheer desperation of the moment, and any hope left was killed. An overpriced RTX 50 Super series launching in these circumstances was unlikely. So, a single churn of the rumor mill isn't enough to reignite excitement; we'll have to wait and see if the frequency of these leaks once again picks up.

During Computex, multiple reports cited that AMD was potentially skipping FSR 4.1 integration on RDNA 3.5 iGPUs, leaving these users with no choice but to use older FSR versions. AMD client and graphics marketing executive Frank Azor posted on X pushing back against this claim, suggesting RDNA 3.5 GPUs will indeed support FSR 4.1 in the future.

The source of all this controversy reportedly originated from AMD’s VP and GM of Ryzen and Radeon products, David McAfee. Azor admitted in his X post that he wasn’t able to hear McAfee’s thoughts about FSR 4.1 support on RDNA 3.5 in person, however, he clarified that no decision to drop RDNA 3.5 support from AMD’s latest FSR implementation had been made.

Azor's post is carefully worded, and doesn't make any promises one way or the other. But it does suggest that support for FSR 4.1 on RDNA 3.5 hasn't been dropped just yet. Even though RDNA 3.5 exclusively revolves around integrated GPUs and not discrete GPUs or graphics cards, many gaming-capable handheld devices and laptops come with RDNA 3.5-powered hardware, including Strix Halo-powered laptops featuring GPU hardware equivalent to an RTX 4060.

All of these devices make RDNA 3.5 a highly valuable user base to keep supporting with FSR updates. There is also no architectural hardware difference that we are aware of that would prevent AMD from porting FSR 4 to RDNA 3.5. RDNA 3.5 is a incremental update over RDNA 3, primarily geared towards improving power efficiency.

AMD finally announced official FSR 4.1 upscaling support for RDNA 3 and RDNA 2 GPUs last month. The move comes almost a year after AMD accidentally leaked its own FSR 4 version online capable of running on non-RDNA 4 hardware using INT8 instructions. FSR 4.1 is the latest iteration of the FSR feature set, including an improved upscaler that better preserves detail in motion and Ray Regeneration 1.1.

It's a grim time to be a PC gamer and enthusiast, as anybody who has spent any time making a build list well knows. The AI gold rush has made practically everything that goes into a PC more expensive as LLMs and agentic workflows conspire to grab every available square millimeter of logic, memory, and storage wafers the world over.

For all that, here we are at Computex 2026 with a fresh graphics card review. AMD is bringing its formerly China-only RX 9070 GRE (aka “Great Radeon Edition,” neé Golden Rabbit Edition) to global markets. This card has been available in the Chinese market for about a year, but AMD has decided that now is the time to bring the GRE to the wider world.

And here it is, launching at the same $549 in the USA that the RX 9070 ostensibly listed for. That's sure to cause some double-takes, but times have obviously changed since the 9070 arrived a bit over a year ago.

In today's wild graphics market, prices on what we might call "entry-level enthusiast" cards with large memory capacities have gotten out of whack with the performance levels they deliver. The $349 RX 9060 XT 16GB is now selling for closer to $450, and the $429 RTX 5060 Ti 16GB is now closer to $570. The RX 9060 XT might be situationally recommendable at that price, but the RTX 5060 Ti 16GB is clearly DOA.

And higher-end cards that would formerly have served as true midrange products are more expensive, too. The $549 RX 9070 sells for closer to $650, as does the RTX 5070.

So there's currently a wide gap in the graphics market for enthusiasts who want strong enough performance for high-refresh-rate gaming at both 1080p and 1440p without spending a dollar more than they need to, and AMD sees an opportunity for the RX 9070 GRE to fill it.

For a quick refresher, the RX 9000 series uses the RDNA 4 graphics architecture, AMD’s first to include dedicated matrix math accelerators for AI tasks like upscaling and frame gen. RDNA 4 also boasts improved RT units that claim up to a 2x improvement over the RDNA 3 CU. RDNA 4 also includes a much-improved media engine that can encode and transcode video quickly with much higher image quality than past Radeon products.

The RX 9070 GRE uses the same large Navi 48 GPU as the RX 9070 and RX 9070 XT, but it's the most cut-down version of that chip thus far, with only 48 RDNA 4 compute units of a possible 64. That downsizing has the expected downstream consequences for texture sampling throughput, pixel fill rate, and raw FLOPS compared to higher-end RDNA 4 cards.

AMD has also decked out the GRE with slower GDDR6 memory and less of it compared to its higher-end stablemates. This card offers 12GB of GDDR6 running at 18 Gbps on a 192-bit bus, which is good for 432 GB/s of raw memory bandwidth. (The RX 9070 and 9070 XT use 20 Gbps GDDR6, as does the RX 9060 XT.)

All of those cuts are clearly meant to thread the performance gap between the RX 9060 XT 16GB and the RX 9070. In terms of raw FLOPS, the GRE isn't that far behind the RX 9070, but its slower GDDR6 clocks and narrower bus both mean that vital memory bandwidth is down a whole 33% compared to the 9070 and 9070 XT. And just 12GB of GDDR6 means this card will be less well suited to RT and 4K gaming versus its two higher-end stablemates.

All that suggests it might have been good for AMD to be bolder with the RX 9070 GRE's price. With just 12GB of VRAM and relatively low memory bandwidth, this card is less appealing for local AI trailblazers than the higher-end 9070 and 9070 XT might be, and as we'll see, its gaming performance isn't so close to the 9070 that it would threaten to cannibalize sales of that product.

But a $479 9070 GRE (or even a $499 one) would probably kill every current RX 9060 XT 16GB card dead — or at least force prices back down, both of which are outcomes that AMD's board partners would likely be unhappy with in today's wild market and constrained upstream supply conditions.

But another angle here is that hardware is just the beginning of evaluating a given graphics card in 2026. You don't just plug one into a PC and install occasional driver updates for it any longer. Modern gaming requires a GPU vendor to conduct ongoing investment in a multi-part software stack encompassing upscaling, frame generation, and RT denoising, and to effectively evangelize that stack to developers and get it into games.

Thanks to Nvidia's sustained investment in the DLSS ecosystem, owning a GeForce card means that you can generally trust that you'll enjoy either day-one support for the latest DLSS versions in games or an easy override using the Nvidia App. And Multi Frame Generation on Blackwell has matured to the point that early tradeoffs with input latency are basically ironed out in the latest titles. That all means that you have a wide range of freedom to tune performance, smoothness, and image quality to taste on GeForces.

AMD certainly has competitive AI-powered upscaling options in FSR 4 and 4.1, both of which are major improvements over FSR 3 and earlier. And you can enable them in many games with driver overrides, just as with the Nvidia App. But community surveys have still shown a strong preference for the output of DLSS, so AMD still has work to do on its upscaling models.

And for those who want to embrace the smoothness boost of framegen, AMD is clearly behind. FSR 4 ML Frame Generation is still limited to a 2X multiplier, and it's only supported in a handful of games compared to DLSS MFG. Even Intel has enabled higher 3x and 4x framegen multipliers for its Arc products.

And AMD's Ray Regeneration RT denoiser is only available in a couple of titles, while you can usually find DLSS Ray Reconstruction alongside titles that are pushing the state of path-traced effects forward. Ray Reconstruction is a key feature in titles like Resident Evil Requiem, Pragmata, Indiana Jones and the Great Circle, Doom: The Dark Ages, and more. In fact, AMD cards are locked out of path-traced effects entirely in Resident Evil Requiem and Pragmata.

Whatever the cause of these divergent experiences on GeForces and Radeons, the fact of the matter is that Nvidia has the money and developer relations muscle to make sure its DLSS features make their way into practically every new game, whereas AMD apparently does not, and that gap seems to grow wider with every AAA release.

All that is to say that if you choose a Radeon today, you are likely going to encounter more inconsistent feature support, fewer cutting-edge options for eye candy, and a less flexible performance tuning experience compared to GeForces.

And that all means that AMD likely needs to be more aggressive on pricing to get gamers back into its camp (and perhaps funnel some of its AI cash back into developer relations to stoke broader adoption of its tech). It's tough to admit that you're behind on these features and their adoption, to be sure, but pricing is a powerful way to make up some of the difference.

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For our testing, AMD sent over XFX's Swift Radeon RX 9070 GRE. This is XFX's most straightforward family of graphics cards, and the 9070 GRE version features a clean, reserved design without any kind of RGB or accent lighting whatsoever. If you like stealthy builds, this card would be a fine pick for the purpose.

This card is already listed at Best Buy in the USA for AMD's $549 MSRP, so we'll have to see whether that price holds and whether you can actually buy it from stock.

At least according to retail specs, XFX rates this card for the same 2790 MHz boost clock and 220 W TDP as AMD's reference spec, so its performance in our test suite should be representative of what a 9070 GRE "reference" card would deliver, even though no such actual product exists.

