Hardware enthusiasts, server administrators, and all regular readers of this site will be well aware of the ongoing "RAMpocalypse," the memory and storage shortage affecting nearly every market and raising prices across the board in the tech sector. If you were hoping for relief, don't hold your breath; at the International Supercomputing Conference this past week, Lenovo reportedly said "it will never be like it was last year." Underlining the point, one of Lenovo's presentation slides was titled "The 5 Step RAMaggeddon Survival Guide."

That comes to us by way of our German friends over at ComputerBase, who note that "never" was said with a smirk, thus implying that it wasn't meant to be taken literally. Instead, the message from Lenovo is that memory prices were unusually low in early 2025, and it will be a long time before we see comparatively low prices on RAM, flash memory, and other components, as the #1 worldwide PC OEM expects AI demand to continue growing.

According to ComputerBase's report from ISC 2026, Lenovo's broader message is that the economics of the memory industry have fundamentally changed. The company reportedly argued that even as significant new manufacturing capacity comes online beginning around 2028, demand from AI infrastructure is expected to absorb much of that additional output, preventing DRAM and NAND prices from returning to the lows seen over the past two years.

The report points to SK hynix's recently announced plans to triple its memory production capacity by 2034 as supporting evidence. Lenovo's reasoning is straightforward: the notoriously profit-hungry memory manufacturers would be unlikely to invest so heavily in expanding production if they expected a return to the razor-thin margins and oversupply that characterized parts of the market in early 2025.

In case you needed extra evidence for its argument, Lenovo also suggested that memory capacity itself is becoming an increasingly important consideration when designing and purchasing servers. While vendors have traditionally advertised the maximum supported memory capacity of new platforms, actually populating those DIMM slots has become far more expensive. New dual-socket servers are on the way next year with 16 memory channels per processor, meaning that even a relatively modest configuration can require around 1 TB of installed memory to fully utilize the available bandwidth.

Lenovo is far from the only company predicting a prolonged memory crunch, although the industry's incentives are worth keeping in mind. Micron recently told investors it expects supply to remain constrained through at least 2027, with only gradual improvement beginning in 2028, while SK hynix has warned the shortage could persist until around 2030 as AI infrastructure continues absorbing wafer capacity. Those forecasts are backed by multi-year supply agreements worth roughly $100 billion that Micron has already signed with customers, underscoring how seriously hyperscalers are treating long-term memory availability.

Even companies that traditionally wield enormous purchasing power are feeling the squeeze. Apple reportedly has sought permission from the U.S. government to source DRAM from Chinese memory maker CXMT, a Pentagon-blacklisted company, illustrating just how valuable additional memory supply has become as prices continue to climb. At the same time, memory vendors are enjoying some of the strongest pricing power (and profit margins) they've seen in years, giving them little incentive to accelerate a return to the boom-and-bust pricing cycles that once defined the DRAM market.

Ironically, one consequence of the ongoing memory shortage is that HBM is becoming more economically attractive relative to conventional system memory. DRAM manufacturers have redirected significant production capacity toward higher-margin HBM for AI accelerators, reducing the supply of commodity DDR5 and LPDDR5 while demand for both remains elevated. As a result, the premium for HBM-backed computing has narrowed, not because HBM has become inexpensive, but because traditional system memory has become dramatically more expensive. Hyperscalers were going to buy the GPUs anyway, so maximizing their utilization to reduce DDR5 requirements suddenly becomes an attractive proposition.

That shift helps explain Lenovo's suggestion that GPU-accelerated computing may now make more financial sense for some workloads. If an application can keep much of its working set in GPU-attached HBM, it may require significantly less DDR5 installed in the host system. With system DRAM now representing a much larger share of overall server cost than it did just a year ago, reducing memory capacity requirements can materially lower the price of deploying large-scale infrastructure.

Obviously, we don't know whether Lenovo's long-term outlook will prove accurate, but memory pricing has historically been cyclical, with periods of oversupply often followed by sharp corrections. With hyperscalers continuing to pour billions into AI infrastructure and memory vendors increasingly prioritizing high-margin enterprise products, the company believes the unusually inexpensive DRAM and NAND prices of 2024 and early 2025 may prove to have been an anomaly.

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.

AI GPU maker Nvidia just announced a “hotter than a hot tub” liquid cooling system that it says will cut water and electricity use. According to the company, this new solution will run coolant — composed of 75% water and 25% propylene glycol — at 113 degrees F (45 deg C). By comparison, the water in hot tubs hovers at 100 to 104 degrees F (38 to 40 deg C). This feels counterintuitive, but the company says that the “cool” water is enough to handle the heat generated by Nvidia’s Rubin chips and exit the system at 131 degrees F (55 deg C).

Traditional water-cooling methods, especially those that use chillers, often account for nearly 40% of a data center’s power consumption. Aside from that, these systems must often deal with water loss through evaporation. On the other hand, air-cooled facilities also use a considerable amount of electricity, plus they also generate noise pollution. On the other hand, Nvidia says that this new solution uses a lot fewer resources because of its higher base temperature.

Since 113 degrees F is often higher than ambient temperature, data centers can simply rely on outdoor dry coolers to expel the heat to the environment. This is also a closed-loop system; Nvidia claims an up to 100% reduction in water consumption — it’s “filled once and runs closed for the life of the facility.” This solution is most effective in regions with cooler climates, but it should still be effective in warmer areas as long as the ambient temperature is below 113 degrees F.

Data centers that face occasional temperature swings that exceed this limit may still be required to turn on their chillers. Nevertheless, this should still reduce resource consumption, as it only needs to run them a few times per year. Aside from that, this should also allow these systems to run more efficiently, as the chillers don’t have to work as hard to hit the target temperature. It’s estimated that increasing a chiller plant’s target temperature by 1.8 degrees F (1 degree C) would reduce electricity costs by 4%. This means that data centers would save significantly on power consumption if they set their chiller units to the 70 to 75 degrees F (21 to 24 degrees C) that traditional chillers run, according to Vertiv, to the 113 degrees F (45 degrees C) that Nvidia recommends for its Rubin chips.

This solution addresses several of the issues that many local governments raised that led to the delay of more than 75 data centers earlier this year. However, it will likely take time for this cooling system to roll out to new and existing projects, so we expect the delays and resistance to continue until Nvidia’s liquid cooling system gains wider adoption. Furthermore, this only addresses the water use of the data center itself — the GPU servers themselves still require massive amounts of electricity.

Unfortunately, most of the power used by data centers, at least in the United States, comes from fossil fuel power plants, which themselves consume a lot of water. Developments that aren’t tied to the grid and get their electricity from natural gas turbines may not need as much water, but residents are concerned about the pollution they generate. Still, this new cooling solution is a step in the right direction to help make AI more sustainable.

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.

Servers running x86 processors from AMD and Intel used to rule the market, both unit and money-wise, less than a decade ago, but fast forward to today, Arm-based machines command well over 45% of the server market, according to data released by IDC. While technically x86 machines still control 52% of the market in terms of revenue, the real winner is a different category altogether: GPU- and ASIC/FPGA-accelerated systems, which generated over 70% of the global server revenue in the first quarter of 2026.

Server market reaches $122.6 billion in a single quarter, Dell leads the game

IDC estimates that the global server market generated a record $122.6 billion in revenue in the first quarter of 2026, up 30.4% year-over-year, as spending on AI infrastructure remained particularly strong.

Sales of ODM Direct servers — custom machines ordered by hyperscalers that run merchant or custom silicon — accounted for 50.2% of the revenue (down from 64.1% in Q1 2025) and reached $61.53 billion, up modest 2.1% year-over-year*. By contrast, sales of standard servers from well-known brands grew at a much higher pace, which suggests that branded vendors such as Dell, HPE, Supermicro, and others won a larger portion of AI infrastructure deployments than they did a year earlier. That was probably made possible by accelerating enterprise AI deployment and sovereign AI projects, which tend to buy machines from branded vendors, as well as hyperscalers increasingly turning to well-known suppliers for AI hardware.

When it comes to vendor rankings, Dell remained the largest server supplier by revenue with a 16.5% share of the market after its revenue surged 244.1% year-over-year to $20.3 billion, which was driven by exceptionally strong AI server demand. Supermicro remained in second place with $9.3 billion in revenue and a growth of 128.9%.

Lenovo ranked third with $5.6 billion and 36.5% growth, while IEIT Systems (which is a part of the sanctioned Inspur Group) dropped to fourth after revenue declined 7.0% to $4.0 billion. HPE was No.5 with $3.7 billion in revenue, up 17.2%. Other vendors — from Asus to Atos and from ASRock Rack to Gigabyte — commanded 14.8% of the market with $18.11 billion in revenue, up from 13% and $12.21 billion in the same quarter a year ago.

Arm-based machines rapidly gain revenue share

As AI servers dominated the market in Q1 2026, systems with various types of accelerators accounted for over 70% of the revenue. However, the rise of Arm-powered machines is the elephant in the room that is hard to miss, as it represents a tectonic shift in the whole market, both to the Arm instruction set architecture (ISA) in general and custom-built Arm CPUs designed by hyperscalers.

Non-x86 platforms generated $58.7 billion in revenue, a 107.6% increase year-over-year, which lifted their share of the market to 47.9%. Most of the non-x86 systems are Arm-based AI machines (think Nvidia's NVL72) as well as systems running custom CPUs, AWS, Google, and Microsoft, just to name a few. Still, also keep in mind IBM Z mainframes and IBM Power Systems (including storage) that use CPUs featuring proprietary non-x86 and non-Arm ISAs and which still generate $1 billion or more in revenue. IDC claims that Arm-based machines accounted for more than 95% of non-x86 revenue, so it is safe to say that Arm-based machines commanded over 45% of server revenues in Q1 2026.

One of the reasons why Arm-based machines now command a huge chunk of the server market is because they are used inside such systems as Nvidia's NVL72 'Blackwell' that sell for up to $6.5 million per unit. Each NVL72 rack-scale solution carries 36 compute trays with two Blackwell GPUs and one Grace CPU per unit, so while unit-wise each we are only talking about 36 processors, dollar-wise one NVL72 machine is as expensive as 928 entry-level 1P server (for $7,000) for cloud or edge applications or 433 higher-end 2P servers (for $15,000) for cloud or virtualization applications.

Given the fact that Nvidia will continue bundling its own Arm-based Vera CPUs with NVL72 'Vera Rubin' machines that will be more expensive than their Blackwell ancestors, we will not be surprised that Arm-based machines will account for well over 50% of the server market revenue in the second half of this year or in 2027. Also, keep in mind that Nvidia plans to sell server racks featuring only Vera CPUs for agentic AI applications, which will further drive sales of Arm-based machines.

Accelerated servers: The real winner

Since AI servers dominate server sales, it is not surprising that sales of accelerated servers are increasing. Systems equipped with GPUs produced $68.9 billion in revenue during the quarter (up 24.8% compared to the same period a year earlier) and accounted for 56.2% of all server sales. Servers based on other accelerator types, including custom ASICs and FPGAs, expanded to $17.7 billion, up 122.1% YoY. As a result, accelerated servers earned $86.6 billion in Q1 2026, which is around 70.6% of all server revenue.

X86 servers remain unit volume champions, but suffer from shortages

In contrast, x86 server revenue declined 2.9% to $63.9 billion, though IDC attributes this weakness to supply limitations rather than deteriorating demand. The market research firm claims that the industry's primary constraint is no longer customer appetite for general-purpose servers, but rather the availability of key components, including CPUs, DRAM, NAND memory, and hard drives.

Without any doubt, x86 servers remain working horses for the industry. In fact, many of them use accelerators, including ASICs, FPGAs, and GPUs, as they are used for a wide range of workloads, including AI, supercomputing, simulations, encryption, video transcoding, and many more.

AMD and Intel shipped nearly 20 million EPYC and Xeon SP processors for data center systems in 2025, according to Dean McCarron, the head and principal analyst at Mercury Research. He believes Nvidia is on track to ship four million Grace and Vera CPUs this year, which is considerably lower compared to shipments of AMD and Intel. It is hard to estimate how many custom Arm-based CPUs are deployed by AWS, Alibaba, Google, and Microsoft, but it is safe to say that we are talking millions of CPUs here; otherwise, the companies would not be able to justify development and production of custom silicon.

From a volume perspective, x86 servers remain the most popular machines, and it will probably take some time before ARM can challenge x86 in mainstream general-purpose servers. Nonetheless, it is safe to say that Arm-based data center CPUs are catching up with x86 parts in terms of volumes.

Summary

The global server market hit a record $122.6 billion in the first quarter of 2026 as AI infrastructure spending continued. Accelerated systems powered by GPUs, custom ASICs, and FPGAs generated more than 70% of server revenue, while Arm-based platforms — including Nvidia's Grace Blackwell as well as custom CPUs from Arm, Google, and Microsoft — captured nearly half of the market.

Although x86 servers based on AMD EPYC and Intel Xeon processors remain dominant in shipment volumes, supply shortages of CPUs, memory, and storage components constrained revenue growth, which further enabled Arm-powered AI-optimized systems to gain share. But while at 20 million data center processors per year, x86 volumes are untouchable for Arm today, things may change in the coming years. Nvidia is on track to ship 4 million CPUs in 2026, and other developers of custom Arm-based CPUs are certainly not standing still.

*There is one significant difference with IDC's 'ODM Direct' classification. IDC classifies revenue according to which company invoices the customer, not necessarily who manufactures the hardware. As a result, while many AI servers are built by ODMs like Compal, Foxconn, or Quanta, they are sold under brands like Dell or HPE. As a result, while the latter get more business from enterprises or sovereign AI deployments, this does not mean that big ODMs are losing business; they are actually gaining it, as the appetites of hyperscalers like AWS, Google, Meta, or Microsoft are not going anywhere, just demand from new entrants emerges.

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.

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.

Nvidia has showcased agentic robots that can teach themselves high-precision and dexterous tasks in the real world. As part of the demo reel for this ENPIRE technology, we see a room full of robots do things like pick up and slot a graphics card in a motherboard, as well as sort metal pins in a container, and manipulate and correctly cut zipties. Jim Fan, Nvidia’s Director of AI & Distinguished Scientist, said that this demo shows researchers can “enable AutoResearch in the physical world for the first time!”

Fan explains that the ENPIRE project gave 8 Codex agents a fleet of robots, an allocation of GPUs, and a generous token budget. Then the agents were given a task to solve as quickly as possible, without making mistakes. Once instructed, “The robot fleet starts to come alive: they learn to look for visual clues, reset the scene, practice novel skills, tinker with control stack, read papers online, debate, reflect, get stuck, and try again directly on the hardware,” explains the Stanford-based scientist. “All we did is giving Codex an API to the world of atoms, and the rest is emergence.”

We were most interested to see a robot “installing GPUs all by itself.” In the brief recording of this particular PC DIY task, you can see one robot arm select and pass a graphics card to another with a motherboard in front of it. The second arm then carefully positions the PCIe slot of the card to align it with the motherboard slot, gently descends, and pushes it into place. It seesawed a bit on insertion, but we guess it would have been fine. Other AutoResearch projects the robots were set to do included organizing fine pins, plus tying and cutting zipties.

In the associated ENPIRE: Agentic Robot Policy Self-Improvement in the Real World research paper, you can learn more about the techniques behind this demo. You can also see the comparison test results when different coding agents were used, including Codex with GPT-5.5, Claude Code with Opus 4.7, and Kimi Code with Kimi K2.6. The researchers also tested scaling up the robot fleet, concluding that “eight robots exploring in parallel solves the task significantly faster than fewer ones.” Fan joked that the goal is to train up the robots, then everyone goes on holiday, “and Jensen wouldn't even notice ;)”

While hyperscalers rush toward expansion amid the swelling demand for AI data centers, Marvell last week shared its vision for an optical interconnect solution that can theoretically pool resources between discrete data centers across thousands of kilometers.

Optical interconnections are steadily being deployed across the industry, over both short and long-distance connections, and we're going to be seeing much more in the future, according to Matt Murphy, Chief Executive at Marvell, speaking at Computex 2026.

"Imagine future data centers, a globally optically interconnected data infrastructure," Murphy said. "These rigid boundaries we have today, and the systems we have, they begin to disappear. Compute can now be pooled, memory can be pooled, and infrastructure can be composed dynamically at scale."

Constrained by distance

Murphy says that workloads no longer fit within one data center, which is why hyperscale cloud service providers increasingly need to build entire campuses consisting of multiple data centers connected by high-speed links, as clusters are becoming larger than a single data center.

Today, connecting multiple data centers within a single campus is not easy or cheap, but relatively straightforward. However, Marvell envisions that in the future it will need to connect data centers that are located at considerable distances from one another.

This is why Marvell is working on coherent optics and long-haul scale across optical networking technologies, which will connect data centers separated by thousands of kilometers. Marvell already has products which enable such connectivity today, including the Colorz 1600 1.6 Tb/s coherent optical solution based on a 2nm DSP, which targets inter-data-center connectivity and will sample later this year.

In addition, Marvell says it will offer the Ara 1.6 Tb/s family of interconnect solutions for data centers (with 3nm DSPs) as well as the Teralynx T100 102.4 Tb/s Ethernet switch, which supports 512 ports running at 200 Gb/s or 64 ports running at 1.6 Tb/s.

Murphy argues that today's architectures are constrained by distance because of copper interconnects: CPUs sit near memory because latency matters, GPUs sit near memory because bandwidth matters. As a result, workloads must be partitioned according to those physical limits. The head of Marvell claims that once optical interconnects penetrate scale-up interconnects, scale-up domains will not be limited by copper cable lengths, and those constraints will begin to disappear.

Nowadays, scale-up AI solutions, such as Nvidia's NVL72, are connected using copper wires, but scale-out connections tend to use optical interconnects. Once the number of AI accelerators within scale-up systems increases, they will also have to move to optical links, according to Marvell. This means that virtually all data center-grade interconnections will become optical, which might inspire hardware developers to reconsider the architecture of data centers.

Pooling resources

Murphy presented a rather interesting vision: firstly, optics will expand scale-up domains from 72 or 144 accelerators to 1,000 or more. But after that, optical connectivity will enter servers themselves. This will enable developers to disaggregate CPUs, accelerators (Marvell calls them XPUs), and memory into separate pools as distance will no longer matter, enabling better configurability and utilization.

"It is a data center without distance, where compute, memory, networking, and photonics operate as one unified system, where millions of resources across the data center can work together as if they were one machine," the head of Marvell said.

Keeping in mind that hyperscalers deploy hardware worth billions of dollars, even a 10% higher utilization will save a lot of money, and companies like Nvidia are clearly paying attention.

"In today's systems, the ratio of CPU and XPU or GPU is fixed, so these ratios have to be defined at the time the system is built and deployed, but no two workloads require exactly the same ratio," Murphy stressed. "Imagine a completely disaggregated architecture, XPUs in one system, memory in another, generic CPUs in another."

Today, companies buy something like an NVL72 system and get a fixed ratio of CPUs, GPUs, and memory, which may be efficient for certain workloads and inefficient for others. In the future, operators will be able to assemble a virtual machine from shared pools of systems, allowing for customization and flexibility, based on the type of workload. If a workload needs more memory than compute, operators often have to buy additional GPUs just to get the extra HBM, but they may just get memory in the future if Marvell's vision comes to pass.

"Once we decompose the system into separate pools of compute, memory, and they are all optically interconnected, we can then compose dedicated systems on the fly, which are then optimized wherever the workload is," Murphy said. "For the first time, architects can begin designing AI systems around the needs of the model, not around the limits of the interconnect."

One detail

While Marvell has the know-how to interconnect data centers across thousands of kilometers and technologies that enable pooled data centers, these visions do not necessarily intersect. Data centers located thousands of kilometers away cannot share resources — a 1,000 km round-trip takes light 10ms — which makes such long-distance resource sharing inefficient from a latency point of view.

However, Marvell's technologies enable hyperscale CSPs to synchronize AI campuses, access distributed storage, replicate data, and perform other operations that do not depend on latency. Meanwhile, the synchronization of AI campuses on different continents in a matter of hours could be a killer app for hyperscalers.

China's Supreme People's Court on Friday upheld an injunction prohibiting Infineon from selling the disputed gallium nitride (GaN) products in mainland China, the final word in a patent case brought by Suzhou-based rival Innoscience, SCMP reports. Both companies sit on Nvidia’s approved supplier list for 800V AI-rack power delivery, and the judgment caps a year of litigation that has handed each side a win in different jurisdictions.

The court upheld a May 27th judgment from the Suzhou Intermediate People's Court that found Infineon infringed two Innoscience invention patents, ordering it to stop selling, offering, and importing the products and to pay 10 million yuan (roughly $1.48 million) in damages.

In May, the full U.S. International Trade Commission affirmed an earlier determination that Innoscience infringed an Infineon patent and ordered import and sales bans, pending a 60-day presidential review period. Innoscience disputes this the impact of this, stating that the same ITC determination cleared its redesigned current products and that its U.S. shipments continue uninterrupted. A German case at the Munich District Court I added a third front, where judges found infringement by Innoscience in 2025, with further patent and utility-model trials scheduled for this month.

"This decision once again highlights the robustness of Infineon's intellectual property," said Johannes Schoiswohl, senior vice president and head of Infineon's GaN Systems business line, in a May statement on the ITC ruling.

GaN is the underlying material that’s powering Nvidia’s shift away from 54V rack distribution toward an 800 VDC architecture for racks pushing past 200kW toward a megawatt. Raising rack voltage to 800V cuts current and copper across the conversion chain, and GaN's faster switching shrinks the power stages between the rack and the GPU core. Both Infineon and Innoscience appear on Nvidia's silicon-provider roster for that transition, alongside Texas Instruments, Navitas, and onsemi.

Innoscience led the global GaN power-device market in 2024 at 29.9% according to TrendForce data, with Infineon fourth at 10.3%. Infineon counters with its 300mm GaN-on-silicon manufacturing and around 450 GaN patent families against Innoscience’s 8-inch fabs in Suzhou and Zhuhai. Mainland China, Hong Kong, and Taiwan together accounted for 38% of Infineon's fiscal 2025 revenue, per its annual report.

Innoscience's Hong Kong-listed shares rose 16.6% on Monday on the back of the ruling, while Shanghai-listed compound-semiconductor makers Silan Microelectronics and Sanan Optoelectronics each hit the 10% daily limit, and power-chip maker China Resources Microelectronics climbed about 13%.

Nvidia has told Chinese clients that its Arm-based Vera server CPUs could be available as soon as August and that orders can be placed now, Reuters reports, citing three sources familiar with the matter. Meanwhile, shipments of H200 AI GPUs to China remain frozen, months after CEO Jensen Huang said Nvidia’s market share in the country had effectively fallen to zero.

This August timeline runs in sync with what was said at GTC Taipei during Computex, when Nvidia indicated that Vera systems would reach customers through system builders and cloud partners starting this fall. Telling Chinese buyers they can have silicon in August, during a global server CPU shortage, suggests they’re sitting near the front of the allocation queue for a product line Nvidia expects to generate $20 billion in revenue by the end of its fiscal year in late January.

According to the report, Chinese cloud companies are already testing more than 300 Vera servers, and at least one major cloud provider plans to place an order. Initial deployments will be restricted to those companies' overseas data centers, one of the sources said.

If this goes ahead, Vera will reach Chinese buyers where Nvidia’s GPUs can’t. Server CPUs face far lighter U.S. export restrictions than the accelerators that underpin Nvidia's data center business, and the company's recent history in China shows that Washington is no longer the only obstacle. The U.S. licensed roughly 10 Chinese firms to buy the H200, but not a single unit has been delivered because Chinese officials, intent on nurturing domestic chipmakers, withheld approval on their side.

That dynamic helps to explain why the deployment of Vera CPUs will be restricted to overseas data centers: Chinese cloud providers want the hardware, but putting U.S. silicon into domestic data centers will obviously invite scrutiny and potential action from Beijing officials.

Vera began life as the CPU half of the Vera Rubin superchip, first shown at last year’s GTC event. Nvidia broke it out as a standalone product at GTC San Jose this March, launching it alongside a rack design that packs in 256 liquid-cooled Vera CPUs and sustains more than 22,500 concurrent CPU environments. Then, at Computex, Nvidia said the chip had entered full production, claiming 1.8 times faster task completion than x86 processors on agentic workloads. Its predecessor, Grace, has shipped nearly 2.5 million units to date.

Meanwhile, server CPUs are being tightly squeezed by the shift of AI workloads from training toward inference and agentic execution. Agentic AI leans heavily on host processors for tool calls, code execution, and data handling, and CPU demand has outrun supply as a result of the agentic explosion.

Intel has quoted Chinese customers lead times of up to six months, while AMD has said that the global CPU market is tight, with demand outpacing its forecasts and supply constraints expected to persist.

Last week at Computex 2026, Wiwynn showed off one of the industry's first Nvidia SCADA (SCaled Accelerated Data Access) servers. Devices such as this are built to handle the extreme data demands of AI data center-focused inference and training workloads, which operate with massive models and datasets, therefore requiring large, fast, and connected devices to serve as the backbone for complex, high-throughput tasks that AI workloads depend upon.

Wiwynn's SCADA server packs up to 96 liquid-cooled solid-state drives and therefore offers petabytes of storage space using currently available E3.S drives, and massive I/O performance. The machine is based on Nvidia's Vera CPU, four RTX Pro 6000 Blackwell graphics cards, four PCIe 6.x switches, and four ConnectX-9 SuperNIC cards.

Storage architecture for AI

Modern AI inference and training workloads often deal with massive datasets that exceed the memory capacity of an AI accelerator's onboard memory, which is why AI applications need to access rapid storage.

While AI training is typically dominated by large sequential transfers, AI inference workloads such as vector search, retrieval-augmented generation (RAG), graph analytics, and KV-cache retrieval often rely on fine-grained random accesses (that frequently involve data blocks smaller than 4KB) with extreme parallelism, as the system deals with thousands of GPU threads.

Traditional CPU-centric I/O cannot efficiently handle such workloads and creates bottlenecks because the CPU must issue commands, manage requests, and control data transfers. Even in advanced solutions like GPUDirect Storage, which allows data to be transferred directly from SSDs to GPUs, the CPU still owns the control path and can become a bottleneck.

The SCADA platform, previewed in late 2025, is designed to allow GPUs access to very large datasets directly and efficiently without involving a central processor. This is impossible to do on conventional machines, as SCADA lets GPUs themselves initiate and control storage I/O operations and the data path.

SCADA runs on PCIe 6.x hardware from partners like Broadcom and Micron, and customers can now build their own SCADA machines with commercially available components. However, SCADA servers have not yet been popularized. In fact, Wiwynn seems to be among the first server makers to even showcase a SCADA server.

Wiwynn's SCADA server

Wiwynn's SCADA server can indeed be a panacea for the problem that is AI storage. It supports up to 96 liquid-cooled E3.S SSDs, meaning that the drives will perform as expected even under high loads. When equipped with 96 30.72 TB Micron 9650 Pro drives with a PCIe 6.0 interface, the server can store 2.949 PB of data.

On the performance side of things, Wiwynn claims an aggregated random read speed of 528 million 4K IOPS, as well as sequential read/write speeds limited by the performance of PCIe switches and/or network cards rather than the drives themselves. As manufacturers expand the capacities and performance of their E3.S SSDs, servers like the one Wiwynn demonstrated at Computex will gain capacity and performance as well.

Architecturally, Wiwynn's SCADA server is an Nvidia MGX rack-compliant system in an 6RU form-actor that has a maximum power consumption of 9 kW. All key components of the machine are liquid cooled, the drives are cooled by six separate cold plate modules that are integrated into the system's liquid cooling loop so to inject coolant to all SSDs simultaneously in order to ensure consistent performance of all drives.

Positioning

Nvidia clearly positions SCADA as tier 3.5 storage servers located behind local SSDs, but ahead of tier 4 remote storage servers that often rely on hard drives.

SCADA machines are meant to feed data to actual compute servers at a very high data transfer rate in small blocks, so its RTX 6000 Pro GPUs act more like very sophisticated storage processors that initiate and handle storage transactions, millions of small storage requests on behalf of AI applications, and pass them to the compute server via the ConnectX-9 cards, while the SSDs and their controllers still perform the actual storage functions.

In general, SCADA is a part of Nvidia's Storage Next vision, which is a collection of technologies aimed to make storage behave more like an extension of GPU memory for AI workloads.

For obvious reasons, Wiwynn does not disclose pricing of its SCADA storage server as it depends on multiple factors, including pricing of 3D NAND, DRAM, and SSDs, not to mention purchase volumes. In any case, an Nvidia Vera-based server equipped with four RTX Pro 6000 Blackwell graphics cards will not be cheap.

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.

Nvidia and SK hynix have inked a multi-year collaboration agreement under which the companies will co-develop next-generation memory technologies for Nvidia's upcoming platforms, and SK hynix will supply them to Nvidia. The deal is designed to ensure that Nvidia will get the memory it needs from a prominent supplier and will guarantee that SK hynix will be able to sell its output in a predictable manner.

The key part of the agreement is indeed the co-development of advanced memory products designed for Nvidia's future platforms. Currently, Nvidia uses HBM, LPDDR5X, DDR5, and 3D NAND memory in various systems, so going forward, SK hynix will develop its new memory with Nvidia in mind. The joint press release says nothing about customization of memory for Nvidia, and while we cannot exclude such a possibility, it looks like the companies will continue to co-develop industry-standard solutions, but will ensure that they are compatible with Nvidia's processors.

In addition, the agreement is intended to address the increasingly long lead times and massive capital expenditures required for the production of advanced types of memory. The two companies will coordinate roadmaps over multiple years. Nvidia will gain greater visibility into future memory availability, while SK hynix secures a guaranteed role in Nvidia's next-generation platforms (i.e., guaranteed demand).

The initial part of the cooperation covers memory destined for NVIDIA Vera Rubin AI systems (HBM4, LPDDR5X, 3D NAND), standalone Vera processors (LPDDR5X), RTX Spark-powered personal computers (LPDDR5X, 3D NAND), and Jetson Thor robotic computing systems (LPDDR5X, 3D NAND).

The deal also extends to semiconductor research and design. SK hynix is deploying Nvidia's CUDA-X libraries to speed up complex chip development workloads, such as technology computer-aided design (TCAD) and computational lithography (CuLitho). In addition, the memory maker is adopting Nvidia PhysicsNeMo to accelerate proprietary simulation software as well as AI-driven physics models used during semiconductor development. In addition, the companies see an opportunity to expand these capabilities into general electronic design automation (EDA) and simulation ecosystems and potentially create tighter relationships within the industry.

Last but not least, SK hynix is creating digital twins of its semiconductor fabs using Nvidia Omniverse and OpenUSD technologies. These virtual facilities enable engineers to model production lines, test changes, and optimize operations before making adjustments in real fabs. The company also plans to use Nvidia's cuOpt and Metropolis platforms to improve the movement of autonomous robots and other factory equipment. In the future, SK hynix aims to connect these digital twins with existing manufacturing software and AI systems and enable them to analyze fab data, automate routine tasks, and help make production decisions.

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.

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.

When not being spotted at night markets or meeting crowds of adoring fans, the hardware industry’s biggest celebrity, Nvidia CEO Jensen Huang, spent most of his time at Computex this week making the case that computing as we know it is collapsing into one repeatable pattern built for AI agents; a blueprint that now runs across the cloud, the PC, the car, and the robot.

"There's a new computing pattern," the Nvidia CEO told reporters at a press gaggle the day after his GTC Taipei keynote, describing an agent architecture he calls a harness that orchestrates reasoning, memory, and tool use the same way whether it sits in a data center or a laptop.

He tied that claim to every product Nvidia detailed at the show, from the Vera data-center CPU now in full production to RTX Spark, its first Windows PC platform, shipping in laptops this fall.

One pattern, every machine

Huang told the room that he repeats the same keynote structure on purpose. "Every time I give you a keynote, it's like Top Gun 17, and it's exactly the same architecture," he said, "because I want you to know that the future of computing is this." The pattern begins with training and inference in the cloud and pushes outward to everything else: "Every edge device will become autonomous. Every edge device will have agentic systems."

He ran that blueprint through self-driving cars, humanoid robots, Nokia base stations, and imaging satellites, casting each as the same agent profile on different hardware. Curiously, the self-driving car got quite a bit of airtime, with Huang describing Nvidia's Alpamayo driving stack as a system that reasons in language rather than reacting to images, one that could read a "skill file" and watch a tutorial video to operate unfamiliar machinery the way a person would. "That's how autonomous vehicles are going to work in the future," he said. "It's essentially that agentic computing pattern with a physical AI model."

A CPU that generates tokens, not cores

Vera, on the data center side, is an 88-core Arm processor that Nvidia is now in full production with, pitching it as a chip built for agents rather than human users. "We built Vera for agents to use," Huang said. "Until six months ago, there were no agents, so that's the definition of a $0 billion market."

A hyperscale CPU piles on cores because humans lease them by the hundred, where an agent, Huang argued, "doesn't want to rent the CPU core, the agent wants to generate tokens." That pushed Nvidia toward single-thread speed and memory bandwidth over core count, and Huang claimed Vera offers the largest step up in single-threaded performance he has seen "in 25 years." His reasoning ties back to latency: "Humans are more patient than agents. Agents, they're working at nanosecond scale, not second scale."

Nvidia claims 1.8 times faster task completion than x86 and a 1.5 times instructions-per-clock gain over its Grace predecessor, with a 256-chip liquid-cooled Vera rack it says reaches six times the throughput of a conventional CPU rack. The chip ships on the back of nearly 2.5 million Grace units sold, and Anthropic, OpenAI, xAI, ByteDance, CoreWeave, and Oracle are named as early customers. CFO Colette Kress told investors on Nvidia's latest earnings call that the company sees "nearly $20 billion in total CPU revenue this year".

Phoronix's first public Vera benchmarks in May measured it roughly 10% ahead of AMD's 64-core EPYC 9575F and about 55% ahead of Intel's 128-core Xeon 6980P across selected Linux workloads. Nvidia ran those tests on pre-production silicon at its own headquarters, limited them to workloads it considers relevant, and, by Phoronix's account, switched off CPU power and frequency monitoring for the session.

Reinventing the PC after 40 years

As for RTX Spark, Huang says that it’s the first real rethink of the PC in four decades. "We have an opportunity after 40 years to go reinvent it for the age of AI," he said, predicting the machine shifts "from your PC being a tool to now really your PC being your system." He pushed even further: "Your laptop is going to be your R2-D2."

The top RTX Spark part, internally N1X, pairs a 20-core Arm CPU built by MediaTek (10 Cortex-X925 performance cores and 10 Cortex-A725 efficiency cores) with a Blackwell GPU carrying 6,144 CUDA cores, up to 128GB of LPDDR5X unified memory, and a 600 GB/s NVLink-C2C link, all on TSMC's 3nm node. Huang justified these specs with the same impatience he applied to Vera, arguing that an agent driving the machine won’t wait, so the software it touches, from Adobe to Blender, "cannot be slow."

The platform is launching in a market that Qualcomm had effectively dominated until its Windows on Arm exclusivity with Microsoft lapsed. Fall 2026 laptops are confirmed from Microsoft, Dell, HP, ASUS, Lenovo, and MSI, with Acer and Gigabyte to follow, and Nvidia says anti-cheat engines, including Easy Anti-Cheat and Denuvo, run natively on the chip. Asked why Nvidia would enter a low-margin business it has steered clear of for years, Huang said, "We don't really have to choose. The real question is, can we make a contribution?"

Vera's 88 cores are Nvidia's own custom Olympus design, its first ground-up server core since the Denver and Carmel projects, while RTX Spark's 20 cores are Arm's off-the-shelf Cortex reference designs licensed through MediaTek, one of them already a generation old. Huang's "same pattern everywhere" runs, at the silicon level, on two different CPUs.

When asked whether the Olympus cores would come to Windows PCs, Huang declined to commit. "Our preference is to use off-the-shelf cores whenever we can, because Arm also builds good cores," he said, adding that Olympus was pushed toward single-thread speed in a way standard many-core Arm parts weren’t: "We wanted to push single-threaded performance as far as we could push it." The first PC chip using Nvidia's own cores isn’t expected until 2028. Meanwhile, Morgan Stanley estimates Vera at around $5,000 per socket inside a vertically integrated rack.

What about memory?

DRAM contract prices have climbed sharply through 2026 as makers divert wafers to high-bandwidth memory, and Nvidia remains short of supply even as it locks in capacity, by Huang's own account: "We have enough supply for very robust growth. However, we are supply constrained."

"One of the best ways to improve memory use is to use extremely, extremely low precision," Huang said, pointing to NVFP4, Nvidia's 4-bit floating-point format that scales between four, eight, 16, and 32 bits and roughly doubles the parameters that fit in a given memory pool, the trick that lets RTX Spark hold larger models in its 128GB. He paired it with neural texture compression that cuts game texture memory by up to eight times in Nvidia's demos. At SK hynix's booth during the show, Huang signed an HBM4E wafer with the words "Please Make More."