While this isn't a fancy RX 9070 GRE, it doesn't feel cheap or insubstantial. The backplate is made of sturdy metal, and the heatsink proper is well-finished and features a dense nickel-plated fin stack for plenty of surface area.

We weren't able to perform formalized noise testing on this card before we had to leave for Computex, but the large heatsink and trio of fans mean that its noise signature is quiet and pleasant under load. You likely won't be able to hear this card over other components in a gaming PC when it's running full tilt.

As is common nowadays, XFX cuts a vent in this card’s backplate to allow air from the forward portion of the fin stack to escape directly upwards into the case’s airflow path.

Around back, you'll find three DisplayPort 2.1 connectors and a single HDMI 2.1b port.

The RX 9070 GRE relies on two eight-pin PCIe connectors to fuel its 220W TDP, so unless you do something really stupid, you won't have to worry about potential 12V-2x6 meltdowns.

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We do our very best to deliver clean, reliable benchmark numbers. Each of our tests encompasses 60 seconds or more of real-world gameplay, carefully chosen to represent what we expect will be typical gameplay experiences. We sanity-check every result and retest whenever necessary to ensure that outliers don’t muck up our final standings.

We test without upscaling or frame generation at a mix of high and ultra settings across all of our titles. While we personally recommend using the full range of upscaling and frame generation options available in a given title to achieve your desired balance of performance and image quality, focusing on native rendering in reviews keeps our results directly comparable across different vendors' products.

Our 2026 GPU test suite covers 15 titles. 11 of them start with a raster baseline or are raster-only, while four more of them include additional RT options that we employ in our tests. Two more require a graphics card with RT support to run at all. We tested Assassin's Creed Shadows and GTA V Enhanced exclusively with RT enabled.

Here's our complete list of tested titles:

• Arc Raiders
• Assassin's Creed Shadows (RT only)
• Black Myth: Wukong (+RT)
• Marvel's Spider-Man 2 (+RT)
• Cyberpunk 2077 (+RT)
• Alan Wake II (+RT)
• Fortnite
• Marvel Rivals
• Apex Legends
• Counter-Strike 2
• Stalker 2
• Doom: The Dark Ages (RT required)
• Indiana Jones and the Great Circle (RT required)
• Grand Theft Auto V Enhanced (RT only)
• Clair Obscur: Expedition 33

We've tried to cover a broad mix of game engines, graphics APIs, and game types in this lineup, from popular esports experiences to crushing AAA visual feasts developed both natively for PC and ports from consoles. Our selected games stress every part of a modern graphics card, from pure compute horsepower to VRAM management to RT to driver overhead at high frame rates. If a card rises to the top of our charts after weathering all of these tests, you can be sure that it's a standout product.

When picking titles to test, we considered games' time in market, active player counts, review scores (to see whether a title is likely to become an enduring part of PC gaming), and the ease of conducting a repeatable benchmark, among other factors.

Wherever possible, we use real, live, eyes-on-screen, hands-on-mouse-and-keyboard benchmark runs. We don't think automated, on-rails, hands-off canned benchmarks fully capture the gameplay experience on a given graphics card.

Only by actually playing a game can we account for factors like how input lag affects the experience, and making sure that a title has acceptable input lag is becoming a key consideration when latency-sensitive framegen techniques are becoming more and more common as performance-boosting tools.

Our current test system comprises the following components:

• CPU: AMD Ryzen 7 9800X3D
• Motherboard: ASUS TUF Gaming X670E-Plus Wifi
• Memory: G.Skill Trident Z5 Neo 32GB DDR5-6000
• Storage: Inland Gaming Performance Plus 4TB PCIe 4.0 NVMe SSD
• Power supply: MSI Ai1600TS

With all that out of the way, let's dive into our results.

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If all you want is the TL;DR, here you go: the RX 9070 GRE delivers a 120 FPS average at 1080p across our 11-game raster-only test suite and an 86.6 FPS average at 1440p. That puts it in a solid position to enable high-refresh-rate gaming for the two most popular monitor resolutions among PC gamers, and it's a nice boost over lower-midrange products like the RX 9060 XT 16GB and RTX 5060 Ti 16GB.

But overall raster performance falls short of a 60 FPS average at 4K, which remains the turf of the RTX 5070, RX 9070, RX 9070 XT, and RX 5070 Ti at a minimum. For a truly midrange product, though, that's an OK tradeoff for the GRE, as 4K monitors are still far less common than 1440p screens. And if you can deploy FSR 4, you can still upscale your way to a fast and high-quality 4K experience.

Read on for per-game results. We'll largely let these numbers speak for themselves except where a given game requires particular elaboration.

Black Myth Wukong

Why it's here: a stunning showcase for PC graphics

What it stresses: Compute, VRAM, RT (when enabled)

Black Myth Wukong is a gorgeous example of what’s possible from Unreal Engine 5, but it places heavy, heavy demands on graphics cards in exchange. This title has a free benchmark tool, but to ensure we get all the updates that Game Science has made to this game since launch, we picked up the full version and devised our own benchmark sequence.

Alan Wake II

Why it's here: One of the richest AAA feasts for the eyes on PC

What it stresses: Compute, VRAM, RT (when enabled)

Counter-Strike 2

Why it's here: over a million active players can't be wrong

What it stresses: Compute, driver overhead at high frame rates

Counter-Strike 2 needs no introduction as one of the most popular esports titles out there. In general, GeForce cards really seem to struggle with 1% lows in this title. Radeons do a better job of delivering both the high average frame rates and 1% lows that we want for a smooth gaming experience. But frame rates are so high in general that you're unlikely to notice any dips in performance.

Arc Raiders

Why it's here: One of 2026's most popular games, powered by UE5

What it stresses: Compute

Arc Raiders shows one of the widest performance divergences between GeForces and Radeons of any game in recent memory. The 9070 GRE barely outperforms the 5060 Ti in this title, and both it and the 9070 are outpaced by the RTX 5070.

We weren't aware of how large this divergence was before we set out to perform our 2026 GPU Hierachy testing, but given how popular Arc Raiders is, you should know about it before buying a Radeon.

Fortnite

Why it's here: It's Fortnite

What it stresses: Compute

Fortnite may have a reputation as a potato game, but make no mistake: this is an Unreal Engine 5 showcase through and through, and it can deliver stunning visuals in between the heated skirmishes of its pop-culture-blending brawls.

Radeons deliver an especially strong showing in Fortnite at 1080p and 1440p. The 9070 GRE even goes neck-and neck with the RTX 5070 until we reach 4K.

Apex Legends

Why it's here: Unique engine, giant player base

What it stresses: Compute

Apex Legends is another wildly popular esports title that needs no introduction. It normally has a 144 FPS cap, but you can disable it with a launch option to reach a 300 FPS ceiling.

In this full-range testing, many of our cards hit Apex's 300 FPS cap at 1080p. Unless you enjoy leaving large parts of your pricey GPU unused, you really should step up to 1440p at a minimum and possibly even 4K, where the 9070 GRE and many other cards can still deliver esports-friendly frame rates with better image quality.

Marvel Rivals

Why it's here: another hugely popular free-to-play title

What it stresses: Compute

Marvel Rivals is another popular free-to-play game that might have a reputation as a bit of a potato title. Unlike other games in our suite that share its UE5 foundation, Rivals doesn’t require a superhero of a graphics card to hit high frame rates. The 9070 GRE turns in a fine performance

Clair Obscur: Expedition 33

Why it's here: One of the most acclaimed games in recent memory

What it stresses: Compute

Clair Obscur: Expedition 33 has stunning Unreal Engine 5-powered visuals. Since it keeps VRAM usage in check even on 8GB cards, its performance is mostly defined by how much compute horsepower you can throw at it.

Marvel's Spider-Man 2

Why it's here: A newer PlayStation port

What it stresses: Compute, VRAM, RT (if enabled)

Marvel's Spider-Man 2 is a representative PlayStation port. Like many games in this vein, it really wants both strong compute resources and plenty of VRAM from a GPU to hit high frame rates, especially with RT enabled.

But for rasterization, 12GB is enough VRAM to allow the RX 9070 GRE to turn in over 100 FPS on average at 1080p and almost 80 FPS at 1440p, so it's a great foundation for swift and smooth gaming under those conditions.

Stalker 2

Why it's here: A visually stunning revival of a classic PC franchise

What it stresses: Compute, VRAM (to some degree)

Stalker 2 is another beast of a UE5 game, so much so that while the RX 9070 GRE manages over a 60 FPS average at 1080p, it falls short at 1440p. You'd probably want to dial in upscaling or dial settings back to high for a good 1440p experience here.