Update: After publication, Microsoft provided us with the following statement: “Microsoft Surface Laptop Ultra is not targeting a 110w sustained TDP. Final power will be disclosed closer to availability.” [Emphasis ours]. The original article continues below.

The consumer tech industry is still absorbing the aftershocks of Nvidia's seismic RTX Spark announcements this week at Computex 2026, and there are still many questions around the platform regarding performance, power, and battery life.

One of those questions is the thermal design power (TDP) of the RTX Spark Superchip that's powering the high-end laptops revealed this week. That power budget is everything in a thermally constrained chassis that has to dynamically share power between the CPU and GPU.

A higher power budget in such a system generally translates into higher performance (albeit not necessarily linearly). And if you know the power budget of one platform, you can better reason about its performance compared to other chips with a similar TDP.

Tom's Hardware's Paul Alcorn and I attended a series of lightning-round hands-on sessions with Nvidia's core laptop partners this week, and among other standard questions, we asked representatives from those companies what the power and thermal budgets of their systems were. Unsurprisingly, those partners generally declined to answer.

But Microsoft's reps freely shared that the Surface Laptop Ultra, at least, is designed around a TDP of 110 W for the RTX Spark Superchip.

That figure makes sense, given our experience with the compact DGX Spark mini-PC. That system has an SoC TDP of 140 W, so it's no huge surprise that even the relatively large and well-ventilated Surface Laptop Ultra is designed to dissipate around 80% of that power at peak load.

As a laptop, the Surface also has other components it needs to power, including a screen and any peripherals connected to its USB ports, so extra headroom is required for that purpose. (Other OEMs did disclose that they were including 140W chargers with their devices, so consider that an interesting data point to this end.)

In any event, the enterprising reader might be tempted to extrapolate from our past DGX Spark performance testing and conclude that 20% lower power equals 20% lower performance. But we'd caution against that reasoning.

Chip power and delivered performance generally have a nonlinear relationship past a certain point, and we have no idea what the behavior of the voltage-and-frequency-scaling curve is for the RTX Spark Superchip in the range we're discussing.

We also don't know the full power and thermal management behavior of the RTX Spark Superchip. Modern laptop SoCs (and all chips, really) opportunistically take full advantage of all available thermal and power headroom at the start of a task, so they'll boost up close to the limits of their TDPs while the system is cool before dialing back clock speeds and power to achieve a steady state that avoids overwhelming the system's heatsink and fans. It's not clear how quickly and to what extent the RTX Spark has to clock down to operate within those limits for long-running tasks.

And in a mobile device that has to share power between the CPU and GPU, performance is also going to be highly dependent on the character of the workload. A game, for example, is going to heavily stress the GPU but might not fully occupy the CPU at the same time, while a highly parallel CPU-dependent task like code compilation might fully load the CPU cores without involving the GPU much at all. If you have a (rare) workload that loads down both of those functional units at once, overall performance is likely to fall further than with one that only demands one type of processing resource or the other.

It's also worth remembering that every laptop is different, and power envelopes are carefully tuned for each chassis to best balance design constraints between SoC temperatures, skin temperatures, and noise, among other factors.

All that said, from what we've seen, Microsoft's 110W target seems likely to be typical of the 15"-16" laptops that other OEMs plan to introduce. Logically, it's also likely that we might see lower power budgets for thinner or smaller systems.

But the short version of all this is that there's a lot we still don't know about the RTX Spark platform, and we're still a long way from the launch of the laptops with this chip inside. We expect to learn more about this platform, its design targets, and its behavior in the coming months as we lead up to Nvidia's projected fall launch. Stay tuned.

Regardless of your opinion of Nvidia’s RTX Spark, there’s no doubt that it’s the most consequential consumer announcement to come out of Computex 2026. Unlike Intel, which told Tom’s Hardware it’s handling the launch with “a healthy dose of paranoia,” AMD’s executives are confident that its Strix Halo and upcoming Gorgon Halo products will compete well with the N1X and N1 under the RTX Spark brand.

“I’m really excited that Nvidia has joined the game. You know, we were the only game in town for almost two years now, and the large local memory is becoming super critical in the agentic AI [workloads],” said AMD’s Rahul Tikoo, senior vice president and general manager of AMD’s client business. “I'm actually happy to see Nvidia join the race for these great products.”

AMD, of course, believes that Strix Halo and eventually Gorgon Halo are positioned well against RTX Spark devices. In a separate discussion, AMD’s Andrej Zdravkovic, chief software officer, said, “At this point in time… I mean, you’re just wrong if you don’t get a Strix Halo notebook,” when speaking on the choice of machine for developers. As the software lead at AMD, however, Zdravkovic is distanced from the hardware. Tikoo had more direct comments on the hardware comparison.

“I’m actually curious about what [Nvidia has] done, but when I look at their specs, their specs are 128 gigs of local memory. We’ve done it on Strix Halo. Their specs are a 20-core CPU. We have a 16-core / 32-thread CPU in here,” Tikoo said. “So, if you just compare the specs, I don’t see… now, Gorgon Halo, which is coming out in Q3, is going to be a better product.”

Hardware is only one part of the battle, which has become clear as AMD continues to push its way into AI infrastructure. Tom’s Hardware asked Zdravkovic about the so-called ‘CUDA moat’ that Nvidia has built for itself, and how AMD plans to address that as it rolls out updates for its own ROCm stack.

“If you asked me the same question like three years ago, I would be, yeah, that really matters. I think that matters less at this point,” Zdravkovic told Tom’s Hardware. “Nvidia has created a phenomenal ecosystem around CUDA, and our advantage is that ROCm is, from a developer point of view, extremely easy to use… the shift from one to another is easy, and the only challenge is if your application ends up using some of the specific commands that Nvidia has and we don’t, and the other way around.”

The posturing against Nvidia is expected, both on the hardware and software side, but Tikoo also pointed out that Nvidia’s entrance into the consumer PC market has downstream benefits for AMD.

“Nvidia has brought validity into the space… I think it’s also going to help the ecosystem move forward faster, right, because Nvidia and [AMD] are the two big players in this space, and both of us now being in this space not only drives the cloud ecosystem, it drives the AI ecosystem in the PC on Windows, and so we’re excited about that,” Tikoo said.

We’re still a few months away before we can see what material impact RTX Spark has on the broader industry, though we expect the initial rollout to be more muted than Nvidia’s keynote suggests. Although Nvidia plans to sell configurations of RTX Spark down as low as 16 GB of memory, the initial configuration will top out at 128 GB and likely demand several thousand dollars. At least initially, it’s a product that looks like it will appeal to a relatively small (but growing) market of AI developers, not dissimilar to Strix Halo.

AMD’s upcoming Gorgon Halo chips are largely a refresh of Strix Halo, leveraging the same Zen 5 cores for the CPU and RDNA 3.5 cores for the GPU, though with a bump up to 192 GB of unified memory. At least from the memory perspective, which continues to be an important specification for AI workloads, AMD has the edge. But, as we’re all well aware, there’s far more that goes into a platform (especially a consumer platform that costs several thousand dollars) than memory alone.

It will be interesting to see how the dynamic between Nvidia and AMD plays out, as we expect Gorgon Halo and RTX Spark to arrive in the same window; AMD says Q3 for Gorgon Halo, while Nvidia has simply said “fall” for RTX Spark.

This week at Computex 2026, we saw Nvidia reveal its RTX Spark, and last month, AMD detailed its Ryzen AI Max 400 "Gorgon Halo" lineup, a refresh of the Strix Halo APUs that lifts supported unified memory to 192GB and allows up to 160GB of that pool to be addressed as VRAM. AMD describes the flagship Ryzen AI Max+ PRO 495 as the first x86 client processor able to run a 300-billion-parameter language model locally, pitching the platform for use cases that need to keep multiple AI agents resident in memory at once.

The market for Gorgon Halo will likely be directly shared with other chips, such as Nvidia's RTX Spark, which debuted at Computex 2026. RTX Spark is also positioned as an on-device agentic computing device. With local AI computing demanding lots of on-device RAM, it poses a difficult issue for device vendors.

DRAM contract prices are forecast to climb another 58% to 63% this quarter, on top of the record 90% to 95% jump TrendForce recorded in Q1, which also saw Nvidia raise the price of its DGX Spark desktop from $3,999 to $4,699, citing memory supply. So, what happens to the dream of accessible local AI compute?

DRAM supply squeeze

The local AI PC has become a category defined by how much memory it carries, and it’s scaling that memory up at a time when memory has never cost more. AMD's three Gorgon Halo SKUs reuse the same Zen 5 cores, RDNA 3.5 graphics, and XDNA 2 NPU as the existing Ryzen AI Max 300 parts, with the Max+ PRO 495 gaining a 100 MHz boost-clock bump to 5.2 GHz, a 40-compute-unit Radeon 8065S, and a 55 TOPS NPU.

Memory capacity has been increased 50% from the 128GB ceiling on Strix Halo, with a leaked PassMark entry putting the 192GB figure as eight 24GB SK hynix LPDDR5X packages on an HP test board, though AMD hasn’t yet confirmed this. Partner systems from Asus, HP, and Lenovo are due in the third quarter of 2026.

It’s all well and good that Nvidia and AMD are releasing machines like the RTX Spark and the Gorgon Halo line-up. However, Samsung, SK hynix, and Micron have all shifted the bulk of their wafer capacity toward high-bandwidth memory for AI accelerators because HBM carries far higher margins than commodity DRAM, and the conventional memory supply has tightened as a direct result of this. HP told investors in February that memory now accounts for roughly 35% of the cost of building a PC, up from 15% to 18% a quarter earlier.

SK Group chairman Chey Tae-won, speaking at Computex 2026 on the show’s official opening day, repeated his position that the shortage will run through 2030, despite the company's intention to double wafer capacity within the next five years. New fabs from all three makers are under construction, but none will reach volume production before late 2027 at the earliest, and most forecasts now predict a structurally higher price floor that persists even after the acute shortage eases.

The 192GB in a Gorgon Halo box, the 128GB in an RTX Spark or DGX Spark, and the LPDDR5X soldered into every AI laptop announced at Computex all come off wafers the memory makers would otherwise sell as HBM. That’s why Nvidia raised the DGX Spark by $700 in February without changing a single spec, and why component makers have begun passing memory costs through directly. One vendor has even taken an extremely on-the-nose approach of adding a flat memory surcharge to every purchase, and in some cases, smaller buyers are now quoted prices that change by the hour.

Bandwidth caps inference speed

A single pool of 192GB would enable an APU to hold a model that would otherwise require a multi-GPU server. While it doesn’t make the model run quickly, dense language model inference reads close to the full set of active weights from memory for every token generated, so generation speed is governed by memory bandwidth divided by the per-token weight footprint, not by idle memory.

Gorgon Halo keeps the same 256-bit LPDDR5X-8000 interface as Strix Halo, which tops out around 256 GB/s in theory and which independent testers have measured closer to 212 GB/s on the GPU. By comparison, the Apple M3 Ultra that AMD and Nvidia are chasing on capacity is rated at 819 GB/s, and an RTX 5090 moves data at 1,792 GB/s.

This gap explains why a dense 70-billion-parameter model fully resident on a Strix Halo iGPU lands in the low single digits of tokens per second, regardless of how much headroom the memory pool has. Our own Corsair AI Workstation 300 review found that Nvidia's slightly higher-bandwidth GB10 pulled ahead of Strix Halo as context length grew, for exactly this reason.

Capacity matters most for mixture-of-experts models, which activate only a fraction of their parameters per token and run far faster than their total size suggests, and for long-context agentic workloads, where it’s KVcache rather than model weights that consume memory. It’s these use cases that AMD’s agentic pitch points at, with leaked details on the next-gen Medusa Halo parts showing a move to LPDDR6 and as much as 80% more bandwidth.

Holding the line on price

Agentic AI is also something of a pricing tool for vendors, beyond describing a workload. A 192GB workstation sold on the promise of running 300-billion-parameter models locally can hold a four-figure price more comfortably than a mini PC sold on cores and clocks, and it justifies loading the most expensive component in the build to its maximum. AMD's Ryzen AI Halo developer box, a 128GB Strix Halo system, opens pre-orders in June at $3,999 through Micro Center, matching the launch price of Acer's GB10-based Veriton GN100 and the original DGX Spark before its increase.

Apple, the one vendor with the scale to hold priority memory allocation, has moved the other way. It pulled the 512GB Mac Studio configuration from sale, raised the price of its 256GB upgrade, and in May removed several more high-memory Mac mini and Mac Studio options as supply tightened.

This shows us beyond doubt that expanding capacity while holding the line on premium pricing is a choice the AMD and Nvidia camps are making, not one that the market is forcing. Whether buyers accept it rests on whether local agentic inference delivers enough value over cloud services to justify the outlay, on machines shipping with memory capacities that outpace the bandwidth that ultimately determines what that memory can do.

Computex 2026 is moving full steam ahead, like an AI train running down a track made of gold-plated DDR5 DIMMs. We’ve moved into the first full day of the trade show, and the announcements are really starting to fill in. You can catch our Day Zero coverage here and keep track of our dedicated Computex 2026 hub.

Arm PC chips are back in focus

Windows on Arm is not new; the first-generation Surface RT launched way back in 2012 with an Nvidia Tegra 3 processor. Since then, we’ve seen various other takes on Arm processors running on Windows, from the Surface Pro X with its Microsoft SQ1 SoC to a slew of laptops running Qualcomm’s PC-centric Snapdragon processors.

Now, we’re seeing an even more interest in the segment with Nvidia RTX Spark “Superchip” and the new Snapdragon C from Qualcomm. From all accounts, the RTX Spark targets the high end of the PC market with its 20-core Arm CPU, Blackwell RTX GPU, and 128GB of unified memory.

The Snapdragon C takes a different approach, instead aiming at the budget laptop segment. Laptops using Snapdragon C are expected to be priced as low as $300. However, that price point will be highly dependent on memory pricing, which remains a real pain point not only for OEMs, but also consumers looking to get the most bang for their computing buck. In fact, things have gotten so bad that even Intel has said that "something has to give” with memory prices.

• Nvidia's RTX Spark could capitalize where Qualcomm's Arm-based efforts have not
• Jensen Huang says Nvidia wants to 'reinvent the single most important tool of humanity' with RTX Spark
• Qualcomm aims the Snapdragon C laptop chip at the budget laptop segment, as manufacturers feel the DRAM squeeze
• Intel says 'something has to give' with memory prices

We get hands-on time with Asus’ latest hardware at Computex

Asus always has a large presence at Computex, and this year was no exception. The company had an extensive cast of new characters in the laptop field, with new Vivobooks, Zenbooks, Expertbooks, and Strix Scar gaming laptops. Of the new models introduced, the Zenbook 14 with an Intel processor and 14-inch 2880 x 1800 OLED display caught my attention.

Asus also had a rather cool-looking ROG 20th anniversary Harpe II Extreme Edition wireless mouse and the ROG Azoth Extreme Edition 20 mechanical keyboard. The devices are finished primarily in black, but feature 24-karat gold accents. The keyboard also includes transparent switches and keycaps. And we can’t get past its 3.5-pound heft, thanks to its all-metal chassis.

• Asus shows off updated Zenbook and Strix Scar laptops, along with a TUF-based Gaming desktop
• Hands-on with Asus’ ROG Harpe II Extreme Edition 20 gaming mouse
• Hands-on with Asus’ ROG Azoth Extreme Edition 20 mechanical keyboard

PCIe 6.0 SSDs are on the horizon

A year ago at Computex 2025, we saw prototype PCIe 6.0 SSDs capable of 30+ GB/s speeds. This year, we’re slowly inching towards production-capable hardware, with Phison showing off its latest PCIe 6.0 SSD controller: the X3. The X3 is a 16-channel design that is capable of 28 GB/s sequential read/write speeds and 6.8 million random read/write IOPS.

According to Phison, the controller will begin sampling to customers by the end of 2026, with volume production starting in mid-2027.

• Phison shows PCIe 6.0 X3 SSD controller with 28 GB/s of bandwidth and 6.8 million IOPS, supports 2 petabytes per drive

Everything else

We can’t get into detail on everything we’ve seen so far at Computex in this wrap-up — we’ll let the individual news stories speak for themselves. Here’s everything else we’ve covered for Computex 2026 Day One:

• Noctua announces new thermal pad for AMD chips in partnership with Carbice
• Gigabyte debuts fourth-gen Tandem WOLED and multi-mode Mini LED gaming monitors
• Gigabyte showcases new Infinity products for its 40th anniversary
• Cooler Master shows off new HAF 500 chassis, aluminum fans, and new air coolers
• AMD ‘had to re-engineer’ the Ryzen 7 5800X3D for a re-release

During a press Q&A held at Computex 2026 this morning, Nvidia CEO Jensen Huang hosted a wide-ranging discussion of why the company is entering the PC market with its just-announced RTX Spark platform, and what it stands to gain by introducing an all-new chip into the already crowded personal computing space.

In a response to a question posed by analyst Ryan Shrout, Huang said that the decision to develop and introduce a new PC platform with RTX Spark isn't fundamentally about business concerns like the potential margins involved, and that "we don't really have to choose between solving one problem or another."

Huang repeatedly emphasized that computing at every scale, from the PC to the data center, is undergoing a fundamental shift from a world where systems sit and wait for us to use them to an agentic loop where they'll autonomously work to complete tasks for us by running AI agents and models that can call tools and use Windows and applications themselves. Vera Rubin is the architecture for that shift at data center scale, and RTX Spark is the engine for powering that loop for the PC.

Huang envisions an RTX Spark-powered future where he'll just talk to agents running on his PC via WhatsApp, and they'll get things done for him and communicate the results of that work back to him. "Tell me that's not R2-D2. Tell me that's not robotics. Tell me that's not cool."

He says the company is driving this shift because it has "a chance to reinvent the single most important instrument, the single most important tool of humanity" with RTX Spark PCs, and "we're not going to sit around and not let it get done." He further elaborated that Nvidia sees the opportunity to make a significant contribution to personal computing's future with RTX Spark, to solve a hard problem, and to do it "insanely well." The ultimate question, as Huang sees it, is "Can we create something the world would love?"

Although the highly integrated CPU and GPU and unified memory architecture of RTX Spark might look broadly similar to Apple Silicon, Huang dismissed the idea that the company is trying to compete with Apple and products powered by its M-series chips. He says that Apple has a "world-class silicon roadmap," and that it's building those chips in service of the needs of its own unique device, hardware, OS, and application ecosystem. He says that Nvidia's goal is to "reinvent the PC," and that its focus is "100% on Windows."

Huang also tried to assuage concerns about Nvidia's long-term commitment to the RTX Spark platform, given the relative lack of purchase that other Windows on Arm devices have achieved in the market thus far.

Huang said that "once we start a new product line, once we start a new software image, we support it for as long as we shall live." He cited the long-lived Nvidia Shield TV platform as an example of how the company "takes great care" of the software of its devices, and he says that will be true for RTX Spark devices, as well.

He asserts that the software stack for RTX Spark "is likely the best software stack provided ever, and the software stack defines the experience of the user these days." He says those stacks are the reason why GeForce, Quadro, and RTX Pro products are already "deeply loved," because "we take care of the software."

Huang also touted the breadth of hardware companies that have signed up to make Spark systems as a vote of confidence in the future of the platform. Referring to the laptops on stage with him from Asus, Lenovo, Dell, MSI, Microsoft, and HP, he boasted that "this is literally every computer maker in the world," and "we have never seen anything like it. No new product, no new chip has ever been launched where this much of the world's computer ecosystem signed up."

Beyond the laptops and desktops Nvidia and its partners have already announced, Huang also notes that the RTX Superchip is the SoC formerly known as N1X, and that it has a second, smaller chip called N1 yet to be detailed. He also described N2 and N3 Spark chips for future systems that will power future AI PCs, a commitment he first revealed during his Monday Computex keynote.

Huang said, "We're going to expand our family... We're going to expand the footprint of this architecture, and we're going to extend this architecture for a very long time."

Wirescreen, a business-intelligence outfit that looks into Chinese firms, says that the People’s Liberation Army (PLA) has been actively purchasing Nvidia AI chips even after the White House applied export controls on the most powerful semiconductors. According to The New York Times, public documents reveal that the Chinese military, from 2019 until 2025, has been seeking ways to acquire Nvidia A100, A800, H100, and H800 chips — these were sometimes identified through the listed specifications, but there were also instances when they were directly named in the document.

According to NYT, of 3,800 procurement records relating to high-end chips and computing, some 500 instances were found where units of the Chinese military tried to get their hands on Nvidia hardware. The report claims "nearly every branch" of China's military, including units focused on nuclear explosive simulations, war games, and cyberattacks, was listed. In one specific instance, a cybersecurity unit sought Nvidia A100-powered AI servers for a password-cracking tool called hashcat.

The White House first put export controls on AI chips in 2022, citing fears that the Chinese PLA was using them to advance its own military research. But despite this ban, which made it illegal to ship advanced AI chips to China without a license (which is almost always denied), buying and using them wasn’t illegal in the East Asian country at that time. Because of this, many institutions, including those linked to the PLA, were still looking for ways to get these chips through other means.

This demand for Nvidia chips in China meant that smuggling them was a lucrative effort. There have been multiple reports of enterprising individuals routing shipments through another country, like Singapore, Malaysia, Thailand, Taiwan, and even Japan, just to get these chips into China. Even Supermicro’s co-founder, Yih-Shyan “Wally” Liaw has been accused of smuggling $2.5 billion worth of Nvidia AI servers to China.

On the other hand, Nvidia CEO Jensen Huang has always been against export controls. He believes that the U.S. should actually allow its hardware to be used across the world so that technological advancements would be anchored on American AI infrastructure and that the bans would only backfire, as it would force Chinese companies to innovate. While it’s true that Washington’s moves made it harder for China-based firms to buy Nvidia’s chips, many were still able to find ways to get their hands on them. Furthermore, it fueled the rise of domestic chip manufacturers, which, although they were behind what American companies can offer, are slowly catching up with innovation and performance (but, sometimes, at the cost of efficiency).

Huang also claimed that the Chinese military would avoid U.S. tech the same way that the U.S. doesn’t trust Chinese-made hardware. However, it seems that the leather-clad chief was mistaken, if we are to rely on this report. Still, Nvidia spokesperson John Rizzo told the NYT that advanced AI systems usually use at least a hundred thousand chips, so the minuscule amount shown on the procurement documents does not match that.

Whatever the case, this news is a nightmare scenario for many American politicians, who are wary of giving China and its military any advantage. Even though President Donald Trump made a 180-degree turn in late 2025 and allowed Nvidia to secure export licenses again for the H200 years after it was first banned, some Republican lawmakers are pushing for a law that would give Congress the power to control AI chip exports.

If it passes, this will once again make it harder for Chinese institutions, especially those working with the PLA, from acquiring powerful AI hardware that uses or contains American technologies. However, this might be too late, as even Beijing itself has now commanded its customs officers to intercept H200 and even the RTX 5090D V2 at the border in an attempt to bolster domestic semiconductor production.

Nvidia unveiled the RTX Spark superchip on May 31st ahead of its GTC Taipei event, and right before Computex 2026. The device packs a 20-core Arm-based Grace CPU and a Blackwell RTX GPU on a single package and points it at the one corner of computing where the company has never had a foothold: the Windows PC.

The chip carries up to 128GB of unified memory, a claimed 1 petaflop of AI compute, and 6,144 CUDA cores, and it ships this fall in laptops and compact desktops from ASUS, Dell, HP, Lenovo, Microsoft Surface, and MSI, with Acer and GIGABYTE to follow. Microsoft is named as a co-developer, not just an OS supplier, having built new Windows security primitives to run on-device AI agents alongside Nvidia's OpenShell runtime. Branded as RTX Spark, it’s the chip the industry has spent three years calling N1X.

"For forty years, you launched apps. Click. Type. With RTX Spark and Microsoft Windows, you ask, and the PC does the work," said CEO Jensen Huang. Running 120-billion-parameter LLMs with up to 1 million tokens of context, RTX Spark can render 90GB 3D scenes and play AAA games at 1440p above 100 frames per second, all on a chip whose CPU was half engineered by smartphone SoC vendor MediaTek.

‘A new era of PC’

RTX Spark hasn’t come out of nowhere; it’s the consumer-oriented sibling of the GB10 Grace Blackwell superchip already shipping inside the Linux-based DGX Spark mini-PC, which carries a price tag currently approaching $5,000 due to memory shortage-related pricing pressure. The GB10 pairs a MediaTek-produced Arm CPU complex with a Blackwell GPU on a TSMC 3nm-class node, joined by Nvidia's coherent NVLink-C2C interconnect and fed by a shared 128GB pool of LPDDR5X. RTX Spark takes that architecture and repurposes it for Windows.

We first began to hear about the RTX Spark under its N1X codename back in 2023, when it was reported that Nvidia was developing Arm CPUs capable of running Windows. The chip appeared repeatedly through 2024 and 2025 via the rumor mill, with various delays attributed to factors including Microsoft’s slow next-gen work on Arm and soft notebook demand, pushing a planned second-half-2025 debut into this year.

For eight years, Microsoft's Windows on Arm program ran exclusively on Qualcomm silicon under a partnership that locked out every other chipmaker. Microsoft chose Qualcomm in 2016, and until the deal lapsed, no rival could ship an Arm chip in a Windows PC. Arm CEO Rene Haas confirmed in an interview in January 2024 that Qualcomm's exclusivity with Microsoft would lapse that year, the first on-record acknowledgment from a principal after years of the deal being treated as an open secret. Reuters had reported in 2024 that MediaTek, Nvidia, and AMD were all building Arm Windows chips to enter once the window opened.

Microsoft's role in RTX Spark goes deeper than the Copilot+ certification program it handed Qualcomm, however. The two companies built the agent security stack together at the operating-system level: identity, containment, and policy primitives in Windows, paired with OpenShell's ability to route queries to local models based on a user's privacy rules and to mask personal information in queries sent to the cloud.

Satya Nadella, chairman and CEO of Microsoft, said the launch will deliver "unmetered intelligence to every home and every desk with Windows,” an outwardly materially closer integration than the Snapdragon X program ever received.

Windows on Arm

Qualcomm spent its eight years of exclusivity demonstrating that Windows on Arm could work, but failing to make it sell. Snapdragon X laptops moved roughly 720,000 units in the third quarter of 2024, their first full quarter on sale, which Canalys data put at about 0.8% of PC shipments that quarter. ABI Research projected Arm wouldn’t clear 13% of the PC market in 2025. Qualcomm's own counter-figures were heavily conditioned: CEO Cristiano Amon's "more than 10%" share claim, made on the company's Q1 2025 earnings call, covered only U.S. retail Windows laptops priced above $800 in a single quarter.

A big factor behind this lacklustre performance was software issues. Microsoft’s Prism runs x86 apps on Arm, but in our own analysis of Snapdragon X2 Elite Extreme, we found that professional tools like AutoCAD were unsupported, and games crashed or rendered incorrectly under emulation. The original Snapdragon X pitch leaned heavily on battery life as a huge differentiator, but then Intel's Lunar Lake matched that efficiency, giving buyers long battery life on x86 chips that run every Windows app natively, with no emulation and none of the slowdowns or crashes that came with it. Ultimately, Arm's share of Windows never reached the 50% within five years that Arm and Qualcomm had floated back in 2024.

Two familiar problems

Unlike Qualcomm, Nvidia isn’t selling battery life. RTX Spark's USP is the GPU, CUDA, and the 128GB unified memory pool, hardware aimed at local AI, agents, creators, and gamers rather than all-day portability. Adobe is rearchitecting Photoshop and Premiere for the platform with a claimed two-times uplift in AI and editing workflows, and over 100 Windows software vendors, plus game developers including KRAFTON, NetEase, Remedy Entertainment, Riot Games, and Microsoft Xbox are listed as backing the platform.

Two problems dogged Windows on Arm for nearly a decade that won’t simply disappear with a faster chip, though. First: x86 emulation. Any application without a native Arm build still runs via Prism, and that has meant performance penalties and outright failures across the Snapdragon era.

Nvidia's full CUDA and RTX stack is native, which helps AI and graphics workloads, but says nothing about the long tail of legacy Windows software and peripheral drivers. The second problem is Microsoft itself: its slow progress on the next-gen Windows on Arm platform was cited as a primary cause of the N1X delays, and developers won’t be getting the full picture of the Windows agent features until Microsoft's Build keynote on June 2nd and 3rd, days after the chip was announced.

As for pricing, we’ve got nothing on that yet. The only reference point is the DGX Spark's $3,999 desktop baseline, a figure that’s now approaching $5,000 but also heavily inflated by enterprise networking hardware that consumer-grade devices will omit. That said, LPDDR5X memory costs and TSMC 3nm manufacturing both point toward premium pricing rather than the sub-$700 bracket Qualcomm targeted to broaden Arm's reach.

With the RTX Spark, Nvidia is opening a door that Qualcomm could only pry at, carrying the one asset it never had, and inheriting compatibility and OS dependencies that no amount of compute can resolve on its own.

It is day three of Computex here in Taipei! With most of the big-name keynotes out of the way, we're traversing the show floor non-stop to bring you the latest, greatest, and weirdest from all your favorite hardware vendors.

Computex 2026: Headlines so far

• Microsoft Surface Laptop Ultra weilds Nvidia's RTX Spark superchip with 128GB of RAM
• Nvidia lays out RTX Spark roadmap for laptops and desktop PCs at Computex 2026
• Nvidia unveils RTX Spark Superchip for laptops and desktop PCs at Computex 2026
• Intel details long-awaited Crescent Island AI GPU at Computex, boasts up to 480 GB of LPDDR5X
• Intel Xeon 7 ‘Diamond Rapids’ CPUs officially launching in 2027 on Intel 18A-P
• Intel Xeon 6+ ‘Clearwater Forest’ puts 18A in the data center with up to 288 cores
• AMD’s formerly China-exclusive Radeon RX 9070 GRE goes global for $549 on June 2
• AMD confirms AM5 support through 2029
• AMD brings back Ryzen 7 5800X3D, launches Ryzen 7 7700X3D
• Dell XPS 13 targets MacBook Neo with Intel's Wildcat Lake
• Alienware debuts 39, 34-inch OLED gaming monitors

Computex 2026: Live updates

Well, good morning, and a very (very) warm (and humid) welcome to our Computex 2026 live blog. Stephen from the UK here to see you through the first few hours of Monday. As mentioned, it has already been a jam-packed first day!

There's really nothing like Taipei during Computex:

Nvidia enters the laptop and desktop market

If you're just joining us, then welcome. It is evening in Taiwan and there's a lot happening. Headlines from the first day of Computex include Nvidia's incursion into the desktop PC and laptop market by way of its new RTX Spark Superchip. RTX Spark is a Windows on Arm platform for laptops, which Nvidia claims is the most efficient every built. Top-spec chips offer 20 Arm CPU cores, a Blackwell GPU with 6144 CUDA cores, 128GB of LPDDR5X RAM, and up to 300 GB/s of memory bandwidth.

• Nvidia unveils RTX Spark Superchip for laptops and desktop PCs at Computex 2026

Surface Laptop Ultra

One of the first companies to get behind Nvidia's new RTX Spark, understandably, is Microsoft. The company has unveiled a new Surface Laptop Ultra, effectively its own version of the MacBook Pro. It features a 20-core CPU, Blackwell GPU, 128GB of unified RAM, and more. That's housed in a 15-inch chassis with a mini-LED display, replete with HDMI, USB-C, USB-A, and an SD card reader.

• Microsoft Surface Laptop Ultra weilds Nvidia's RTX Spark superchip with 128GB of RAM, 20 Arm CPU cores, and a Blackwell GPU

Intel Crescent Island

Somewhat overshadowed by Nvidia, Intel has unveiled its new Crescent Island AI GPU, featuring up to 480GB of LPDDR5X memory. The data center GPU is "built for agentic AI," is built on Intel's Xe3P architecture, but details about raw specs are scant at this stage.

• Intel details long-awaited Crescent Island AI GPU at Computex, boasts up to 480 GB of LPDDR5X to combat memory shortages

Radeon RX 9070 GRE

AMD's China-exclusive Radeon RX 9070 GRE is going global, with a $549 price tag when it launches on June 2. This GPU sits right between the 9060 XT and the RX 9070, and you'll be able to catch benchmarks on Tom's Hardware very soon.

• AMD’s formerly China-exclusive Radeon RX 9070 GRE goes global for $549 on June 2

Jake is hungry!

"You ever get to the end of the day and realize you haven't eaten a thing." A quick look behind the scenes at Tom's Hardware, where CPU analyst Jake Roach has just realised that he hasn't eaten anything today. It's 8pm.

AM5 lives on

After previously only committing to supporting its AM5 platform through 2027, the company this week confirmed that it is actually going to support AM5 through 2029, with both Zen 4 and Zen 5 likely to see two further generations of CPU release. It's unclear if this is 2029 will mark the end of the line for AM5.

• AMD confirms AM5 support through 2029

The return of a legend

AMD has announced it will bring back its legendary Ryzen 7 5800X3D, and is also launching a Ryzen 7 7700X3D to fight the rising price of PC building. The latter is a downclocked version of the 7800X3D for AM5 platforms, but the real headline is the 5800X3D, which supports DDR4 RAM and, in theory, should give users a more affordable way to build a potent gaming PC on AM4.

• AMD brings back Ryzen 7 5800X3D, launches Ryzen 7 7700X3D to combat rising component prices

Dell comes after the MacBook Neo

This $699 XPS 13 laptop built around Intel's Wildcat Lake platform is the company's answer to the popular MacBook Neo. Featuring between 8-32GB of RAM, a 13.4-inch display, and up to 1TB of storage, it comes with either the Intel Core 5 320 or an upcoming Intel Core Ultra 7 355 variant.

• Dell XPS 13 targets MacBook Neo with Intel's Wildcat Lake — $699 starting price, $599 for students

DLSS 4.5

Nvidia has confirmed that DLSS 4.5 Ray Reconstruction, an advanced denoiser for better ray-tracing and path-tracing image quality when it releases later this year. Nvidia says it can process 35% more input data and uses 20% more paramaters using the same compute budget as the previous-generation.

• DLSS 4.5 Ray Reconstruction update arrives in August for better ray tracing visuals — broader training data set and second-gen transformer architecture combine for improved image quality

Qualcomm hands on

Qualcomm's new $300 and up ARM laptops come with a mystery eight-core CPU and active cooling. Rocking the new Snapdragon C chip, our very own Paul Alcorn made a discovery that perplexed even the Qualcomm representative on the floor...

• We went hands-on with Qualcomm's new '$300 and up' ARM laptop platform with mystery eight-core CPU — active-cooled Snapdragon C laptop surfaces in Acer Aspire Go 15

A big EXPO boost

AMD is launching a new automatic memory overclocking feature. EXPO Ultra Low Latency promises a 13% uplift in performance compared to standard DDR5 JEDEC speeds, and a 4% uplift over existing EXPO.

• AMD promises 13% uplift with new EXPO ‘Ultra Low Latency’ overclocking on DDR5 DIMMs — automatic memory overclocking delivers 4% improvement over standard EXPO, says AMD

Intel not resting on its laurels

Speaking to Tom's Hardware in response to news about Nvidia's RTX Spark, Intel says it treats all such developments with "a healthy does of paranoia," but touted the virtues of x86, warning of compatibility, DRM, and other issues that inevitably follow Arm CPUs entering the market.

• Intel warns it has 'a healthy dose of paranoia' over Nvidia entrance into PC market — company says RTX Spark is 'great for the market' while touting the virtues of x86

Supermicro makes an appearance

Computex isn't all about consumer hardware, with plenty of B2B and industrial hardware on display too. We got a look at Supermicro's new Vera Rubin NVL72 rack, replete with a new type of cooling that the company says offers 1,000 times higher electrical impedance than standard.

• Supermicro shows off Vera Rubin NVL72 rack with all-new type of coolant — company claims coolant offers 1,000 times higher electrical impedance over standard cooling

A staggering 5090 from Asus

To celebrate 20 years of its ROG brand, Asus has unveiled a monster new ROG Astral GeForce RTX 5090 Edition 20, which includes a wraparound AMOLED display. There's also a 3,000W power supply, a new NUC, a PC case, peripherals, a gaming chair, and more.

• Asus' monstrous ROG Astral GeForce RTX 5090 Edition 20 includes expansive curved AMOLED display — also debuts 3,000W power supply and striking PC case

See what happened at the show before the show

Computex starts before the show floor opens. While it's nighttime in Taipei, you can still take a look at everything we saw early with our Day Zero Wrap Up.