Cyberpunk 2077

Why it's here: One of the biggest PC releases of all time

What it stresses: Compute, VRAM, RT (when enabled)

Cyberpunk 2077 remains a beast of a title even this long after its introduction, at least once you get above 1080p. True to its mission, the 9070 GRE turns in high frame rates at 1080p and a solid 60 FPS average at 1440p.

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Our 2026 ray-traced tests span relatively lightweight RT titles such as Doom: The Dark Ages, Indiana Jones and the Great Circle, and Grand Theft Auto V Enhanced to moderately challenging titles like Cyberpunk 2077 and Marvel’s Spider-Man 2 to performance monsters like Alan Wake II, Assassin’s Creed Shadows, and Black Myth: Wukong at its Very High RT preset. If a card passes all of these tests with flying colors, it’s ready for any RT experience you can throw at it.

Beyond the high initial performance cost of enabling ray tracing, RT titles at higher resolutions are more likely to run over lesser cards’ VRAM pools, resulting in rough performance. That behavior tends to show up as wide spreads between average and 1% low frame rates, so keep an eye out in our graphs for when cards with less VRAM start to stumble.

The TL;DR: The RX 9070 GRE handles our RT suite at 1080p just fine, turning in a 65 FPS average and well-controlled 1% lows overall and a nice generational uplift compared to the 7800 XT. That’s a good baseline for enabling FSR 4 upscaling and ML Frame Generation where it’s available in pursuit of higher output resolution targets.

At 1440p, though, the GRE is already showing weakness due to its 12GB of VRAM, barely outperforming the RX 9060 XT 16GB and RX 7800 XT and landing behind even the RTX 5060 Ti 16GB. The RX 9070 and its 16GB of VRAM pull far ahead. If you're serious about RT on a Radeon, we'd strongly suggest stepping up.

DOOM: The Dark Ages

Why it's here: one of a new crop of games that requires RT to run

What it stresses: Compute, RT, VRAM

Even with mandatory RT support and everything cranked to Ultra Nightmare, DOOM: The Dark Ages isn't terribly hard for our stable of graphics cards to run well. The 9070 GRE hands in strong results at 1080p and 1440p, but 4K proves too much (as it does for most of our cards without upscaling).

Indiana Jones and the Great Circle

Why it's here: another of a new crop of games that requires RT to run

What it stresses: Compute, RT, VRAM

Indiana Jones and the Great Circle is a weird beast. It uses a unique fork of the id Tech engine to deliver its cinematic adventure gameplay. And at least in our test area, it's full of autosave points that can have rough effects on 1% lows. We've tried to control for this as much as possible, but just be aware that the 1% lows here are as much a product of the game's behavior as they are any differences between graphics cards.

Alan Wake II

Alan Wake II's RT effects are crushing even without Path Traced Indirect Lighting enabled. The biggest issue beyond the performance demands of these settings is that these effects don't really make a huge visual difference in this title, so you could just as soon ignore them and enjoy much higher frame rates.

Cyberpunk 2077

Cyberpunk 2077 is one of the few RT-heavy titles we've seen where enabling the feature creates major differences in image quality, so you might actually care about its performance. What we’re really looking for here is a solid foundation for upscaling, and the 9070 GRE delivers that level of performance at 1080p with a near-60-FPS average.

At 1080p, 12GB of VRAM is enough to avoid performance cliffs, and you can see the huge generational advantage the 9070 GRE has over the 7800 XT. That raw performance difference persists at 1440p, but the 9070 GRE's 1% lows suggest that 12GB of VRAM is starting to become a problem. And at 4K, the GRE's performance is roughly half that of the RX 9070 and behind even the 7800 XT, showing the advantages of 16GB of VRAM.

But none of those cards are delivering a playable experience at native 4K with RT, showing why it's more important to evaluate 1080p and 1440p as upscaling foundations.

Black Myth Wukong

Black Myth Wukong is tough on graphics cards even before we apply its RT presets, and Very High RT crushes everything into dust with native rendering. Even then, the game favors GeForce cards to such a degree that you'd need a massive dose of upscaling to reach playability with Very High RT on Radeons, even at 1080p.

Assassin's Creed Shadows

A new title for our 2026 GPU Hierarchy testing, Assassin's Creed Shadows boasts gorgeous RT visuals that make for a major upgrade when they're enabled. And it does all this without putting major pressure on VRAM.

As with many of our other RT titles, though, Shadows really seems to expect you to dial in upscaling (and maybe even some framegen) to achieve smooth frame rates, and the 9070 GRE provides a strong enough foundation for that purpose if you consider 1080p an input resolution for FSR 4 Performance at 4K, for just one of many potential examples.

Marvel’s Spider-Man 2

Enabling RT in Spider-Man 2 greatly improves the appearance of reflections on the many glass-clad buildings you'll swing by in its New York City setting, so it's worth the performance hit in our eyes. But the RX 9070 GRE's 12GB of VRAM already seems to be holding it back in this game at 1080p, as it isn't performing much better than the RX 9060 XT 16GB and RX 7800 XT. And the 9060 XT 16GB even outperforms the GRE at 4K.

Grand Theft Auto V Enhanced

It’s hard to believe we’re still testing Grand Theft Auto V more than 10 years after its arrival on the PC, but here we are. The latest Enhanced re-release adds appealing RT eye candy to Los Santos, and its demands on hardware are modest enough that even modest hardware can provide a solid enough performance foundation for upscaling.

Even with that in mind, GTA V produces some... interesting results on our cards. Radeon RX 9000-series products suffer from a major frame rate drop partway through our run, and that results in much lower 1% lows compared to RX 7000-series cards, which don't experience the same issue. (And neither do RX 6000-series cards, even though they're not shown here.) We've watched this issue persist for many months, and it doesn't speak well for AMD's latest-gen graphics cards that it's lingered this long.

GeForces aren't immune to weird performance in this title either, however. At 1080p and 1440p, higher-end RTX cards seem to suffer from some weird potential CPU-boundedness, and that also appears as a wide gap between average frame rates and 1% lows in our charts. But unlike the RX 9000-series cards, those drops are only perceptible as slight stutters rather than an extended, painful dip. Raise the resolution to 1440p or especially 4K, and those stutters lessen or go away.

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The Radeon RX 9070 GRE is surgically targeted to land in the wide-open performance gap between the RX 9060 XT and the RX 9070 for Radeons and the RTX 5060 Ti and RTX 5070 for GeForces, and it does exactly that for $549 as it arrives Stateside.

Wait, you might be saying. Didn’t the RX 9070 already launch at $549? Indeed it did, but outside of Prime Day events and holiday sales, we’ve rarely seen those cards available at that price. And the ongoing chip-pocalypse has durably spiked graphics card prices well above MSRP across the board, keeping $549 9070s a rare sight.

Even before the AI gold rush made all consumer tech more expensive, the past couple of years have shown that MSRPs are basically hopes and dreams without the supply to back them up, and that’s a headache that’s affected both AMD and Nvidia to varying degrees. Witness the consistently elevated prices of the RTX 5070 Ti, the RTX 5080, and the RTX 5090 even before the AI crunch.

But AMD was perhaps unreasonably aggressive with the promised pricing of the 9070 and 9070 XT given how rarely those products have been seen at MSRP. A 12GB card with a heavily cut-down die like the 9070 GRE would seem to offer a stronger price anchor, and as the distant player two in PC gaming graphics right now, AMD needs to give buyers a big, loud reason to pay attention.

At $479, the RX 9070 GRE would be the single best value in gaming by our calculations, period. But the realities of today’s market and AMD’s partner relationships probably limit the room for such a splashy sticker, given how much downward pressure it would place on the GDDR6-intensive RX 9060 XT 16GB. As things stand, the $549 MSRP makes the 9070 GRE the third-best value in gaming right now, after the RX 9070 and RTX 5070.

So what are you getting for that money? As a baseline, the GRE delivers a roughly 90 FPS 1440p raster experience, and that’s a solid place to be before you add FSR 4 upscaling and framegen to the mix. But if you got a $499 Radeon RX 7800 XT back in the day, you’re already enjoying a similar experience. And with a version of FSR 4 for RDNA 3 cards coming soon, there’s little reason for midrange RX 7000 owners to consider a jump.

Looking further back, the 9070 GRE is a strong upgrade for owners of the five-year-old RX 6700 XT and its 6750 XT refresh, both of which are now on the wrong side of 60 FPS at 1440p in our 2026 GPU Hierarchy testing. It delivers much better raster and RT performance, a vastly improved accelerated media engine, and official FSR 4 upscaling and framegen support, all of which will give RX 6000-series upgraders a much more modern and enjoyable gaming, streaming, and media transcoding experience.

The 9070 GRE might also tempt RTX 3070 owners that are struggling within the confines of that six-year-old card’s 8GB of VRAM. But the universal availability and generally superior image quality of DLSS upscaling and the added performance boost of DLSS MFG means that AMD will probably have a hard time convincing GeForce gamers to switch to an RX 9070 GRE versus an RTX 5070.