You'll learn more about chips from Intel and AMD, monitors from Acer and Alienware, and, of course, learn a ton about Nvidia's RTX Spark system on a chip.

That should hold you over until the show floor doors open and we get into even more of the nitty-gritty.

Read: Computex 2026 Day Zero Wrap-Up: Nvidia launches RTX Spark Superchip assault on laptop and desktop markets, Intel readies Xeon 6+

Vincent van Gogh, on a laptop

MSI is taking its Prestige 14 Flip AI+ and putting some prestige art on it. The company says the laptops are "inspired by The Starry Night and Starry Night Over the Rhône". That language makes it unclear if they're exact duplicates of the paintings, but either way, they don't look like anything else we've seen lately.

Asus ROG Xbox Ally X20 finally brings an OLED screen

Among the many twentieth-anniversary branded Asus ROG gadgets the brand is releasing is a new version of the Asus ROG Xbox Ally X.

The ROG Xbox Ally X20 bundle includes an updated version of the handheld, with a clear shell, OLED display, TMR joysticks, and a transforming D-Pad with four and eight-way movement. It still has the same AMD Z2 Extreme processor as its predecessor.

ROG XREAL R1 Edition 20 Gaming AR Glasses, with a 171-inch, 240 Hz virtual display at 4 meters.

No pricing information is available just yet.

Who ISN'T having a milestone anniversary?

Lots of companies and brands at Computex seem to have started in years that end with 6.

• Asus ROG has a 20th anniversary product line
• MSI is celebrating 40 years, marked by the Titan 18 HX Dragon Edition Draco Epic laptop (pictured above).
• Gigabyte marked 40 years at the end of May, and is celebrating with its Infinity Design lanauage, including a GPU with rounded edges.

So consider this your reminder to at least get a card for your or a loved one's anniversary. Clearly everyone is celebrating.

How Intel is reacting to RTX Spark

With Nvidia's RTX Spark announced, CPU manufacturers are sizing up the field.

When we sat down with Tom’s sat down with Nish Neelalojanan, senior director of product management for Intel’s Client Computing Group, he told us how Intel is reacting:

“Nvidia puts out great products, right? And they know how to do gaming, they know how to do all these different things. So we always take everything with a healthy dose of paranoia, but we are also very, very confident with our products." He also pointed out Arm chips for Windows have typically had compatibility issues.

Read more: Intel warns it has 'a healthy dose of paranoia' over Nvidia entrance into PC market — company says RTX Spark is 'great for the market' while touting the virtues of x86

An 18-inch laptop for the rest of us

Usually, an 18-inch laptop is a massive workstation or gaming rig. But at Computex, Acer has an 18-inch system, the Aspire 18 AI designed for everyday use. Above, it's pictured next to a 16-inch PC.

That 18-inch screen has just a 1920 x 1200 resolution, but for people who turn up the font size to read (no shame in it!), it may still help. The refresh rate tops out at 165 Hz.

Specs include a CPU up to an Intel Core Ultra 9 386H, up to 32GB of DDR5 RAM, up to 2TB of SSD storage, and Wi-Fi 7 support. Acer claims 22 hours of battery life. And hey, there's room, so you get a number pad.

Like much of what we're seeing at Computex, we don't have a price. But if you've been jonesing for a big screen without a discrete GPU, it is on the way.

AMD had to reengineer the Ryzen 7 5800X3D for a rerelease

AMD's David McAfee shared the story behind the Ryzen 7 5800X3D, and why it took so long to come to market. Apparently, AMD had plans to bring back the chip earlier, but the silicon bonding process TSMC had previously used was no longer available, McAfee says. That led to some additional development time in order to get the CPU into shape, which happened to line up with the 10th anniversary of the AM4 socket. - Jake Roach

Get ready for Intel's Computex keynote

Intel's CEO Lip-Bu Tan is set to take the stage at Computex in just under an hour, and we expect about a 45-minute keynote from the executive, followed by a Q&A session that Tom's Hardware is attending. Although we've already seen most of Intel's announcements, ranging from the G3 Extreme Range to a Diamond Rapids tease, it's possible Tan could drop some hints about next-gen Nova Lake chips during the keynote. - Jake Roach

• Watch Intel's Computex 2026 keynote here — CEO Lip-Bu Tan takes the stage in Taipei at 10:30pm PT on June 1

Intel's 3D V-Cache competitor?

Tom's Hardware attended a Q&A session with Intel CEO Lip-Bu Tan, as well as a panel of executives, including Alex Katouzian, a Qualcomm veteran who recently joined Intel's ranks. We asked Intel about its supposed 3D V-Cache competitor, rumored to be called bLCC or Big Last Level Cache, and Katouzian shared the following:

"When I first came in and started reviewing road maps for the team, I was very pleasantly surprised. So, stay tuned, a very strong roadmap coming, and we will be gunning for that section of the market as well. And so, please stay tuned," Katouzian told Tom's Hardware.

Phison has demoed its future PCIe 6.0 SSD controller in the past, but the earlier displays last year merely showed the chip on a large development. Development of the new X3 controller has obviously moved forward well, as the company had two reference SSDs on display in its booth here at Computex.

Phison says these new SSDs deliver up to 28 GB/s of sequential read/write throughput and an incredible 6.8 million IOPS, easily beating anything available on the market. Stay tuned for our full write up.

Stephen checking in

Well a very good morning from day 2 of Computex! Stephen here to see you through the next few hours.

Timing is everything!

Computex is just like comedy, timing is very important! Coordinating a team around the globe is pretty hectic, so here's some insight into how tricky it can be. It's 10:24am in the UK, but our team on the ground in Taipei have already been at it all day, where it's currently 5:24pm. Of course, our U.S. readership and staff are just waking up. Lots of companies are still working in Eastern or even Pacific time too. A lot of plates in the air.

Snapdragon makes an appearance

We haven't heard too much from Qualcomm this week, with Nvidia dominating the headlines thanks to RTX Spark. However, this Asus Ascent QN10 is a nifty new Mini PC with Snapdragon X2 Elite, which QC claims is the world's first to deliver 80 TOPS through its NPU.

Noctua's latest cooling efforts

For those who want to squeeze every last drop of power and temperature optimization from their CPU, Noctua has announced new thermal pads for AMD chips. Made in partnership with Carbice, these pads are for AM4 and AM5 Ryzen CPUs and are made from carbon nanotubes to improve thermal conductivity.

• Noctua announces new thermal pad for AMD chips in partnership with Carbice — product will work with processors in AM5 and AM4 sockets

Gigabyte's latest and greatest monitors

Gigabyte has unveiled a new series of Aorus Elite gaming monitors. Ranging in size from 27 to 32 inches, three of them feature fourth-generation Tandem WOLED technology for improved color and brightness. The fourth is a mini-LED monitor.

• Gigabyte debuts fourth-gen Tandem WOLED and multi-mode Mini LED gaming monitors — 27 to 32 inches, up to 480 Hz, and up to 5K resolution

Asus’ ROG Harpe II Extreme Edition 20 hands on

Asus is going big to celebrate the 20th anniversary of its Republic of Gamers brand. Alongside a monster RTX 5090 and a 3,000W PSU, there are new peripherals including this Asus ROG HArpe II Edition 20 gaming mouse. It features a gold logo and scroll wheel, as well as gold accents. A little garish for some tastes, it'll cost an eye-watering $259.99.

• Hands-on with Asus’ ROG Harpe II Extreme Edition 20 gaming mouse – 24K gold and a 65K sensor

Relive Intel's keynote

Intel held its Computex keynote overnight, with CEO Lip-Bu Tan taking to the stage. You can relive the keynote below!

The latest in cooling from Frore

Frore has been showing off its latest in solid-state cooling tech. Its AirJet Mini is out here cooling Intel's Wildcat Lake laptop reference design. With 15W of sustained power and just 11.3 mm in total thickness, could it give the MacBook Neo a run for its money?

• Frore System’s solid-state AirJet Mini cools Intel’s Wildcat Lake laptop reference design – 15W of sustained, fanless cooling helps MacBook Neo competitor reach a svelte 11.3 mm, remain silent

Take our quiz!

'The single most important tool of humanity'

Nvidia CEO Jensen Huang says the company wants to 'reinvent the single most important tool of humanity' with its new RTX Spark. The company unveiled its new chip for desktops and laptops at the start of this week.

• Jensen Huang says Nvidia wants to 'reinvent the single most important tool of humanity' with RTX Spark — Nvidia CEO touts support of 'literally every computer maker in the world' for its agentic AI PC platform

Favorite Computex announcement so far?

Cooler Master's MasterDimm

Unveiled ahead of Computex, this Cooler Master MasterDimm is a collaboration with G.SKILL that brings active cooling to DDR5 RAM. No word on just how big those sticks are yet...

New from Gigabyte

Gigabyte is another vendor celebrating a major anniversary at Computex, specifically 40 years in the game. There's new motherboards, GPUs, and a monster 1,600W power supply.

• Gigabyte showcases new Infinity products for its 40th anniversary — X870 Infinity Next halo motherboard boasts metal 3D-printed elements, Aero Wood goes dark, MicroATX Stealth boards, Infinity-style GPUs extend down the product stack

Phison shows off its new controller

Down at Phison, we took a look at its new PCIe 6.0 SSD controller, the X3. The company touts sequential speeds of up to 28 GB/s and 6.8 million IOPS in random read/write workloads. There were also benchmarks on display for a new DRAM-less PCIe 5.0 SSD controller. Get the details here:

• Phison shows PCIe 6.0 X3 SSD controller with 28 GB/s of bandwidth and 6.8 million IOPS, supports 2 petabytes per drive— also new power-sipping E37T SSDs for PCIe 5.0 systems consume a mere 4.5W

You don't know the HAF of it

More from Cooler Master, where we took a look at the company's new cases, fans, and coolers. The new HAF500 case supports up to E-ATX motherboards, dual-GPU setups, and plenty of cooling.

Asus ROG Rapture GT-BE98 Pro Edition 20 gets decked out in black and gold

Asus just launched the ROG Rapture GT-BE98 Pro Edition 20, the 20th-anniversary edition of its existing ROG Rapture GT-BE98 Pro. The overall design of the new router is identical, but the stealth black look is now accentuated with gold trimmings. You can even see gold plating beneath the clear plastic window on top of the router, along with a 20th anniversary badge finished in gold.

While you can expect the same blazing performance as the ROG Rapture GT-BE98 Pro, the ROG Rapture GT-BE98 Pro Edition 20 also includes an exclusive Signature Edition 20 web interface for configuring the router.

MSI Claw 8 EX AI+ joins the growing number of handheld gaming PCs

There's a new competitor to take on the likes of the Steam Deck, ROG Ally, and Legion Go 2. The MSI Claw 8 EX AI+ is a fresh entry using a 14-core Intel Arc G3 Extreme CPU and an Arc B390 GPU. The handheld can also be decked out with up to 32GB of RAM and up to 1TB of storage.

The design looks somewhat unorthodox, with the 8-inch 1080p IPS display jutting well below the flanking controllers. The display is spec'd for a 120 Hz refresh rate and maxes out at 500 nits. Rounding out the main features is an 80 WHr battery inside the 1.3-pound package.

Best Buy already has a product page for the Claw 8 EX AI+ on its website, listing the 32GB/1TB configuration at $1,699.99. However, the handheld is only shown as "coming soon" rather than being available for preorder.

Asus ROG Rapture GT-BN98 Pro will be among the first Wi-Fi 8 routers on the market

If you want to be on the bleeding edge in wireless networking, you won't have to wait much longer for Wi-Fi 8 routers. The first Wi-Fi 8 router coming from Asus will be the ROG Rapture GT-BN98 Pro, which is a gaming router aimed at the high end of the market.

We must caution that Wi-Fi 8 routers won't result in another huge leap in theoretical performance over existing Wi-Fi 7 routers. Instead, optimizations with the standard will make it so that real world performance and range will far exceed what's possible with current hardware. We should also see even longer range for IoT devices, epecially those sitting at the far reaches of the coverage for your home router.

The ROG Rapture GT-BN98 Pro will also include a wide range of LAN/WAN ports, including two 10 GbE ports and four 2.5 GbE ports.

• Asus unveils its first Wi-Fi 8 router — ROG Rapture GT-BN98 Pro offers up to 2x real-world throughput uplift over Wi-Fi 7

We go hands-on with the Acer Predator Atlas 8 Arc G3 gaming handheld

Last week, we brought you news that Acer was working on a Predator Atlas 8 gaming handheld. Well, we got a chance to get a hands-on with the device at Computex, and it's quite impressive.

The Predator Atlas 8 uses Arc G3 and Arc G3 Extreme processors paired with an Arc B370 or B390 iGPU. Systems come with an 8-inch 1200p 120 Hz variable-refresh-rate display rated for up to 500 nits of brightness. An 80 WHr battery should help extend your gaming runtime, and Wi-Fi 7 and Bluetooth 5.4 are included in the mix.

At 1.79 pounds, the Predator Atlas 8 slots in between the Legion Go and the Steam Deck OLED in weight.

Intel's Xeon 6+ in the flesh

We stopped by Intel's demo suite, and the company had a Xeon 6+ chip, along with a wafer, hanging on the wall. This is Intel's first time using 18A in the data center, with Xeon 6+ now sporting up to 288 Darkmont E-cores. You can learn more about it in our Xeon 6+ write-up and go behind the scenes with our Xeon 6+ interview transcript on Tom's Hardware Premium.

Day 3

Good morning and welcome to day three of Computex! I say day 3, but as we've explained before timing is tricky here. In Taiwan day three is almost over, but for our global audiences in places like the UK and U.S., it's just beginning! - Stephen Warwick

Some highlights from Acer

We dropped by Acer to see what the company has to offer at Computex this year. We saw the new Acer Swift Spin 14 AI tablet, the new Predator Atlas 8, and more!

Jensen will sign anything

Everyone knows that if you see Nvidia CEO Jensen Huang at Computex, chances are he'll sign something for you. How about this epic Nvidia GTX 1080Ti Founders Edition?

Noctua's AIO in all its glory

We've been hearing a lot about Noctua's entry into the AIO market for some time. The company is back at Computex 2026 and has finally revealed specs, pricing, and release date. Coming on June 16, pricing should be around $250 (It is listed at 220 euros), with more expensive 360mm and 420mm options available. The NL-LC1 features Asetek's Emma V2 pump and NF-A12/14 fans.

• Noctua's first-ever AIO features a silenced Asetek Emma V2 pump and NF-A12/14 fans — 240mm NL-LC1 starts at around $250, could cost $325 for 420mm cooler

The first 8K ultra-wideband gaming keyboard

Cherry's gaming branch Cherry XTRFY has unveiled the first 8K ultra-wideband gaming keyboard at Computex. With a 70% layout, the technology should be more reliable than 2.4GHz wireless. That means a more stable connection that is less vulnerable to interference from other wireless devices.

• Cherry XTRFY launches first 8K ultra-wideband gaming keyboard — featuring more compact 70-percent layout

Corsair's new mouse feat. Stream Deck

New from Corsair is this Nightsword v2 Wireless SD Stream Deck gaming mouse. Striking name aside, you can map its buttons to Stream Deck features, eight in all, so that you can control streaming functions without taking your hand off the mouse. It's a similar philisophy to the Scimitar Elite Wireless SE. However, the Nightsword also comes with a unique dedicated Stream Deck Launch button.

• Corsair shows off gaming mouse with dedicated Stream Deck launch button — wireless mouse also gets almost 50 hours of 8K battery life

New from NZXT

We stopped by NZXT to see what's news. The company showed off new RGB fans, cases, and more.

Counterfeit DRAM

Tom's Hardware spoke to G.Skill and V-Color at Computex. The latter confirmed to us that it has seen an influx of counterfeit DRAM hitting markets in China, to the extent that it is negatively impacting sales.

• Counterfeit G.Skill and V-Color DDR5 modules hit Chinese marketplaces, impacting company sales — cheap contraband memory using identical PCBs and heat spreaders almost impossible to spot

A long day for Jensen

Nvidia CEO Jensen Huang is one of the main attractions at Computex, and is often mobbed wherever he goes, shutting down booths or even entire floors here in Taipei. Here he is enjoying some brief respite at the Gigabyte booth with a beer and some barbecue.

Taipei drone show

The evening skies in Taipei lit up with a drone show to celebrate Computex, check it out!

Lian Li's new Edge PSUs

Take a look at Lian Li's new Edge Platinum V2 PSUs, equipped with LED dust indicator, magnetic filter, snap-on fan, and a USB header hub. There's also the trademark 90-degree power connector.

The claaaaaaw

The new MSI Claw 8 EX AI+ is an 8-inch handheld that features a 120 Hz display and new ergonomic grips. Bathed in a striking 'Void Purple' finish, our immediate hands-on yielded some impressive performance.

• MSI Claw 8 EX AI+ brings Intel Arc G3 Extreme to handhelds — 8-inch, 120 Hz display and new ergonomic grips

AMD reacts to Nvidia RTX Spark

AMD is acting confident in the face of Nvidia's new RTX Spark announcements.

"I’m really excited that Nvidia has joined the game. You know, we were the only game in town for almost two years now, and the large local memory is becoming super critical in the agentic AI [workloads],” said AMD’s Rahul Tikoo, senior vice president and general manager of AMD’s client business. at Computex “I'm actually happy to see Nvidia join the race for these great products.

Comparing the specs, he suggested that "Gorgon Halo, which is coming out in Q3, is going to be a better product.”

We'll see how these platforms shake out later this year.

Read more: AMD executives react to Nvidia’s RTX Spark — ‘you’re just wrong if you don’t get a Strix Halo notebook’

Sizing up the Dell XPS 13 and MacBook Neo

Which of these systems is thicker? Trick question: both are half an inch thick. At Computex, our own Jake Roach saw the two together at Dell's booth.

The Neo's bottom is thicker, while Dell's is a bit more equal. And the XPS has a slightly rounded bottom, making it appear slightly thinner than Apple's blockier design style. But both list the exact same height, and the spec sheets are identical.

The XPS, however, is lighter than the MacBook Neo, at 2.2 pounds, compared the Apple's 2.7 pounds.

See all of the photos in the gallery above.

MSI adds an internal SSD slot to its flagship Wi-Fi 7 router

Wi-Fi 8 is just around the corner, but there’s still plenty of life left in the Wi-Fi 7 standard. MSI is proving that with a new flagship Wi-Fi 7 router called the RadiX BE19000. At first glance, the RadiX BE19000 looks like any other high-end gaming router, complete with eight antennas that give it an arachnid-like appearance.

However, the RadiX BE19000 hides a secret within — it features a PCIe SSD slot, making the router what MSI calls “NAS Lite.” You can add your own M.2 SSD to enable PC backups or simply to share files across your network.

You still get all the usual trimmings, like tri-band Wi-Fi, dual 10 GbE ports, and four 2.5 GbE ports. In addition, MSI says that the RadiX BE19000 is compatible with its proprietary mesh standard, allowing you to expand your network with compatible routers and access points.

Read more: MSI unveils latest set of WiFi 7 gaming routers touting ultra-fast speeds — flagship RadiX BE19000 model comes with a built-in SSD slot for 'NAS Lite' experience and wireless speeds up to 19 Gbps

Do your science homework

We talked a bit about Noctua's new AIO cooler in this live blog, but one thing we didn't mention: just how much homework they show. The company is ready to defend its doctoral thesis.

If you're ever at Computex, need to rest and do some not-so-light reading to explain what a thermosiphon or a flooded condenser is, Noctua has your back. You can see some of it in the gallery above, and believe me, that is just some of it.

Here ends Computex

Good morning folks, Stephen here to announce that we are signing off our Computex coverage for 2026. At least, our live correspondence from the floor. There's still plenty of news and insight to come from our conversations, but we'll be winding up this live blog soon. It'll remain on the site so you can look back and trawl through any announcements you may have missed, but thank you for joining us for another great year!

Intel is taking Nvidia’s RTX Spark SoC range seriously. Tom’s Hardware sat down with Nish Neelalojanan, senior director of product management for Intel’s Client Computing Group, to get the company’s reaction to Nvidia’s new chips at Computex 2026. Rather than discrediting Nvidia’s new range, Neelalojanan says Intel is handling RTX Spark with “a healthy dose of paranoia,” while highlighting compatibility issues for Windows on Arm and the potentially high price point of Nvidia’s new platform.

“Nvidia puts out great products, right? And they know how to do gaming, they know how to do all these different things. So we always take everything with a healthy dose of paranoia, but we are also very, very confident with our products,” Neelalojanan told me. “When an Arm CPU enters a market, there’s going to be tons of compatibility, DRM issues, backwards compatibility, so as a result, we are very confident that we have the right CPU, GPU mix for clients, both for gaming and when it comes to what you call AI inference workloads.”

Although Qualcomm laid the groundwork for Windows on Arm, the momentum behind the company’s Snapdragon X range has leveled out. Both AMD and Intel have since released chips that deliver the same all-day battery life without the need to fuss with any Arm-to-x86 translation. Nvidia entering the market is a different beast, however. As one of the most valuable companies in the world and the clear forerunner in the AI space, Nvidia demands attention.

To that end, and for just one example of its commitment, Nvidia already revealed that Adobe is working on native Arm versions of Photoshop and Premiere Pro to support RTX Spark, a feat that Qualcomm has been unable to accomplish after two years on the market.

Given how much attention Nvidia demands, it makes sense that Intel is paying closer attention. The company is also in a strange position, as it rarely competes directly with Nvidia. Intel has made some inroads into consumer graphics with discrete GPUs like the Arc B580, and the top-end Arc B390 on Panther Lake is an impressive integrated part, but it hasn’t built anything to seriously challenge Nvidia’s dominance. And the companies continue to work together. Just this week, with the announcement of Xeon 6+ ‘Clearwater Forest’ CPUs, Intel highlighted its work with Nvidia in the data center.

Now, Intel has a direct mobile platform competitor in the form of Nvidia, which isn’t to be taken lightly. Even with that direct competition, Intel says it will continue to work with Nvidia, especially in the data center.

“Nvidia is a great partner. We will continue to work with them. You saw some of our announcements,” Neelalojanan told me. “We have some longer-term commitment with them, so both of us have different parts of the roadmap that we will expand together, there'll be [areas] where we will be partnering, and where there might be places where we will be competing, but I think it's great for the industry that there [are] different choices.”

Although compatibility is the main point of concern — Neelalojanan says “compatibility is going to be a key thing [with RTX Spark]” — pricing is another concern. Nvidia hasn’t revealed the starting configuration for RTX Spark, but given rising memory costs, higher-end configurations with a lot of memory will likely run several thousand dollars. Neelalojanan pointed to Wildcat Lake as an option for the budget market, which goes as low as 8 GB of single-channel memory.

We still have a few months before we see RTX Spark in action to evaluate how it compares to Intel’s Panther Lake, AMD’s Gorgon and Strix Point, and Qualcomm’s Snapdragon X2 chips. Nvidia says RTX Spark designs will arrive in the fall.

Nvidia is transforming Windows into an agentic AI platform at Computex 2026. During his keynote, CEO Jensen Huang revealed the RTX Spark: a Windows on Arm platform for laptops powered by the company's RTX Spark Superchip. The company boldly claims that this platform is “the most efficient ever built,” and it’s throwing its full weight into building a first-class Windows on Arm experience for what it envisions as the next frontier of personal computing.

Nvidia says AI agents are already shaping a new mode of interaction with PCs. Instead of relying on the same mouse and keyboard inputs that have defined personal computing for 40 years, the company sees AI agents as a new interface that will let users command their systems and find information with natural language.

And once those agents have their marching orders, they’ll need to set goals, call tools, evaluate the quality of their work, and refine it, potentially using local and cloud AI models to achieve those ends. Agents might also continue working on long-running tasks even when the user is away from their system or overnight. That all requires powerful, efficient hardware and lots of local memory.

To power all this AI reasoning in the new era of computing it envisions, Nvidia is unleashing the RTX Spark Superchip, a Windows on Arm platform more powerful and capable any other on the market, and a roadmap for the Spark family outlining the next three generations of technology.

At full strength, this chip offers up to 20 Arm CPU cores, a Blackwell GPU with 6,144 CUDA cores, 128GB of LPDDR5X RAM, and up to 300 GB/s of memory bandwidth. That powerful CPU and GPU, connected over NVLink C2C, and the large memory pool give AI agents and 120-billion-parameter models plenty of power and space for long-running tasks with context lengths stretching to a million tokens, according to Nvidia.

RTX Spark will power high-end laptops from partners including Dell, HP, Lenovo, Asus, and MSI -- and notably, a new Surface Ultra laptop from Microsoft. Nvidia says it’s worked with those partners to create “the most extraordinary laptops [they’ve] ever built,” with tandem OLED G-Sync displays, “all-day” battery life, premium aluminum chassis with large glass touchpads.

Nvidia says that the incredible efficiency of the RTX Spark platform “transforms what a high-performance laptop looks like,” so buyers in the promised agentic AI age will no longer need to choose between high performance or thin chassis with long battery life. RTX Spark PCs will also deliver similar performance whether plugged in or unplugged, as we’ve come to expect from other Windows on Arm and Apple Silicon-powered systems.

RTX Spark will also bring this agentic Windows on Arm experience to compact, powerful desktops in the vein of the DGX Spark. In total, Nvidia expects over 30 laptops and “10 or so” desktops to lead the charge when the platform launches.

In addition to its agentic AI chops, Nvidia positions the RTX Spark Superchip as a creative and gaming powerhouse. The company promises the platform is good for “100 FPS 1440p gaming,” potentially enabled by DLSS 4.5 upscaling and Multi Frame Generation. And its large memory pool means creators can work with massive 3D projects and ultra-high resolution video files like 12K 4:2:2 content without running out of resources.

To further the RTX Spark platform’s creative chops, Nvidia says it’s working with Adobe to rebuild the core of Photoshop, transforming it into a 100% GPU-accelerated application for RTX Spark. Those updates will enable new generative workflows, high-dynamic-range editing, and more natural brushing for artists.

And Premiere is also getting a core overhaul that’s claimed to enable faster and more sophisticated AI workflows, editing, color, and effects. Adobe will also expose Model Context Protocol controls for AI agents to harness its products.

In partnership with Microsoft, Nvidia is also helping to transform Windows into an agentic platform with its OpenShell framework and a “new set of security primitives” that form a set of guardrails, ensuring that local agents and models only have access to the tools and data the user grants them access to. Nvidia says Microsoft will reveal more details of this agentic AI transformation at its upcoming Build conference.

RTX Spark systems will begin arriving in the fall of 2026, and we can't wait to dig into them to see whether Nvidia's backing will truly transform the Windows on Arm experience for the agentic AI era - or just make for a really great PC platform. Stay tuned.

Nvidia CEO Jensen Huang is kicking off Computex 2026 this year with a keynote address, starting at 8pm PT / 11pm ET on May 31, or at 11am Taipei local time. Tom's Hardware will be covering the event live from Taipei Music Center as Nvidia lays out "the breakthroughs driving the next generation of AI." You can join along live with a stream of the keynote on YouTube, which we've embedded below.

We currently expect the keynote to run about two hours, which is typical for Nvidia. However, we've seen keynotes as short as 90 minutes and as long as two and a half hours before. Although we expect much of the keynote to focus on enterprise AI and Nvidia's "AI factories," there's a decent chance we'll hear some consumer announcements around Nvidia's long-rumored N1X chip, as well.

Just hours ago, full specs for the N1X and N1 leaked, and that follows a tease from Nvidia and Microsoft promising "a new era of PC" at Computex. Otherwise, however, we don't expect to hear anything related to GeForce. There have been murmurs that Nvidia could reintroduce older GPUs to fight rising component prices, but that seems unlikely at the moment.

Leading up to the keynote, Nvidia is hosting GTC Live, which is a pregame event presented by Bruce Lu (Goldman Sachs, Taiwan Semiconductor Research) and Tracy Tsai (Gartner, VP Analyst).

It's finally happening — Nvidia is set to launch the N1 family of SoCs at Computex tomorrow after years of it being stuck in the rumor mill. And just a day before the grand reveal, most of the specs for the lineup have leaked, courtesy of Videocardz. As expected, there seem to be two distinct SKUs: N1 and N1X, both targeting different performance and price levels. Take the following information with a grain of salt since it comes from documents dating back to 2024.

We begin with the standard N1 that reportedly comes in two configs. There's a 12-core (8+4) model with 2,560 CUDA cores and a 10-core (7+3) model with 2,048 CUDA cores. Either variant comes with 8x PCIe 5.0 lanes and 3x PCIe 4.0 lanes; the base N1 supports up to two M.2 SSDs. Memory support tops out at 64GB across 8x LPDDR5X channels. In terms of power budget, we're looking at 18W-45W TDPs.

Then there's the more exciting N1X that, at the top-end, is identical to the GB10 found in Nvidia's DGX Spark mini-PC, which Nvidia CEO Jensen Huang already confirmed. There are two SKUs for this SoC as well: a full-fat 20-core (10+10) monster with 6,144 CUDA Cores — same as the desktop RTX 5070 — and an 18-core (9+9) variant with 5,120 CUDA Cores. Both chips have the same power envelope of 45W-80W.

N1X will reportedly start at 16GB LPPDR5X configs, but the platform can support up to 128GB across 16 channels. We don't know at what speeds exactly yet, but a previous leak suggested these chips are operating at 8,533 MT/s, which would make the RAM config faster than AMD's Strix Halo. The N1X also has 12x PCIe 5.0 lanes and 5x PCIe 4.0 lanes capable of accepting up to three M.2 SSDs.

All signs point toward Nvidia unveiling the N1/N1X family tomorrow, so we should know all about these chips very soon. Based on the history of leaks and rumors, and educated guesses, these specs make sense. Once made official, Nvidia would re-enter the laptop market, directly competing with AMD, Intel, and, of course, Apple. We say re-enter because the company already tried selling ARM-based PC chips back in 2011.

The advent of a new mainstream SoC from Nvidia could open doors to exciting handhelds, OEM PCs, and perhaps even a refreshed Shield TV that fans have been yearning for forever. It's a positive development considering just how abandoned consumers and, in particular, gamers have felt these past few years, but it all comes down to pricing. And during a RAM crisis, that's not going to be ideal.

N1X will likely target the $2,000+ market, competing with the MacBook Pro, but the N1 could be an exciting midrange option under $1,500.

Some people are pretty excited that we are on the cusp of a new Windows PC era ignited by technologies from the mighty Nvidia and Arm. Our article on the teasers for the rumored wave of new N1X laptops makes it clear that companies like Nvidia and Microsoft are excited, at least. However, Microsoft veteran Steven Sinofsky is here to remind folks that it has been done before, with a similar level of simmering excitement, when the first Surface hybrid PC ran on Nvidia Tegra Arm silicon back in 2010/11.

Sinofsky shares some interesting media in the above embedded Tweet. There’s a slide from the promotional deck, shown at CES 2011, where the “strong partnerships” behind this Windows on Arm thrust would surely lead to unstoppable momentum. That’s what you may have believed if you swallowed the effusive presentations at the time.

This prior push for Windows on Arm didn’t exclusively support Nvidia Tegra. Sinofsky points out that Windows 8 on Arm also supported Qualcomm and TI processors. However, we saw Microsoft switch to a Qualcomm partnership focus in the years following. That collaborative effort also didn’t break through, even when the much-lauded Nuvia Oryon architecture arrived with the Snapdragon X family.

The former-President of the Windows Division (July 2009 to Nov 2012) also shares a video that should be preserved for posterity. Check it out to witness “an old school Windows Phone video of the first time Windows ran on Nvidia Tegra Arm using the desktop compositor which was a BIG deal. Sept 2010.”

The video appears to show a Tegra dev kit running Windows 7, with multi-window and Start menu manipulation, which looks rather lethargic to my eyes. However, that was a “first” achievement several months before CES 2011, and it would be over a year and a half until the Surface RT shipped to customers (October 2012).

Will the latest Nvidia and Arm thrust into Windows work out better? We’ll probably have a much better idea about that in the coming days at Computex. Sinofsky replies to some comments on his Tweet to say the result could be “a reliable platform for graphics compute,” using Windows. Pricing is also obviously going to be a sticky issue for any new platform looking to attract buyers right now.

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.

TikTok owner ByteDance is reportedly developing its own custom AI CPUs in a bid to reduce its reliance on US chipmakers. Per a Reuters report, ByteDance's new chip is inspired by Groq's "language processing units," a fancy term for a chip optimized for inference tasks — running AI models instead of training them. The move comes in a context where inference-heavy agentic AI is quickly becoming the new normal. The project is seemingly in the concept and design stage, with Reuters' sources claiming that ByteDance is evaluating both Arm and RISC-V designs.

Additionally, The Information claims ByteDance is partnering with Chinese startup InnoStar Semiconductor for memory technology related to the project, potentially obviating the need to acquire rare and expensive HBM chips from Samsung and the like. The Chinese startup got investments from ByteDance and Alibaba, China's cloud and e-commerce giant.

However, ByteDance doesn't appear to have its own chip design teams, and will purportedly rely on "several external partners", who are expected to also take care of the actual silicon manufacturing. The firm's CPU project takes place against a geopolitical tussle that got China's government banning the purchase of Nvidia H200 Blackwell chips, after the Trump administration backtracked on its technological export controls.

This is hardly ByteDance's first rodeo with investing in its own technology, too, as it started designing its own SeedChip AI accelerator with TSMC back in 2024, a silicon slab expected to tape out and be mass-produced this year still. For now, the expectation is that ByteDance will use hybrid architectures for its servers as dependence on Nvidia is still an unfortunate necessity, but over time, it wouldn't be surprising to see the firm waving goodbye to the back of Jensen Huang's leather jacket.

Furthermore, much like any other advanced chip vendor these days, Intel and AMD reportedly keep increasing prices every quarter as they hold the lion's share of the CPU market. Nvidia's recently unveiled Vera chips show great promise, but once again, we're talking about a U.S. firm. Although Bytedance is best known for TikTok, the world's leading short-form video app, the company runs China's AI chatbot app Doubao and has a handful of AI models under its belt.

A day after Taiwanese authorities seized 50 Supermicro servers and arrested three people on suspicion of smuggling them into China, Supermicro has clarified that it "worked closely" with law enforcement in Taiwan leading up to the arrests and that it will continue to do so.

This comes days after Nvidia CEO Jensen Huang called on Supermicro to "improve regulation compliance," and months after Supermicro co-founder Yih-Shyan "Wally" Liaw was charged by U.S. prosecutors for allegedly smuggling $2.5 billion worth of servers into China.

Here is the statement in full:

"Supermicro is committed to protecting our advanced technologies and intellectual property, and we are proud to have worked closely with Taiwanese authorities on the recent event, helping to prevent the illicit diversion of our highly sought-after systems into the restricted China market. Our collaboration with authorities in Taiwan resulted in the arrest of three suspects and the seizure of 50 servers that had been deceptively acquired after being sold by Supermicro to an authorized reseller. We thank local law enforcement and legal officials for their vigilance and professionalism.

The initial transaction – Supermicro's sale of products to an authorized reseller – followed a rigorous vetting and review process that exceeded applicable government requirements. This case highlights the challenges that can arise when products are resold through multiple downstream parties beyond direct manufacturer control. It also underscores the importance of continued collaboration across industry and government to strengthen safeguards, enhance supply chain visibility, and facilitate the enforcement of export control laws. Supermicro will continue to cooperate with law enforcement and government officials in the United States, Taiwan and other jurisdictions to ensure our technology is distributed as lawfully intended."

The smuggling operation that led to arrests reportedly routed servers coming from Taiwan through Japan. Supermicro itself claims that the servers were sold to an authorized reseller, presumably in an attempt to wash its hands of any accusations that the company was directly involved.

Although three Supermicro employees have been charged by U.S. officials in connection to an earlier smuggling operation, neither Supermicro nor Nvidia have been charged. Despite this, Supermicro's stock plummeted nearly 30% after news of U.S. charges broke.

The U.S. government, and presumably Taiwanese authorities, have been cracking down on server smuggling to China over the past several months. In March, the Trump Administration proposed a strict licensing system for advanced AI hardware exports, and some U.S. senators have called on a wholesale ban on export licenses for Nvidia hardware to China, as well as several other south-east Asian countries including Malaysia, Thailand, and Vietnam.

The very first set of Nvidia Vera CPU benchmarks have just been released by Phoronix, with results from a set of common Linux benchmarks. While the tests were curated by Nvidia at its Santa Clara headquarters, the early data from those tests indicates that Vera is highly competitive compared to AMD's EPYC and Intel Xeon offerings, at least in the workloads Nvidia is targeting with the chip.