The two major drawbacks of this card lie in its 12GB of VRAM and, consequently, its RT performance at resolutions higher than 1080p. If you’re a fan of ray tracing and you’re considering this card, you will want to pay close attention to the availability of FSR 4 upscaling and ML Frame Generation or support for their overrides in any game you’d like to play. Those technologies will help mitigate the potential issues caused by 12GB of VRAM for memory-hungry RT titles.

But if you’re really serious about RT, we’d strongly recommend spending less than $100 more and getting an RTX 5070. It not only provides better baseline performance all around but also offers the one-two software punch of DLSS 4.5 upscaling and Dynamic MFG for effortless performance tuning, as well as Ray Reconstruction in some titles. You also avoid the annoying AMD lockout for path tracing in the latest Capcom releases like Resident Evil Requiem and Pragmata.

All told, the RX 9070 GRE is a strong midrange graphics card that gives buyers a useful step up between the RX 9060 XT 16GB and RX 9070 (and the RTX 5060 Ti 16GB and RTX 5070). We’d much rather have this product as a lifeline for PC gaming than the long-rumored-to-be-reintroduced RTX 3060 12GB, which is well past its sell-by date by every measure at our disposal.

But we still think that AMD could have truly changed the midrange game by going even cheaper than the GRE's $549 MSRP, given its performance and software ecosystem limitations compared to GeForces. At its listed price, we'll have to see whether the 9070 GRE offers enough of a hook to get buyers to bite.

• MORE: Best Graphics Cards
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• MORE: All Graphics Content

Asus has used its Computex press event to showcase a huge celebration of its ROG gaming sub-brand. It's been 20 years since the first ROG gear arrived, and Asus Chairman Jonney Shih commemorated the first footsteps of “The Journey of Dare” with the announcement of products that will form the ROG Edition 20 collection. You name it, there’s a cool black and gold ROG Edition 20 collection edition of it. From the headlining ROG Astral GeForce RTX 5090 Edition 20 to motherboards, full PCs, PSUs, monitors, routers, peripherals, chairs, and even luggage, there’s an Edition 20 design being showcased in Taipei.

ROG Astral GeForce RTX 5090 Edition 20

For many, the most alluring new limited edition product celebrating the first 20 years of the Asus Republic of Gamers will be the ROG Astral GeForce RTX 5090 Edition 20. The Astral is a well-established flagship for Asus and has even formed the basis of opulent extravaganzas dripping in gold.

Again, there’s gold in the Edition 20 design, but it is contrasted with plenty of matte black, red accents, and here plays second fiddle to the striking curved AMOLED display used by this commemorative design. Asus says this screen can be used to deliver “dynamic 3D visuals, custom animations, and real-time hardware data that extend ROG’s immersive design language beyond performance alone.”

Beyond the significant frills (i.e. the screen, the design), it looks like the Edition 20 raises itself above ‘ordinary’ Astrals by leveraging boosted power delivery opportunities. Standout claims for this new graphics card include the provision of a dual-input power subsystem, with a detachable GC‑HPWR adapter, for providing up to 800W to the graphics card. We ran a comparison vs the ‘regular’ Astral RTX 5090 on the official Asus site and saw that the Edition 20 version also had faster clocks (OC mode 2,750 MHz vs 2,467 MHz), and is a 4.7-slot (rather than 3.8 slot) design with a hidden BTF connector with a recommended 1,200W PSU companion.

Other specs of the ROG Astral GeForce RTX 5090 Edition 20, like the quad-fan design, vapor chamber, and liquid metal GPU compound, appear to be in line with previous ROG Astral RTX 5090 models.

ROG Crosshair X870E Edition 20

Asus also sought to emphasize the commemorative special edition ROG Crosshair X870E Edition 20. In summary, this flagship motherboard wears all the anniversary garb possible and is paired with a matching ROG Ryujin 360 Edition 20 AiO cooler.

Buyers of these coordinated ROG Black, ROG Red, and ROG Radiant Gold components will have an excellent foundation for a system build, with a slick unified commemorative design. Moreover, a system built upon this foundation will benefit from a robust 24+2+2 power-stage design with copper heatsinks, alongside support for up to nine M.2 slots to provide exceptional expandability. The AiO adds another in-system display option for builders with its Swivel Dual 6.67‑inch AMOLED LCD.

Lots more ROG Edition 20 gear

As indicated in the intro, the Edition 20 line doesn’t end there. Asus also launched the ROG Thor 3000W Titanium III Edition 20 PSU. Yes, it has a detachable magnetic OLED display and extender, too.

Asus has also lined up full pre-built gaming PCs for those who would like to honor its ROG Edition 20 anniversary. Go large with the ROG G1000 Edition 20, which features top-tier hardware support up to an RTX 5090 GPU and a Ryzen 9 9950X3D2 processor, housed in a tri-zone cooling architecture case with up to 420mm AiO. Alternatively, go compact with the Asus ROG NUC 16 Edition 20. This diminutive design also features up to GeForce RTX 5090 (laptop) graphics. However, it maxes out at a combined CPU + GPU TDP of 300W due to its size.

DIYers can also jump aboard the Edition 20 commemorative train with the ROG GR20 Edition 20 premium open-frame, modular PC case. It looks pretty handsome in the red, black, and gold color scheme and is primarily constructed from aluminum.

Outside the confines of the PC case, there is no shortage of new ROG Edition 20 products, with the same design language. You can get the ROG Swift OLED PG27AQWP-G Edition 20 gaming monitor, which runs at up to 720Hz. Anniversary input peripherals include the ROG Azoth Extreme Edition 20 keyboard and ROG Harpe II Extreme Edition 20 mouse. Those on a tight budget but who want to join the celebrations can buy a ROG Keycap Mystery Box Edition 20.

Other ROG Edition 20 products include the ROG XBOX Ally X20 Bundle, ROG Rapture GT-BE98 Pro Edition 20 router, the ROG Destrier Edition 20 gaming chair, ROG SLASH Hard-case Luggage Edition 20, ROG SLASH Backpack Edition 20, ROG Saga: In Search of Lapuntu Edition 20 board game, and ROG OMNI Edition 20 collectable figure.

Last and possibly least, Asus says there is a “limited edition software experience” ROG Armoury Crate Edition 20 to monitor and control your gear. It is pre-loaded on Edition 20 systems and will be available through 2026. We aren’t sure if this will be a theme for existing users of this software suite.

At Computex 2026, Intel is offering a few more details and updates for its next-generation Data Center GPU product, code-named Crescent Island. The Crescent Island GPU will be built on Intel's Xe3P GPU architecture. Intel says this architecture is "built for agentic AI," and it supports a broad range of potential data types, from FP4 for high-performance AI inference all the way up to FP64, potentially for scientific computing applications. Intel isn't providing any raw throughput specs at this stage of Crescent Island's development, so we can't make any guesses about its compute performance.

Crescent Island will be a PCI Express add-in card with a 350W power target, placing its power and thermal requirements close to products like Nvidia's RTX Pro 5000 Blackwell card. But Crescent Island's architecture is quite different from anything else on the market. It forgoes GDDR or HBM memory for LPDDR5X. Intel says its Crescent Island reference design will include 160GB of LPDDR5X, but that the chip is designed to allow partners the flexibility to build accelerators with up to 480GB of memory.

Recent leaks and past analysis have suggested that Crescent Island will take a wide-and-slow approach with LPDDR5X, potentially using a 640-bit bus connecting 20 LPDDR5X devices, to achieve these high capacities. Some basic math suggests that partners would need to employ 24GB LPDDR5X modules to fully realize that memory capacity, and those modules are already available from sources like Samsung. With 10.7 Gbps LPDDR5X, Crescent Island would offer 684 GB/s of memory bandwidth.

From a design standpoint, maximizing memory capacity while maintaining adequate bandwidth will help keep more AI data close to the GPU and require less data movement, potentially making Crescent Island a more efficient inference engine compared to GPUs built with lower-capacity GDDR devices.

Going with LPDDR5X also doesn't put pressure on valuable advanced packaging capacity or compete with higher-end accelerators for scarce HBM, making it potentially easier for Intel to produce these accelerators economically and in volume. There's no word on how or where the Crescent Island package itself will be fabricated, however.

Because Crescent Island is an air-cooled card with relatively modest power requirements, it's likely ready to drop into traditional 4U or 5U GPU servers, potentially making it appealing for companies trying to develop on-premise inferencing solutions. Eight of these accelerators with a full 480GB of RAM each would produce an impressively dense server with 3.8 TB of local GPU memory, allowing for massive models or swarms of smaller AI agents to reside within one box.

Of course, orchestrating AI work across multiple GPUs requires a capable software stack to manage the entire show, and Intel touts its oneAPI stack for use with Crescent Island. oneAPI is far less widely adopted than CUDA or ROCm, but those blazing the AI inference trail on Crescent Island will find software that the company calls "open, upstreamed, and Day 0 ready" for the product.

Intel describes Crescent Island as "coming soon" and has touted a second-half 2026 launch for the platform, so we'll presumably learn more about the product and the ecosystem building around it as we progress further into the year.

Instead of launching an entirely new product to go head-to-head with the best graphics cards on the market, AMD did the next best thing. The chipmaker has decided to make the Radeon RX 9070 GRE, once a China-exclusive SKU, available worldwide. Announced at Computex 2026, the Radeon RX 9070 GRE will hit global retail shelves on June 2 for $549.

The Radeon RX 9070 GRE features the same 4nm Navi 48 silicon found inside the Radeon RX 9070 and Radeon RX 9070 XT. The primary differentiator among these models is the number of enabled Compute Units (CUs), which directly affects their graphical performance. The Radeon RX 9070 and Radeon RX 9070 XT are equipped with 56 and 64 RDNA 4 CUs. In contrast, the Radeon RX 9070 GRE has only 48 CUs, which is 14% fewer than the Radeon RX 9070 and around 25% fewer than the Radeon RX 9070 XT.

If you want to look at it from another angle, AMD is employing a strategic approach to maximize silicon utilization. The Radeon RX 9070 recycles silicon that didn’t quite meet the stringent requirements to become a Radeon RX 9070 XT. In contrast, the Radeon RX 9070 GRE takes this process a step further by reusing silicon that doesn’t fully meet the specifications of the standard Radeon RX 9070.

The Radeon RX 9070 GRE’s memory subsystem further differentiates it from its more powerful siblings. It comes equipped with 12GB of GDDR6 memory, which is 25% less capacity than the Radeon RX 9070 and Radeon RX 9070 XT, each of which has 16GB.

In addition to its lower memory capacity, the Radeon RX 9070 GRE uses a narrower 192-bit memory interface compared to the wider buses on the Radeon RX 9070 and Radeon RX 9070 XT. The architectural design restricts the Radeon RX 9070 GRE’s maximum memory bandwidth to 432 GB/s, which is 32.5% lower than that of its counterparts. Despite these scaled-back specifications, the Radeon RX 9070 GRE retains a 220W TDP, which is identical to that of the standard Radeon RX 9070.

AMD asserts that the Radeon RX 9070 GRE delivers, on average, 21% higher gaming performance than the GeForce RTX 5060 Ti 16GB in 1440p (2560x1440) gaming scenarios. The chipmaker tested 40 different games across a high-end system powered by a Ryzen 7 9800X3D. Multiple independent reviews from Chinese technology news outlets have confirmed that the Radeon RX 9070 GRE is indeed faster than the GeForce RTX 5060 Ti 16GB, but they also show the RDNA 4 graphics card falling short of the GeForce RTX 5070.

The Radeon RX 9070 GRE will debut globally at $549, so it's essentially launching at the original MSRP as the Radeon RX 9070 and GeForce RTX 5070. However, the Radeon RX 9070 GRE offers lower performance than its counterparts. Thanks to the ongoing memory shortage, the Radeon RX 9070 and GeForce RTX 5070 typically start at $599. The price increases have created a gap in the market for a sub-$550 model, such as the Radeon RX 9070 GRE.

The Radeon RX 9070 GRE is AMD's tactical response to current market conditions that don't seem to be improving. The chipmaker is leveraging an existing SKU and offering it globally at a competitive price point. It's not a bad move if you look at it from that perspective. Stay tuned for our review with the latest updated drivers and benchmarks.

Earlier this week, we reported on the Green Team officially retiring the creaky Nvidia Control Panel (NVCP), with all its major settings adjustments claimed to have been ported to the Nvidia App. Throughout its tenure, this long-in-the-tooth piece of graphics settings software stuck resolutely to the classic non-themed Win32 controls style, but we know there will be holdouts and those who miss it for one reason or another. Thankfully, Nvidia has left an NVCP installer in the Microsoft Store, for now. Let’s look closer at whether it is worth a separate download in mid-2026.

To be clear, you will still need to download a modern Nvidia graphics driver to use the separately available NVCP. The familiar control panel software that is now available via the Microsoft Store is simply a controls access UI - one that has now been relegated to a secondary, optional choice.

For existing Nvidia graphics card users, you probably won’t have to go out of your way to grab the old NVCP from the Microsoft Store. It should normally persist from previous driver installs and updates, unless you opt for a ‘clean install’ from now on.

Possibly the primary reason you will want to keep a copy of the NVCP handy is the updated Nvidia Apps’ missing “professional features.” From my nosing at the information available, RTX Pro / Quadro features - things like offering adjustments to Mosaic, Sync, stereo, and a few pro‑workflow toggles - are yet to be migrated. So, modern GeForce gamers shouldn’t worry about hanging onto NVCP for functionality.

Even if you don’t need the handful of missing features in new vs old, some folks will want to keep using the NVCP due to familiarity with Nvidia’s older lightweight settings software.

We’d also be tempted to download or keep a shortcut to the NVCP handy in case upcoming software from Nvidia messes up the controls accessible in the Nvidia App. The Green Team’s software has come under fire for a string of buggy releases lately. In the likely scenario that Nvidia will ship an upcoming version of its Windows drivers with some feature-breaking wrinkles or crashing issues, the NVCP might be handy for fallback or troubleshooting.

An enthusiast who has a habit of browsing Facebook Marketplace for great bargains just stumbled upon a deal of a lifetime. According to u/Sycosisv’s Reddit post, they saw a nearby listing that offered an ROG Astral RTX 5080 GPU for just $500. Even though it wasn’t brand new, it’s still a massive discount from the current retail pricing of the white GPU, which is listed for $1,949.99 on Amazon, Newegg, and Micro Center.

5080 Marketplace grail $500 from r/PcBuild

The GPU seems to be in good condition based on the photos added to the listing, and the OP immediately jumped at the chance to get a powerful GPU for a fraction of the price. However, someone offered the seller $800 while they were in transit to pick up the GPU. The seller at first thought about backing out of the deal and offering $100 to the Redditor for their trouble. But, in the end, they decided to honor the original deal, and u/Sycosisv went home with a new-to-them RTX 5080. They’ve also already tested out the GPU and were happy to report that it worked perfectly.

The Nvidia RTX 5080 is one of the most powerful gaming GPUs you can buy at the moment, but its high price is making it hard for us to recommend it as one of the best graphics cards for gaming. But at $500, the RTX 5080 turns from an expensive piece of gear into a must-have for your gaming PC build. By comparison, $500 would only get you a Radeon RX 9060 XT 16GB, which has significantly less performance (but is still quite usable).

Prices for PC components have been rising uncontrollably in recent years. It started with the GPU shortage that began with the cryptocurrency mining boom and continued with the massive demand by AI hyperscalers. When GPU pricing started to get back down to “normal” levels, PC builders and enthusiasts were hit by the memory and storage chip crisis, resulting in a massive jump in prices of RAM sticks and SSDs. It also affected graphics cards, especially those that feature high amounts of VRAM, and we’re now hearing reports that CPUs are in short supply, too.

Because of this, many people are holding off on purchasing new PCs or upgrading the components of their current ones. But if you really need to get computer parts right now and can’t spare that much cash, buying used is the way to go if you know what you’re looking for.

After 20 years of service, Nvidia is officially retiring the Nvidia Control Panel for good and replacing it with the Nvidia App. According to the patch notes for Nvidia’s latest Game Ready driver, the control panel will no longer have new features added to it, and will no longer be bundled with the latest Game Ready and Studio drivers for GeForce GPUs. The only exception is RTX Pro GPUs, where Nvidia will keep supporting the control panel until all “professional features” have been migrated to the Nvidia App.

The Nvidia Control Panel will now live in a “maintenance mode” for the foreseeable future. Users who still want to use the Nvidia Control Panel won’t be forced to use outdated Nvidia drivers to keep the control panel installed. Future driver updates will not delete the control panel from a user's PC unless they are installed with the “clean install” method. Nvidia is also keeping the control panel downloadable through the Microsoft Store.

This news represents the accomplishment of Nvidia’s goal to replace the Control Panel and GeForce Experience applications with one application. Nvidia has been slowly migrating control panel features into the Nvidia App since it was unveiled in 2024. Migration of Nvidia control panel tools into the Nvidia App reached a tipping point in 2025 when Nvidia finally moved 3D Settings, Multi-Monitor support, and added offline support for system-level control panel and driver options, leaving almost no features left to migrate to the Nvidia App.

It still remains a mystery why Nvidia took so long to discontinue the control panel (or update it with a better-looking UI), but late is better than never. Likely, competition from AMD’s outgoing iteration of its Adrenalin control panel was what finally incentivized Nvidia to make its own counterpart.