Phoronix was invited to NVIDIA's Santa Clara headquarters to test the upcoming 88-core CPUs. Vera is notable for all kinds of reasons, but most especially because it doesn't license an Arm processor core. Instead, like Apple's chips, it uses the ARM instruction set on a fully custom CPU core known as "Olympus." This isn't the first time Nvidia has produced a custom CPU core; that would be "Denver" in the Tegra K1 from 12 years ago. However, where Denver was a desktop-class CPU constrained by a mobile power budget, Vera is a server-class monster fed with a server-class power budget, and the proof is in the benchmark results.

Phoronix's Michael Larabel was able to test Vera across a range of benchmarks, including code compilation tests, synthetic memory benchmarks, AV1 video encoding, Python, Java OpenJDK, file compression, Lua JIT, and some database benchmarks. In most of the tests, the Vera processors are highly competitive against the competition, which includes AMD EPYC "Turin" processors in single- and dual-CPU configurations as well as an Intel "Granite Rapids" Xeon chip. As Larabel says, Vera offers "competitiveness to Intel/AMD x86_64 CPUs that [he has] never seen out of any other ARM or non-x86_64 processors." It doesn't win outright in most tests, but it's running very close to the EPYC configurations, which is shockingly good for a first-generation custom server core from Nvidia.

What's even more impressive is if you switch things over to a per-thread view of the data, which Phoronix does for some tests. Historically, Arm server vendors have achieved similar performance versus AMD and Intel in multi-threaded workloads by simply cramming a huge pile of cores onto a chip, but the single-threaded performance of x86 was beyond reach. Well, in a timed Gem5 compilation, only the AMD EPYC 9575F was able to beat Nvidia's Vera on a "performance per core" metric. In a Linux kernel build, Vera tops the stack of server chips by a decent little margin. It's real eyebrow-raising stuff, and speaks to the strength of the Vera core.

Looking at the geometric mean of test results, Vera comes out on top by a fair margin, in part thanks to very strong performance in LuaJIT FFTs, ClickHouse database server, and the Renaissance JVM benchmark, where it absolutely dusted the competition. This is genuinely exceptional, but there are caveats to this data. Larabel notes that Nvidia limited the scope of these initial benchmarks to its "intended markets and target use-cases," but it's also true that these tests are benchmarks that Larabel is familiar with and already runs on server CPUs for performance analysis. He says that today's results are a "small subset" of his typical preferred approach, which is to say that this data is valid, but may not represent all workloads or use-cases.

One key detail that the site wasn't able to test comes down to power efficiency. This is a big deal for consumer systems, but it's a much bigger deal for AI data center operators who are currently struggling with build-outs because the power infrastructure worldwide simply isn't robust enough to support megawatt AI training clusters popping up all over the place. Nvidia says that Vera has a 450W TDP, while the fast SOCAMM2 memory it uses consumes another 50 watts; the Xeon and EPYC chips used for comparisons are rated for 500W before accounting for platform memory power. Real power consumption can be very removed from TDP figures, though, so we'll have to wait and see how that plays out.

Another point in favor of Vera is software support. According to Larabel, Vera has "great upstream open-source support," which is encouraging for the future of these chips. Over the decades, we've seen many examples of promising hardware that falls by the wayside due to insufficient software support. All of the testing was performed on a mainline Linux kernel with no need for nasty Device Trees or hacky bespoke driver solutions.

While Nvidia's Vera looks legitimately formidable next to current-generation chips, both AMD and Intel have new chips on the way that look downright gobsmacking. AMD's planning to pack some 256 Zen 6 CPU cores into a single socket with the dense version of EPYC "Venice", while Intel's "Clearwater Forest" will combine up to 288 Darkmont cores with its bleeding-edge 18A process technology in a direct attempt to reclaim the performance-per-watt crown. The end of the year and next year's server landscape are going to be very, very different from today.

China's official technology security bodies on Tuesday certified nine domestically designed AI processors for state procurement, according to the South China Morning Post, creating a brand-new "AI training and inference chips" category under the country's Anke security certification framework. The approved products include Huawei's Ascend 310 and Ascend 910 processors, Alibaba's T-Head Zhenwu M530 and M890, and chips from Biren Technology, Hygon Information Technology, Iluvatar CoreX, MetaX, and Moore Threads. Two of China's most prominent AI chip developers, Cambricon Technologies and Baidu-backed Kunlunxin, didn’t appear on the list.

The certifications are valid for three years and were issued jointly by the China Information Technology Security Evaluation Centre and the National Secrecy Science and Technology Evaluation Centre. Their approvals function as a de facto procurement catalog for government agencies, central state-owned enterprises, and other entities covered by Beijing's Xinchuang initiative, the long-running campaign to replace Western hardware and software across sensitive Chinese IT systems.

The new list represents a substantial expansion from China's initial foray into certifying domestic AI hardware. In December, Beijing added only Huawei and Cambricon to the Xinchuang procurement list (a separate state approval mechanism) for AI processors. Five months later, seven vendors now hold Anke security certification for nine separate chips. The Xinchuang program had previously focused on replacing Intel and AMD CPUs and Oracle databases in government systems, but AI accelerators are the newest addition to that.

Cambricon's absence stands out given that the company was on the December list and is targeting 500,000 AI chip shipments in 2026. An anonymous source told the SCMP that companies can choose whether to submit products for testing, so exclusion doesn’t necessarily indicate a failed evaluation. Each chip must pass tests under the Anke V3.0 requirements to qualify.

Chinese chipmakers continue to eat into Nvidia's position in the domestic market. Chinese semiconductor firms delivered 1.65 million AI GPUs in 2025 out of a total of 4 million units, claiming 41% of local AI server shipments. Huawei alone shipped roughly 812,000 AI chips and is projecting $12 billion in AI processor revenue for 2026. Morgan Stanley estimates China's total AI chip market could reach $67 billion by 2030, with domestic supply covering roughly 76% of demand.

Wafer fab capacity remains a big constraint, however, with all of the certified chipmakers competing for limited production slots at SMIC, whose most advanced stable node is its N+2 process, which is roughly equivalent to 7nm. SMIC reported overall utilization rates above 93% for 2025 and spent $8.1 billion in capex last year, with plans to hold that level through 2026.

Prosecutors from the Taiwan Keelung District Office arrested three individuals last week, suspected of smuggling Nvidia chips to China. According to Bloomberg, the Taiwanese authorities also seized 50 Super Micro servers with falsified documents that were reportedly ultimately destined for Hong Kong via Japan. Aside from the seized servers, authorities say that an earlier batch of shipments had already been smuggled successfully using fake documentation.

This is the first arrest Taiwan has made in connection with the U.S. crackdown on AI chip smuggling, and the first to reveal Japan as a transshipment point for these illicit goods. Many smuggling operations have been using Southeast Asian nations to route Nvidia chips to China. However, countries like Singapore and Malaysia have started cracking down on these outfits, meaning smugglers need to look for other ways to get the banned hardware under the radar.

It is surprising that the recently broken-up operation in Taiwan routed the servers to Japan, especially as the country is known for its strict customs enforcement. The latter is a staunch U.S. ally and is one of the key pillars of the United States’ strategy in the Pacific to contain China. However, some Chinese AI companies also use the country to rent Nvidia AI chips owned by foreign firms that they otherwise wouldn’t be able to access domestically — a route that’s currently allowed by Washington’s export control rules. Japanese authorities from the Ministry of Finance's Customs Bureau and the Ministry of Economy, Trade, and Industry have remained silent on the issue, and they also did not confirm if they’ve been in touch with their Taiwanese counterparts regarding the arrest.

While the arrested individuals were illegally dealing Supermicro servers powered by Nvidia chips, the Taiwanese authorities have refrained from accusing both companies of breaking U.S. export control laws. Nevertheless, Nvidia CEO Jensen Huang said that the company explains the rules and regulations to its partners and is urging the company to fix its compliance systems. “Ultimately Super Micro has to run their own company,” Huang said to reporters. “I hope that they will enhance and improve their regulation compliance and avoid that from happening in the future.”

It’s unclear which chips were being smuggled, but the last-generation Nvidia H200 have already received clearance from the White House for export to China. However, Chinese customs officials were instructed to block these chips at the border, with the order recently being expanded to RTX 5090D V2 gaming GPUs.

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.

Nvidia CEO Jensen Huang called on Super Micro Computer to strengthen its export compliance controls after arriving in Taipei on Saturday, months after U.S. federal prosecutors charged the server maker's co-founder and two others with conspiring to smuggle approximately $2.5 billion worth of Nvidia-equipped servers to China through shell companies in Southeast Asia.

Huang told reporters at Songshan Airport that Nvidia insists its partners follow U.S. trade rules. "We insist our partners are compliant. We hope that they will enhance and improve their regulation compliance and prevent that from happening in the future," Huang said in an address to the media.

Huang's comments came days after Taiwan launched its first formal crackdown on illicit AI hardware exports. The Keelung District Prosecutors' Office announced earlier this week that three suspects had submitted fraudulent shipping declarations to export Super Micro servers containing Nvidia AI chips to China, Hong Kong, and Macau.

The Taiwan case is separate from, but closely related to, the much larger U.S. federal prosecution unsealed in March. That indictment charged Supermicro co-founder Yih-Shyan "Wally" Liaw and two others with conspiring to smuggle approximately $2.5 billion worth of Nvidia-equipped servers to China through shell companies in Southeast Asia. Liaw has pleaded not guilty, and Supermicro has said it’s not named as a defendant and is cooperating with the investigation.

In the same press scrum at Songshan Airport, Huang confirmed that China is included in the $200 billion addressable market he projected for Nvidia's upcoming Vera CPU during the company's earnings call on May 20th. "H200 has been licensed to ship to China. It would be terrific to be able to serve that market. The Chinese market is very important. It's very large, of course," Huang told reporters, according to Reuters.

Despite the licensing approval, not a single H200 has been delivered to a Chinese customer. While roughly 10 Chinese firms have been cleared to purchase the chip, shipments haven’t started, and President Trump's talks with Chinese President Xi Jinping in Beijing earlier this month produced no breakthrough on Nvidia chip sales.

Huang is in Taipei ahead of Nvidia's GTC Taipei event and his Computex keynote on June 1st, where he’s expected to explore the Vera Rubin platform's software stack. He described the platform as "the largest product launch, probably in the history of Taiwan," noting that each Vera Rubin NVL72 system contains nearly 2 million parts and involves around 150 Taiwanese ecosystem partners.

This week, Nvidia released its Q1 2027 results, posting a record-breaking $81.65 billion in revenue thanks to sales of its AI and data center products. Colette Cress, chief financial officer of Nvidia, said that he expects sales of the company's Grace and Vera CPUs for data centers to hit $20 billion this fiscal year, thus outselling both AMD and Intel and becoming the world's largest supplier of processors by revenue. This is a realistic expectation, principal analyst and president of Mercury Research, Dean McCarron, tells Tom's Hardware Premium.

Outselling AMD and Intel

"Vera CPU opens a brand-new $200 billion TAM for Nvidia, a market we have never addressed before," Cress said during the company's conference call with financial analysts and investors. "Every major hyperscale and system maker is partnering with us to get it deployed. We have visibility to nearly $20 billion in total CPU revenue this year, setting us up to become the world-leading CPU supplier."

Nvidia later clarified that the $20 billion figure includes sales of Grace and Vera processors within Superchip combinations, NVL72 systems, and standalone CPUs sold either as racks aimed at agentic AI workloads or other applications.

Intel's data center and AI (DCAI) division's revenue totaled $16.8 billion last year, whereas AMD's data center unit earned $16.635 billion in 2025. While CPUs account for the lion's share of earnings of these business units, their sales are by far not 100% of their revenue, so actual sales of Xeon and EPYC products are well below $16 billion. The entire x86 server CPU market is worth around $30 billion. Therefore, the $20 billion figure would indeed approach two-thirds of the traditional server CPU market, making Nvidia the world's No. 1 server CPU supplier.

What makes Nvidia's statement especially remarkable is that while Grace CPUs are widely available and have shipped in huge quantities, its 88-core Vera CPU hasn't yet shipped in high volume. Furthermore, Nvidia has never meaningfully participated in mainstream server CPUs before. Given that Nvidia is poised to sell millions of Rubin data center GPUs, and every two of them will be attached to a Vera CPU, the company is almost guaranteed to sell plenty of CPUs.

"We will sell millions of Rubin GPUs and every two of them is connected to a Vera [CPU]," Jensen Huang, chief executive of Nvidia, told analysts and investors. "Vera is used in [four] ways. The first is Vera Rubin [platform containing two Rubin GPUs and one Vera CPU]. The second use case is Vera as a standalone CPU. The third is Vera with CX9 and its software stack for storage. The fourth is Vera with CX9 alongside a software stack for security, compute isolation, and confidential computing."

Conquering the CPU kingdom

Given the dominance of x86 servers, alongside AMD's EPYC and Intel's Xeon CPUs in particular, it is hard to imagine that another company can outsell these highly popular products. Yet, it is more than possible, given the fact that Nvidia can price its CPUs well above the average selling prices (ASPs) of other x86 offerings, and still manage to outsell competitors. This is because Nvidia sells vertically integrated platforms rather than standalone CPUs or GPUs. While Nvidia is not 'known' for its CPUs, it is definitely not a new entrant.

"Nvidia is in a unique situation, and I do not think we can really call them a 'new entrant," McCarron told Tom's Hardware Premium.

Based on leaked estimates from Morgan Stanley Research, Nvidia will charge its hyperscale clients around $5,000 per Vera CPU when they purchase VR200 NVL72 machines later this year. Assuming that the estimate is correct, then selling CPUs worth $20 billion will require Nvidia to sell 4 million Vera units. Four million units is perfectly achievable for Nvidia, McCarron believes.

"As far as delivering 4 million CPUs per year, Nvidia is already on track to deliver a number very near that for its GB300 and Rubin systems in FY2027 (so roughly Q2 2026 - Q1 2027 calendar year)," McCarron said. "So, their comment indicates some moderate upside to CPU shipments."

In fact, Nvidia could probably sell considerably more than four million CPUs this fiscal year if it wanted to, and if it secured or reallocated additional capacity for production of its 88-core Arm-based processor, according to McCarron.

"This really just comes down to customer demand and pricing/revenue allocation to get to the $20 billion," the analyst told us. "I would expect that the number is going to be heavily weighted towards the end of their fiscal year."

Speaking of capacity, Nvidia has commitments for capacity and inventory of around $145 billion, so capacity allocation may not be a problem for the company.

"We remain front-footed in securing sufficient supply to support our customers' growth," Cress said. "In Q1, we increased total supply, inclusive of inventory, purchase commitments, and prepaids, to $145 billion."

AMD and Intel shipped nearly 20 million EPYC and Xeon SP processors for data center systems in 2025, Dean McCarron told us. Meanwhile, AMD's EPYC average selling price was about $1,325, whereas the ASP of Intel's Xeon SP was about $1,125, according to Mercury Research. That said, if Nvidia sells 4 million processors worth $20 billion, then it will not only outsell both AMD and Intel, but will become a formidable rival for both companies from a pure unit sales point of view, too.

As prices of components are increasing rapidly due to high demand from the AI sector, the cost of these machines is also increasing significantly. Morgan Stanley Research estimates that a next-generation Vera Rubin-based VR200 NVL72 rack will cost major hyperscale cloud service providers (CSPs) around $7.8 million per unit (via @Aaronwei3n), which is tangibly more than about $4 million per GB300 NVL72. Furthermore, because every VR200 NVL72 rack packs plenty of DRAM and NAND, memory now accounts for around 25% of the total cost.

Nvidia plans to charge $55,000 per Rubin GPU and $5,000 per Vera CPU when selling them in volume inside VR200 NVL72 chassis to hyperscalers, according to Morgan Stanley. Although the upcoming VR200 NVL72 racks use the already familiar Oberon chassis, they use more sophisticated switching, networking, printed circuit board (PCB), cooling, power supply, and even chip packaging components, which increases bill-of-material (BOM) costs and eventually the price of the systems. As a result, each VR200 NVL72 will cost hyperscalers around $7.8 million, according to Morgan Stanley, which is higher than around $7 million we were told by one of our sources in late March. Meanwhile, the cost of memory within a VR200 NVL72 rack will be about $2 million, up 435% from the memory cost in GB300 NVL72, according to the same figures.

There are several reasons why the cost of memory is expected to account for 25% of the cost of a VR200 NVL72 system and why the system carries $2 million worth of memory.

First up, each of such racks now contains 54 TB of LPDDR5X memory, up from 17 TB of LPDDR5X in the case of a GB200 NVL72, a threefold increase. SemiAnalysis estimates that Nvidia paid $8 per GB per GB of LPDDR5X in Q1, though that price may increase as demand rises in the coming quarters, especially if we are talking about SOCAMM2 modules that are expensive to make and test. In any case, even at $8 per GB, each GB200 NVL72 machine carries $136,000 worth of LPDDR5X memory, whereas each VR200 NVL72 system will contain $408,000 worth of LPDDR5X content. If the price rises to $10, we are talking about $540,000 for LPDDR5X alone. Note that even $10 per GB may be an underestimate* as Nvidia adds its own markup.

Secondly, each VR200 NVL72 rack carries about $1 million or more of 3D NAND storage, up from virtually zero inside GB200 NVL72.

As a result, $2 million of memory content per Vera Rubin NVL72 rack is not something completely unexpected: the system uses a lot of LPDDR5X and 3D NAND memory (not to mention HBM4 memory onboard of Rubin GPUs), and memory now comes at massive prices.

*Contract price of DDR5 memory is now between $12 and $16 per GB, depending on various factors and luck, according to Framework. Spot price for DDR5 was about $20 per GB on average at press time, according to DRAMeXchange. LPDDR5X is more expensive than DDR5. When installed on SOCAMM2 modules (which are exclusively used by Nvidia's Vera CPUs), it will get even more costly, especially when Nvidia's markup is added.

Nvidia announced its financial results for the first quarter of its fiscal year 2027 on Wednesday, posting a whopping $81.615 billion in revenue, marking its best quarter ever. Sales of the company’s AI platforms to various customers were record, prompting the company to reconsider how it reports its earnings going forward. From now on, the company will no longer report sales of its consumer graphics cards — whether for gaming or professional workloads — as separate product categories. Instead, GPU sales will be reported under different categories.

For the quarter that ended on April 28, 2027, Nvidia's GAAP revenue totaled $81.615 billion, up 20% sequentially and up 85% compared to the same quarter a year ago. Nvidia’s net income topped $58.321 billion, up 211% year-over-year (YoY) as its gross margin reached 74.9%. Sales of Nvidia’s Compute & Networking hardware hit $74.55 billion (an all-time record), whereas sales of its graphics hardware totaled $7.065 billion, up 20% sequentially and 85% year-over-year.