For the vast majority of GeForce users, there is virtually no reason to use the Nvidia control panel anymore or keep it installed. The Nvidia App has all the features you need to tune and optimize games for GeForce GPUs. The app comes with driver-level tuning, but video recording, GPU monitoring, overclocking controls, automatic game optimization, and automated driver updates. That said, it's great to see Nvidia keeping the old control panel around for occasions where the Nvidia app might be buggy.

Chinese graphics card manufacturer Lisuan Tech has proven to the world that you don't need to release one of the best graphics cards to attain commercial success. Although the LX 7G100 graphics card fell short of performance expectations and did not compete directly with the latest generation models, the company nonetheless managed to sell out more than 30,000 preorders. The LX 7G100's remarkable success reflects consumers' appetite for alternatives in a market traditionally dominated by major players like Nvidia and AMD.

The LX 7G100 has an MSRP of $485 in China. With more than 30,000 units already spoken for through preorders, Lisuan Tech has generated over $14.55 million in advance sales. While the exact Bill of Materials (BOM) cost for the LX 7G100 remains undisclosed, the level of early success is a remarkable milestone for Lisuan Tech, a newcomer to the highly competitive graphics card market.

Lisuan Tech’s rapid rise to the spotlight has landed the company in the sixth position among big names on JD.com, China’s leading e-commerce platform for electronics, where it officially sells its products. The brand trails behind established industry giants like Asus, Colorful, Gigabyte, and MSI. The strong sales not only demonstrate effective marketing by Lisuan Tech but also reflect consumer curiosity and willingness to support emerging domestic brands, even if their products are not the highest-performing on the market.

Lisuan Tech often markets the LX 7G100 as a competitor to the GeForce RTX 4060. However, reviews have revealed that the LX 7G100 didn't hit the performance goal. Instead, it's more along the lines of a GeForce RTX 3060, one generation behind the target, and two generations behind the latest GeForce RTX 5060. The issue was that Lisuan Tech priced the LX 7G100 like a GeForce RTX 5060 Ti 16GB; however, it seems the high price didn't impede its early adoption at all.

Borrowing a page from Nvidia's playbook, Lisuan Tech launched a special Founders Edition of the LX 7G100, mirroring the approach that Nvidia takes with some of its mainstream GeForce RTX graphics cards. This exclusive batch was limited to just 1,000 LX 7G100 Founders Edition units. Each graphics card is individually numbered and personally signed by Lisuan Tech’s co-founder and co-CEO, Xuan Yifang. The initial batch sold out almost instantly, but the company has announced that a second batch of Founders Edition cards will be released and ready for shipping on June 18.

The LX 7G100 is only the beginning for Lisuan Tech, and June 18 will not only mark the highly anticipated restock of the Founders Edition but also serve as the official launch date for two new graphics cards: the LX Pro and the LX Ultra. The LX Pro specifically meets the demands of professional engineering applications, whereas the LX Ultra caters to cloud computing. Meanwhile, the LX Max, designed for creative professionals, has an uncertain launch date.

Lisuan Tech may be a startup in the graphics card market, but its leadership brings a wealth of experience and industry knowledge. Silicon Valley veterans Xuan Yifang, Kong Dehai, and Niu Yixin founded Lisuan Tech in 2021, all of whom had previously worked at the renowned but now-defunct S3 Graphics. It only took the company five years to put out a working graphics card that's competitive with models two generations behind. Everybody has to start from somewhere, and Lisuan Tech has a firm stepping stone.

At CES 2026, MSI unveiled a new lineup of power supplies under its MPG and MAG series. The 2026 MPG models are available in 1600W and 1300W variants and feature server-grade SiC MOSFETs designed to deliver a high level of stability and power efficiency. However, the standout addition is GPU Safeguard+, a new protection system aimed at preventing the overheating and melting issues associated with 12V-2x6 GPU power connectors.

Today, we will take a closer look at GPU Safeguard+. We will explore the PSU’s available software monitoring tools, explain how they work, and demonstrate how to use them. We will also evaluate the 12V-2x6 protection system in practice by simulating an improper cable connection to see how the safeguard mechanism responds. This should give us a decent indication of whether or not this feature works in practice, though naturally it would be impossible to test in all scenarios.

12VHPWR/12V-2x6 Connector Issues

12VHPWR/12V-2x6 Connector Issues

With the launch of the RTX 40-series in 2022, high-end GPUs adopted the new 12VHPWR power connector. The goal was to simplify cable management by replacing 3x8-pin configurations with a single connector. Under normal operating conditions, this setup is reliable. However, several factors can lead to an improper connection, potentially causing overheating issues.

One of the main issues with the implementation of this connector is the lack of load balancing. If the cable is not properly connected, excessive current can be routed through a single wire instead of being distributed evenly. This can lead to overheating and, in severe cases, melting of the cable or connector, potentially damaging the GPU, the power supply, or both.

What can cause a faulty connection?

At one point, improper cable insertion by the user was believed to be the primary cause of these failures. While this can still contribute to the problem, the updated 12V-2x6 connector specification introduced several changes intended to reduce the likelihood of user error. In addition, manufacturers implemented features such as colored connector housings to make it easier to verify that the cable is fully seated.

Many reported cases have also been linked to the use of 12VHPWR and 12V-2x6 adapter cables rather than native PSU cables designed specifically for those connectors.

The issue has continued to persist, with reports of damage affecting GPUs ranging from the RTX 5090 to the RTX 5070, as well as models of the 9070 XT that utilize the 12V-2x6 connector.

This is where GPU Safeguard+ comes in.

What is GPU Safeguard+?

What is GPU Safeguard+?

GPU Safeguard+ is a safety mechanism designed to combat the aforementioned issues with the 12V-2x6 connector. It does this through multiple phases.

First, the PSU detects a fault, such as a current imbalance between an abnormally uneven current distribution from the power supply’s 12V-2x6 connector or a sudden current spike that exceeds the safe load range.

After a fault has been detected, the PSU warns the user of the anomaly through a built-in buzzer or through various software tools, which we will discuss later. The buzzer continues to beep for 3 minutes after the fault has been detected.

If the current returns to normal, the buzzer continues to beep, but the PC remains powered on. The user must force shutdown the PC and reconnect or change the cable. The issue is recorded in a log automatically.

If the current is still abnormal, the buzzer continues to beep, but the power to the GPU is cut, and the screen goes black. The user must force shutdown the PC and reconnect or change the cable. The issue is recorded in a log automatically.

The best course of action is for the user to turn the PC off immediately once they hear the buzzer beeping. According to MSI, the three minutes between the first beep and the PSU cutting power to the GPU if the current remains abnormal are meant to allow the user to save their work before shutting down, or to take action on the user’s behalf if they are not around when the fault is detected.

Software Monitoring Tools

Software Monitoring Tools

The MSI MPG Ai1600TS power supply (along with the 1300W variant) comes with a USB-C Port and a USB-C to 9-pin cable that is plugged into the USB-C port in the PSU and the 9-pin USB connector on the motherboard. This allows the user to monitor PSU performance through various metrics in MSI Center, MSI Afterburner, and HWiNFO.

To access the PSU monitoring in MSI Center, go to the Features tab and select ‘power supply.’ This will take you to a page where you can view metrics such as total system output wattage, PSU efficiency, PSU temperature, and most importantly, per-pin current distribution for the 12v-2x6 connector. There is also a real-time dashboard where you can see the same info on several graphs, and also save this info as CSV for further analysis.

To enable PSU monitoring in MSI Afterburner, make sure you are using version 4.6.7 of Afterburner. Open up the settings in Afterburner and head to the Monitoring tab. Press the ellipsis next to “Active hardware monitoring graphs,” and you will get a pop-out window with available plugins. Scroll down and activate the PSU.dll plugin. Hit OK, and once you are back in the Monitoring tab, you will see several PSU metrics available, which you can add to the on-screen display.

You can also set alerts with customized values for these metrics. By selecting the ‘PSU 12VHPWR1 alarm’ or ‘PSU 12VHPWR2 alarm’, you can enable GPU Safeguard+ for the 12v-2x6 connectors. If a fault is detected, you will get a pop-up warning you of abnormal current. MSI Afterburner will then reduce the GPU power limit to 75% and will advise you to shut the PC down and check your connection.

Above, you can see the MSI Afterburner PSU metrics in action during gameplay. We tested in Alan Wake 2 and Cyberpunk 2077 at native 4K with path tracing and maxed out settings. Under these conditions, total system power draw occasionally exceeded 800W.

PSU efficiency remained high at 94%, and the cooling fan never needed to engage during testing. Out of the box, the PSU ships with a relatively relaxed fan curve, though it can be customized through MSI Center. By default, the fan only begins spinning once the PSU consistently reaches roughly half of its 1600W rated capacity. The brief power spikes observed during testing were not sustained enough to trigger active cooling, with PSU temperatures remaining in the low 50°C range throughout. This keeps the PSU nice and quiet during operation.

HWiNFO v8.42 added monitoring support for the MSI MPG Ai1600TS and MSI MPG Ai1300TS power supplies. Similar to MSI Center and MSI Afterburner, you can setup alerts for abnormal current distribution.

Testing GPU Safeguard+

Testing GPU Safeguard+

In order to test GPU Safeguard+ functionality, we simulated an improper connection of the 12v-2x6 cable into an RTX 5090. Do be aware that we cannot test every possible scenario, so view our results as a general indicator of how the tech would ideally work.

Test system

• MSI GeForce RTX 5090 Vanguard SOC
• AMD Ryzen 7 9800X3D
• 64GB (2x32GB) G.SKILL Flare X5 DDR5 @6200 MHz CL30
• Crucial T700 Gen5 SSD
• ASUS ROG STRIX B850-F Gaming WiFi
• Corsair Nautilus 360 RS AIO Cooler
• HAGS enabled
• Windows 11 25H2 (Build 26200.8328)
• NVIDIA Driver 596.49

As you can see above, once we ran Furmark to apply 600W to the 5090, it did not take MSI Afterburner long to warn us of a fault. In addition to the pop-up warning, an audible alert sounded, and Afterburner automatically lowered the GPU power limit. MSI Center also detected a current imbalance, which also triggered a series of pop-up warnings, as did HWiNFO.

The alerts continued for three minutes before the PSU cut power to the GPU, causing the display to go black. At that point, we performed a forced shutdown of the system and properly reseated the cable. After powering the PC back on with the connector fully inserted, the system returned to normal operation.

Of the three software monitoring tools we tested, MSI Afterburner offers the most comprehensive monitoring and safety mechanisms. Not only does it issue a pop-up warning and an audible alert, but it also immediately limits the power to the GPU. It also allows you to conveniently monitor various metrics in real-time during gameplay.

Is Your GPU Safe?

Is Your GPU Safe?

The system worked well for us overall. The solution implemented by MSI is more comprehensive than simply having an improved cable that enlarges wire load capacity and reduces cable temperature. GPU Safeguard+ offers active protection that not only warns the user of an anomaly, but actually takes action to mitigate the risk of damage. Based on our testing, it works exactly as intended, but do be aware that we cannot simulate all possible failure scenarios or setups.

If we had one nitpick, it would be the three minutes between fault detection and the PSU finally cutting power to the GPU. In most scenarios, this is unlikely to cause any damage. Most users will also be close enough to their PC to hear the audible alerts and shut the PC down manually long before the protection kicks in. Still, we’d prefer a faster response for extra peace of mind. MSI says that the three-minute window is meant to allow users ample time to save their work before shutting down, but one to two minutes would also be plenty of time.

GPU Safeguard+ is an innovative protection feature that will hopefully become the standard on all high-end PSUs. Several other manufacturers have already announced similar technologies, and we hope to see every premium PSU adopt robust GPU protection in the near future. With the 12V-2x6 connector likely here to stay, features like this will be essential – especially for owners of power hungry GPUs.

Today, we will take a look at Advanced Shader Delivery (ASD) – a new gaming feature aimed at improving the overall user experience by reducing load times dramatically and improving 1% low FPS. We tested six games, measuring up to a 95% improvement in game loading times and solid improvements in 1% Low FPS in some titles. We will explain the issues that it aims to fix, we will go into detail about its functionality, and then we will test it in several games with on vs off comparisons.

Shader compilation stutter has been the bane of every PC gamer’s existence for a long time. Imagine finally sitting down after school or work to play a highly anticipated new release, only to spend several minutes waiting for shaders to precompile. Worse yet, even after that lengthy process, some shaders may still compile during gameplay, causing noticeable stuttering. First impressions matter, and technical issues like these can quickly sour the experience.

Pipeline State Objects (PSOs) define how input data is interpreted and rendered by the hardware when submitting work to the graphics card. PSO creation is also where shader compilation and related stalls happen. Modern games can contain such a massive number of PSOs that engines are unable to fully enumerate them ahead of time. Developers have introduced various mitigation techniques, but these are ultimately compromises that can still miss certain shaders during pre-compilation. In theory, allowing every player to locally precompile every possible shader permutation could eliminate these issues, but in large modern titles, that process could potentially take hours.

That is why Microsoft has introduced Advanced Shader Delivery.

What is Advanced Shader Delivery?

What is Advanced Shader Delivery?

Advanced Shader delivery is a feature that aims to eliminate long shader pre-compilation and shader compilation-related stuttering in games by distributing precompiled shaders when downloading a game — those shaders are downloaded just like other parts of the game. In other words, faster initial load times and smoother performance when first playing a game after installation, a game update, or a driver update.

The idea is that developers will programmatically capture and generate a new type of asset from pipeline state object inputs, called a State Object Database (SODB.) An SODB is a SQLite3 database that contains the shaders, as well as the structure for how to group them into PSOs.

The next step after collecting the SODBs is to precompile shaders using offline compilers. Compilation happens outside of the game and does not require a GPU. The SODB is converted into a precompiled shader output that can target a wide range of hardware without needing that hardware to be physically present. This output is called a precompiled shader database (PSDB), which can be registered for a game and distributed by the Xbox store alongside the game to supplement the shader cache.

After installing a game with Advanced Shader Delivery support, the Xbox store downloads an update containing the precompiled shaders. As you can see below, the ‘Shaders’ folder will contain an SODB and PSDB file after this update.

When a game runs for the first time, all the shaders it needs will already be available. The game will see this and will skip the compilation step on the gaming device. If a device requires a driver update, the shaders will be updated automatically.

Theoretically, if developers programmatically capture SODBs with every required shader represented in the PSDB – and the system functions correctly – a game could achieve a 100% cache hit rate on its first run. This would not only dramatically reduce initial load times but could also entirely eliminate shader compilation stutter during gameplay.

Microsoft recently expanded the public preview for Advanced Shader Delivery with support for dedicated and integrated AMD GPUs on desktops. However, not all system configurations currently support Advanced Shader Delivery, even if you own an AMD GPU.

The device requirements are as follows:

• OS: Windows 11 24H2 or higher
• Xbox Gaming Services: 37.113.11003.0 or higher (Microsoft Store > Library > Update Gaming Services)
• Xbox Insider Hub: Open Xbox Insider Hub > Select Previews > PC Gaming Preview
• GPU: AMD RDNA 3, RDNA 3.5, RDNA 4 architectures
• Driver: Adrenalin 26.5.2 or higher

Advanced Shader Delivery is currently only supported on the Xbox store, but it is coming to other storefronts in the future.

NVIDIA and Intel GPUs are expected to receive support in the near future, although Intel has a similar technology on its graphics cards called “Precompiled Shader Distribution.”

If Advanced Shader Delivery is working, ‘Precompiled shaders installed’ will appear in the bottom left corner of the launch window.

With all that said, let’s see how it performs in practice.

Load Time and Performance Tested

Load Time and Performance Tested

Advanced Shader Delivery is supported in a little over 30 games. It is available in every game that initially supported the feature on the ROG Ally, plus the recently released Forza Horizon 6.

We selected six games known for lengthy shader pre-compilation times, shader compilation-related stuttering, or both.

The on vs off comparisons were run with the exact same settings for each individual game, but we did not use maximum settings. We used custom settings to get a playable experience on the 9070 XT.

There is no official way to disable Advanced Shader Delivery, but we managed to disable it by deleting the files in the Shaders folder of each game and then disconnecting the system from the internet so that the Xbox store will not download those files upon launching the game.

Each test was performed after a fresh driver install.

Since ASD is only supported on AMD GPUs, we used a Radeon RX 9070 XT for our testing.

Test system

• PowerColor Red Devil RX 9070 XT
• Ryzen 7 9800X3D
• 64GB (2x32GB) G.SKILL Flare X5 DDR5 @6200 MHz CL30
• Crucial T700 Gen5 SSD
• ASUS ROG STRIX B850-F Gaming WiFi
• Corsair Nautilus 360 RS AIO Cooler
• HAGS enabled
• Windows 11 25H2 (Build 26200.8457)
• Adrenalin 26.5.2
• NVIDIA driver 596.49

Forza Horizon 6

Forza recently launched with Advanced Shader Delivery support. Both the Forza Horizon and Forza Motorsport series are known for having lengthy pre-compilation steps. As such, it is no surprise that ASD dramatically reduces the initial game load time.

From 48 seconds down to just 2 seconds. That’s a whopping 96% improvement in load time.

Not only did we see a reduction in load time, but gameplay performance was also smoother.

During the first stage of the prologue, there is a nasty shader compilation stutter on the very first run of the game with ASD disabled. With ASD enabled, that stutter is no longer present.

Below you can see a comparison between our test system paired with an RTX 5090 vs an RX 9070 XT with ASD enabled. This is not a comparison between the two GPUs, as the 5090 is far more powerful, which is evident from the average framerate. Indeed, NVIDIA GPUs will also support this feature in the near future. Rather, it serves as an illustration that highlights how shader compilation stutter can bring even the most powerful system to its knees.

Both of the runs shown above were performed with the same settings. With the 5090 (top) plugged into our system, we experienced a massive stutter on the first run, that brings the 1% low to 3 FPS at this particular point of the scene. Meanwhile, the 9070 XT (bottom) cruises past this point with a smooth frametime on the very first run.

The Outer Worlds 2

The Outer Worlds 2 has a very long shader pre-compilation step that takes almost 3 minutes, so it is a very good candidate for our testing.

From 2 minutes and 52 seconds down to just 9 seconds. That’s a 95% improvement, but more crucially, it cuts down your waiting time by an incredible 2 minutes and 43 seconds.

We did not experience any shader compilation stutter in our run with ASD disabled, so there was no improvement in performance here.

Ninja Gaiden 4

Ninja Gaiden 4 does not have a pre-compilation step with ASD disabled, so there is no improvement in load time.

However, we did experience a couple of minor stutters with ASD disabled in our first run that were no longer there in the second run. These are shader compilation-related stutters.

The game was mostly smooth during our runs, but those two minor dips were enough to give ASD about a 10% edge in 1% lows. This is important, because those dips came during combat.

Avowed

Avowed is another game that has a lengthy pre-compilation process of almost 3 minutes.

This is a 78% improvement in initial load time. While not as dramatic as what we saw in Forza Horizon 6 and The Outer Worlds, it still cuts your initial waiting time by 2 minutes and 16 seconds.

There were no shader compilation stutters here with ASD on or off, so the performance remains the same.

Hogwarts Legacy

Hogwarts Legacy’s pre-compilation is not as long as others we have seen, but it does take over a minute.

We see a 56% reduction in load time. Quite a bit lower than the previous games we tested, but it is nothing to sneeze at.

Performance remains the same whether you enable or disable ASD as we encountered no shader compilation related stuttering.

Silent Hill f

Silent Hill f does not have a pre-compilation phase, so there is no improvement in initial load time.

However, the game does have some rather significant shader compilation stutters in the town area at the beginning of the game, as seen below.

We were hoping that ASD would entirely eliminate those stutters, but unfortunately, that is not the case.

Unlike Forza Horizon 6 and Ninja Gaiden 4, Silent Hill f’s shader stutters are not eliminated by ASD, and performance remains the same.

It's unclear whether this stems from an API limitation or the developer failing to supply all shaders to the SODB. Either way, it serves as an example that – while the technology is genuinely impressive – it still needs some work to completely eliminate shader compilation stutter.

The Verdict

Our testing shows that Advanced Shader Delivery can significantly improve the player experience. A gamer’s first impression is critical, and nothing sours it faster than technical issues. Being able to load right into a game without waiting several minutes and having smooth performance unencumbered by intrusive shader compilation stutter should be the standard.

Advanced Shader Delivery delivered this experience in most of the titles we tested. However, there is still work to be done – whether by Microsoft, game developers, or both – to make the feature consistently reliable across all games.

Pictures of the PCB of Intel’s upcoming Crescent Island data center GPU, announced last year, have surfaced. The images, which come by way of @yuuki_ans on X, show the front and back of the Crescent Island PCB and reveal the layout of the board's components, including the GPU, VRAM, and power delivery system.

The PCB shots confirm that Intel has opted to go with a single-GPU setup for Crescent Island, rather than a dual-GPU setup. A vast majority of the PCB’s real estate is consumed by a massive GPU socket in the middle, taking up the width of almost the entire PCIe x16 slot below.

There are pads for twelve LPDDR5X modules to the top, left, and right of the GPU socket and an additional eight on the back of the PCB, totaling 20. This confirms the GPU will use 32GB (8 GB) modules, the highest capacity modules out there for LPDDR5X currently on the market. The power delivery system consists of a single 16-pin 12V-2x6 power connector on the right and 19 power phases.

Crescent Island is the codename for Intel’s next-generation data center GPU powered by its Xe3P GPU architecture. Its most noticeable trait is the inclusion of LPDDR5X memory over HBM, which should make Crescent Island the world’s first AI GPU to use LPDDR5X. This will give Crescent Island significantly inferior memory bandwidth, but undoubtedly, Intel is opting to use slower memory to save on production costs, thanks to the memory shortage. (HBM memory sits at the center of the outgoing memory shortage crisis, as it's the hardest to secure for GPU manufacturers .)

Assuming the GPU comes with a 640-bit memory interface and uses 10.7Gbps memory, maximum memory bandwidth will be well under 1TB/s — a far cry from Nvidia’s older H200 GPUs, which have nearly 5TB/s of memory bandwidth. Memory bandwidth is one of the most important aspects of an AI GPU's performance and how quickly it can execute machine learning workloads, so it will be interesting to see how much LPDDR5X impacts Crescent Island’s performance compared to HBM-equipped cards.

Intel’s new AI-GPU will be targeted at air-cooled servers and will be a competitor to existing Nvidia and AMD cards in the same target demographic, such as the recently released AMD MI350P with 144GB of HBM3E and the Nvidia H200 NVL with 141GB of HBM3. Intel plans to start sampling Crescent Island to its customers in the second half of 2026.

Lisuan Tech’s LX 7G100, China’s first real attempt at a serious gaming graphics card, falls significantly short of competing with the best graphics cards from Intel, AMD, or Nvidia. Chinese reviewer 潮玩客 recently put the LX 7G100 through extensive testing, and the results showed that the homegrown Chinese graphics card is nowhere near the performance of the GeForce RTX 4060, despite bold marketing claims. What's concerning, at least for Chinese consumers, is that Lisuan Tech has priced the LX 7G100 at around $485, roughly equivalent to the lowest price for a GeForce RTX 5060 Ti 16GB.

The reviewer tested the LX 7G100 on a variety of modern games at 1080p (1920x1080) resolution. They adjusted the image settings for each game, ranging from low to medium presets and, when possible, to high, to gauge the graphics card’s upper limits. The reviewer also enabled FSR 3 and frame-generation features, when supported, to improve frame rates and provide a smoother gaming experience.

To guarantee that the graphics card was the only variable affecting performance, the reviewer assembled a high-end test system. The setup featured AMD’s Ryzen 7 9800X3D processor installed on an MSI MPG X870E Edge Ti WiFi motherboard. The system also had 32GB (2x16GB) of Biwin Black Opal DW100 DDR5-6000 C28 memory and a Biwin Black Opal X570 2TB PCIe 5.0 SSD. By selecting premium components across the board, the reviewer ensured that the LX 7G100’s performance could be evaluated without bottlenecks from other hardware limitations.

Lisuan Tech LX 7G100 Benchmarks*

*The results are from 潮玩客's Bilibili video. The first value corresponds to the average frames per second (FPS), whereas the second value represents the 1% Low FPS, a metric for measuring the slowest 1% of frames observed during the benchmark.

A significant performance gap separated the GeForce RTX 4060 and the LX 7G100. The former was between 20% to 70% faster than the latter. Logically, the LX 7G100 also substantially trailed behind competitors, such as the Arc B580 and Radeon RX 6600 XT. If we look at the bright side, the LX 7G100 was able to run various titles at very high frame rates, including Cyberpunk 2077, Horizon Zero Dawn, Marvel’s Spider-Man: Remake, and Hogwarts Legacy. However, the Chinese homebred graphics card also struggled in many titles, such as Forza Horizon 5, Assassin’s Creed: Shadows, and Red Dead Redemption 2, failing to maintain consistent frame rates above 60 FPS.

Beyond the performance, the biggest win for the LX 7G100 is its out-of-the-box compatibility and driver maturity, both of which have been weak points for Chinese graphics cards. The LX 7G100, unlike other offerings, launched with compatibility with a wide range of modern AAA games. It just goes to show that Lisuan Tech didn't obtain Microsoft's WHQL certification for the LX 7G100 in vain.

Perhaps the most glaring issue facing the LX 7G100 is its price, which significantly undermines its competitiveness in the current graphics card market. Lisuan Tech sells the LX 7G100 for $485, a price tag that will turn many heads. In comparison, the GeForce RTX 5060 Ti 16GB, which is leagues above the LX 7G100, starts at $489 in this overblown-price market. Even consumers motivated by national pride will struggle to justify purchasing the LX 7G100, especially given the availability of better, more affordable alternatives. Technological progress is important, but crafting a value proposition that aligns with consumer expectations and the current competitive market is equally important.