New reporting framework

Selling $81.615 billion worth of hardware in a single quarter is, without any doubt, an incredible achievement. However, a more startling revelation is that Nvidia will cease to report sales of gaming and professional graphics cards as separate categories, which emphasizes once again that Nvidia's primary business now is artificial intelligence and data center hardware, not graphics.

Instead of its traditional product categories, Nvidia will now split its revenue based on deployment markets. Going forward, the company will report two main platforms: Data Center and Edge Computing. Within Data Center, Nvidia is splitting revenue into two major sub-segments: Hyperscale, which includes hyperscale cloud providers and large internet companies (AWS, Google, Meta, Microsoft, etc.), and ACIE (AI Clouds, Industrial, and Enterprise), which covers enterprise AI factories, industrial deployments, sovereign AI deployments, supercomputing, and other deployments not controlled by hyperscalers. Edge Computing will include PCs, workstations, robotics, automotive, gaming consoles, and telecom infrastructure.

Splitting its data center segment into two major sub-segments — hyperscalers and ACIE —makes a lot of sense for Nvidia. Hyperscalers tend to deploy custom silicon, own AI accelerators, or hardware from competitors, which limits Nvidia's growth in this segment. By contrast, there are thousands of participants in the broad ACIE category, virtually all of whom can take advantage of Nvidia's rack-scale platform-based approach, and almost none of them can afford development of custom silicon, which means limitless growth for Nvidia. As a result, Jensen Huang repeatedly emphasized that the ACIE category eventually becomes larger than hyperscale simply because AI is going to become ubiquitous and there are thousands of companies to address.

The 'new' results

As Nvidia will from now on report its revenue split differently, the company had to re-report results across the new market platforms for previous physical years. One interesting observation is that the ACIE segment was outperforming the hyperscale segment till Q2 FY2026, when large CSPs began to deploy Nvidia's GB300 platform for inference, spending tens of billions of dollars per quarter. Now, the ACIE platform has almost caught up.

In the first quarter of its fiscal 2027, hyperscalers bought $37.869 billion worth of hardware from Nvidia, revenue from the ACIE segment reached $37.377 billion, whereas sales of edge computing hardware totaled $6.369 billion. Meanwhile, as noted above, while the bulk of Nvidia's revenue today comes from sales of compute and networking hardware, the company also sells graphics processors, but going forward, those sales will be reported as part of other segments. For example, sales of graphics hardware topped $7.065 billion in Q1 FY2027, which by far exceeds sales of the edge computing segment and strongly suggests that Nvidia now considers graphics as part of multiple newly established market platforms.

Outlook: $100 billion per quarter approaching

For the second quarter of fiscal 2027, Nvidia expects revenue of about $91 billion ± 2%. The company does not expect to ship any AI hardware to China. Gross margins are projected at around 74.9% on a GAAP basis. Nvidia expects GAAP operating expenses of roughly $8.5 billion.

China reportedly banned Nvidia's RTX 5090D V2, an export-friendly version of its top-end RTX 5090 GPU, while CEO Jensen Huang was visiting the country as part of President Donald Trump's state visit last week, the Financial Times reports. The report claims the chip has been added to a list of banned goods at Chinese customs. Huang was a late addition to Trump’s entourage last week, boarding Air Force One in Alaska after he was initially not included on the President’s guest list.

FT cites a document confirming the chip was added to the list, as well as two people "with knowledge of the matter," stating that the card was added to the list on Friday, May 15.

The Nvidia RTX 5090D V2 is a version of the company’s top-of-the-line gaming GPU designed to comply with U.S. export controls. This graphics card, which has less VRAM and lower bandwidth compared to the vanilla 5090, is designed for Chinese gamers and 3D artists. However, AI developers have also been taking advantage of this relatively powerful GPU, especially as they’ve been cut off from Nvidia’s more potent Blackwell-powered AI GPUs.

The most powerful Nvidia AI processors available to Chinese firms at the moment are H200 chips, which Trump approved for export to China in a surprise move in late 2025. But despite that, Beijing refuses to give its AI companies the green light to purchase these GPUs. Instead, the central government wants them to buy domestically manufactured chips, allowing Huawei to leapfrog Nvidia’s market share position in the country.

China’s alleged move to ban the RTX 5090D V2 while Trump and Jensen were still in town, paired with the continuing restriction on H200s, may be Beijing’s signal to the U.S. that it does not need its de-fanged AI chips. This is what the Nvidia chief is worried about — that if Chinese AI firms start ditching the American tech stack, the U.S. will lose its hardware advantage in the AI race. Still, others argue that the United States’ rivals shouldn’t have access to its latest technologies, as they can potentially be used to close America’s technological edge when it comes to defense and the military. Tom's Hardware has reached out to Nvidia for comment on this report, and we'll update this story accordingly if it responds.

Both those for exporting American AI chips to China and those against giving them access to this advanced hardware have valid points, but we can only know which side is right years, if not decades, from now. The Nvidia chief remains hopeful, though, saying on Bloomberg TV, “My sense is that over time, the market will open.”

Nvidia CEO Jensen Huang served as a guest speaker at Stanford’s CS 153 Frontier Systems course and discussed the hardware that powers AI systems today. One of the topics covered in the YouTube session is his stance on granting “adversarial countries” access to Nvidia chips. It’s widely known that the Nvidia chief is against export controls on AI chips, saying that it was a failure and has completely backfired.

Other industry leaders do not take a similar stance, with Anthropic's head, Dario Amodei, comparing selling advanced AI chips to China to selling nuclear weapons to North Korea. Jensen did not take this comparison too kindly, saying it does not make any sense.

“What I’m fundamentally against, and it makes no sense, it makes no sense in this moment, is to compare Nvidia GPUs to atomic bombs. There are a billion people with Nvidia GPUs; I advocate Nvidia GPUs to all of you, I advocate Nvidia GPUs to my family, my kids, to people I love — but I don’t advocate atomic bombs to anybody,” the Nvidia CEO said. “So that analogy is stupid. And so, so if you start from there, you can’t finish a thought — if you start from believing that, you can’t finish the rest of the thoughts.”

Jensen Huang is a firm believer that the world should use the American tech stack and that it would be detrimental to the U.S.’s advantage if it were to block a nation from accessing it. Nvidia has a global advantage in that it’s the largest and most popular manufacturer of AI chips, and its technologies, like the CUDA architecture, drive the progress of most of the world’s AI developers. Keeping this technology widely available to anyone would mean that most of the world's AI—whether developed in the U.S. or built in China — runs on American hardware.

However, critics point out that this could fuel the nation’s adversaries, enabling them to develop and train advanced artificial intelligence for military purposes using Nvidia chips. Jensen said that the Chinese military will avoid U.S. AI tech, much like how the Pentagon does not use Chinese systems. The company also denied providing technical assistance for DeepSeek to improve its training efficiency on models, which were later used by the People’s Liberation Army (PLA). However, public documents revealed that some Chinese universities with deep ties to China’s military-industrial complex acquired Super Micro servers configured with Nvidia A100 AI GPUs.

Unlike nuclear missiles and atomic bombs, AI GPUs aren’t strictly military systems designed for a specific mission. Artificial intelligence is a powerful tool that has applications in science, research, business, and many other industries. However, its flexibility also makes it a dual-use technology, meaning it can be used in civilian and military contexts. It is the latter application that has U.S. policymakers worried, in which the same hardware and AI models can be leveraged by armed forces for operational use, such as intelligence and threat analysis, autonomous systems, simulations, and more. This could erode the U.S.’s technological and military edge and give its adversaries a strategic advantage.

Both sides of the argument have valid points — America has the advantage as the key provider of AI technologies worldwide, and it makes sense to keep it that way. However, it also does not want its rivals to have access to advanced technologies that could accelerate their capabilities and narrow the United States’ lead in defense technologies. Unfortunately, we can only tell which approach proves to be more effective years, if not decades, from today.

President Donald Trump has said that Beijing is refusing to let Chinese companies buy Nvidia's H200 AI chips, telling reporters aboard Air Force One after the conclusion of a two-day summit with Chinese leader Xi Jinping that China "chose not to" approve the purchases because "they want to develop their own," according to Bloomberg.

The remarks came a day after a report claiming the U.S. Commerce Department had cleared roughly 10 Chinese firms to buy H200s, including Alibaba, Tencent, ByteDance, and JD.com, but no chips have shipped.

The U.S. side of the export licensing framework is now largely in place, with distributors Lenovo and Foxconn having also received approval. Under terms formalized in January, each H200 must pass through U.S. territory for third-party inspection before re-export to China, and Nvidia must remit a 25% fee on every sale to the U.S. Treasury.

None of that matters if Beijing won't let its companies place orders. Trump said Friday that the topic came up during his meetings with Xi and that "something could happen," but characteristically offered no specifics. U.S. Trade Representative Jamieson Greer said the same day that any movement on H200 purchases is now up to China.

Commerce Secretary Howard Lutnick made a similar point last month, saying that Beijing has blocked imports in an effort to steer investment toward domestic chipmakers like Huawei. Chinese companies that had placed purchase orders with Nvidia earlier this year later informed the company they couldn’t follow through.

Nvidia CEO Jensen Huang wasn’t on the original delegation list for the Beijing summit but was added at the last minute, boarding Air Force One during a refueling stop in Alaska. His presence raised expectations of a breakthrough on H200 sales, but Trump's post-summit comments suggest the impasse remains. Tom's Hardware has reached out to Nvidia for comment.

Nvidia's $78 billion annual revenue guidance assumes zero H200 recovery from China, but analysts estimate a functioning export framework would restore $3.5 billion to $4 billion in annual revenue from the country, where Nvidia's market share has fallen from roughly 95% to what Huang has described as essentially zero.

Trump also said he discussed AI guardrails with Xi during the summit, describing them as "standard guardrails that we talk about all the time." U.S. officials had previewed the topic ahead of the trip, telling reporters the administration would explore opening a dedicated bilateral channel for regular AI discussions.

The White House last month also unveiled measures targeting distillation attacks, a practice in which Chinese AI developers are accused of extracting outputs from frontier U.S. models built by companies including OpenAI, Anthropic, and Google to train competing systems at lower cost.

Nvidia CEO Jensen Huang is surprisingly not among the business leaders invited to join President Donald Trump as he visits China from May 13 to 15, 2026. One source familiar with the matter confirmed this with Bloomberg, saying that the leather-clad chief of the most valuable company in the world isn’t on the guest list, which includes Apple’s Tim Cook and Tesla’s Elon Musk. These executives represent significant business interests in China, but, for one reason or another, the White House passed over Huang this time.

Jensen is a fixture around Washington, and he’s been included in several of Trump’s state visits. He was part of the presidential entourage in the Middle East and the UK, and he was even praised by the president in London last year, where Trump said, “You’re taking over the world, Jensen.” So, his exclusion from the president’s China state visit is quite a surprise to many, especially as Trump approved Nvidia H200 exports to China in late 2025.

The AI chip maker used to be the driving force of China’s AI industry, that is, until the U.S. blocked its most advanced semiconductors over concerns that American “dual-use” technologies could be diverted towards China’s military programs. Nvidia made several adjustments to let Chinese companies have access to its hardware with the introduction of defanged versions of its latest chips, like the H20, but even that was disallowed in April 2025.

This ban caused Nvidia’s China market share to plummet from a high of 95% to essentially zero, allowing homegrown chipmakers like Huawei, Cambricon, Alibaba, and Baidu to gain ground as they fill the vacuum left behind by the American chipmaker. Even though Trump eventually allowed Chinese companies to purchase H200 chips once again (provided Nvidia secures a license to sell them to a firm), Beijing stepped in and told its customs officers to stop the chips at the border. It has been almost six months since the White House gave Nvidia the go-signal to sell the H200, but U.S. Commerce Secretary Howard Lutnick said that the company has yet to sell a single H200 AI GPU to China.

Even though Beijing understands that its AI companies need advanced hardware, like Nvidia’s Blackwell and upcoming Vera Rubin chips, it also needs to balance this with its desire to have a domestic semiconductor industry that can compete against what the U.S. offers. This is likely the reason why Nvidia’s H200 chip is still in regulatory limbo. Nevertheless, China’s access to the latest AI chips has always been a sticking point in its trade negotiations with the U.S, Bloomberg reports. American Enterprise Institute fellow Ryan Fedasiuk also told the publication that Huang’s absence from Trump’s entourage is a “strong signal” to the CCP that Washington will not budge on its stance when it comes to these high-end AI chips.

With the prices of memory and storage at record highs, the amount of laptop you get for the money has shrunken significantly. Now is a great time to start looking for a laptop deal during Amazon Prime Day 2026. We've used our knowledge and experience, informed by our extensive testing and benchmarking program, to find the best available gaming and productivity laptops on sale for under $1,000 to help you find the right laptop for you. We're updating this page constantly with the best deals available, but be aware that these deals often expire quickly, so you'll need to act fast.

A giant desktop gaming PC isn't for everyone! Price, space, and portability are negatives of a giant desktop gaming rig. These are things a compact and powerful gaming or productivity laptop can help to solve, especially if you can get your hands on one for under $1,000. There are, of course, obvious compromises that you'll need to make if you're going to try to find a budget machine. Things like dedicated graphics, the amount of onboard RAM, storage space, and even the size and quality of the screen and chassis.

Apple has jumped to the rescue with the likes of the MacBook Neo, but Windows users haven't been as lucky as of late. For gaming laptops, you're going to be looking at the lower end of GPUs from Nvidia's RTX 5050 and even graphics chips from older generations. The same goes for the processors used. Expect to see previous-gen CPUs in lower-priced laptops that are available for under $1,000.

Best Gaming and Productivity Laptops Under $1,000: Quick Links

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Best Gaming and Productivity Laptops Under $1,000

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Gaming laptops can be pricey, and in the past few years, they have only gotten more expensive. The components inside laptops have gotten more expensive, the market below $1,000 has effectively been decimated, and finding a good deal is harder than ever. But we're still testing, and while the goal posts of what defines a budget gaming laptop may be a bit more expensive than they used to be, there are still ways to save.

At Tom's Hardware, we test many gaming laptops every year at a range of prices with different features and parts, so we know what to expect at every price point, no matter what your budget. While even the budget gaming laptops may not be cheap, we can still point out where you get the most for your money. We thoroughly benchmark all of the best budget gaming laptops in numerous games, extensively measuring gaming performance under a wide range of graphical conditions to suss out the best cheap laptops on the market.

Most gaming laptops under $1,500 will use Nvidia's GeForce RTX 5050 and RTX 5060 graphics cards. Many of them will use the latest Intel Core Ultra or AMD Ryzen mobile processors, though sometimes you'll still find last-gen options. Above $1,500 (which, unfortunately, is still on the low end with all-new components these days), you should have the latest. That being said, don't cut corners so far that you settle for 8GB of RAM or just 256GB of storage. Those are outdated specs for gaming laptops.

With a budget gaming laptop, you'll be able to play most games — even graphically intensive ones — on medium or high settings, if not better. If you're playing lighter games, like esports, you should still be able to achieve high frame rates.

Prime Day Exceptional Budget Gaming Laptop deal

Here is a few standout deal from the Prime Day event, which is currently taking place. Our list of best overall picks continues below.

Best Budget Gaming Laptops You Can Buy

Best budget gaming laptop overall

The Acer Nitro V 16S AI is, as of this writing, typically selling around $1,500. This laptop is great for those who are willing to trade off some gaming performance for a bright and colorful screen and a ton of ports, including a microSD card slot.

Those ports, paired with a speedy storage drive in our tests, make the Nivro V 16S AI a solid productivity machine alongside one that can play most games. Acer is using an RTX 5060 with an 85W graphics card, so it's not the most performant system out there, but it's well-balanced if you're going to use just one laptop for gaming, work, or school.

The 16-inch, 1920 x 1200 IPS screen goes up to 180 Hz, allowing for smooth gameplay for esports and indie games. Our system came with a 1TB storage drive, which should hold a few games, and there's room to add another inside. It also came with 32GB of RAM, which should be a bit future-proof.

There is a bunch of bloatware that you'll probably want to uninstall, and the webcam is just 720p.

Read: Acer Nitro V 16S AI review

Best budget gaming laptop for work and play

We had previously seen this laptop as high as $1,800, but lately it's been on sale closer to $1,500. The machine is another good mix of productivity and gaming. Like many other budget systems, it's using an 85W GPU (in this case, an RTX 5070), which means you won't get the most powerful gaming performance.What it does allow for, however, is strong battery life, lasting 9 hours and 13 minutes on our test. We also found the keyboard and touchpad to be quite comfortable.

The Ryzen AI 7 350 is a recent chip, and one that offers strong productivity performance, should you be using this system for work other than just gaming.It would have been nice to see Wi-Fi 7 at this system's full price, though on sale, Wi-Fi 6E is more forgivable. That being said, the display and audio are both middling, so this may be best if you use a monitor or speakers to bump up your experience.

Read: Gigabyte Aero X16 review

Best for battery life

If you want something a bit more minimalist, the Alienware 16 Aurora, the gaming brand's stripped-down machine, may work for you. This one has been consistently available.

The Aurora has an attractive chassis that mixes its plastic body with an alumium lid. The indigo color seems almost black, but has a navy shimmer in the right light.

The biggest benefits we saw were in the 16-inch, 2560 x 1600 IPS display, which goes up to 120 Hz. That screen was brighter and far more vivid (112% of sRGB color volume, 312.2 nits) in our measurements compared to other budget machines.

We also appreciated the Aurora's 96 WHr battery, which helped the system last for 9 hours and 41 minutes on our battery test.

The 80W RTX 5060 is fairly low-power, which might help with the longevity, but means you'l have to set your expectations while gaming. Additionally, the storage could be faster, though you could consider swapping that out down the line.

Read: Alienware 16 Aurora review

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What to Expect From the Best Budget Laptops for Gaming

We took Nvidia's RTX Mega Geometry technology through a series of tests in Alan Wake 2 and the RTX Bonsai Diorama Demo to see how this tech reduces VRAM consumption and eliminates visual artifacts, thus helping pave the way to photorealistic real-time graphics.

In 2018, NVIDIA announced its GeForce RTX line of graphics cards based on the Turing architecture, which would allow for hardware-accelerated real-time ray tracing. In November of that year, Battlefield V became the first title to support real-time ray tracing using the Microsoft DirectX Raytracing API (DXR). The game only supported one ray-traced effect – ray-traced reflections.

In 2019, Control launched with support for multiple ray-traced effects – RT reflections, RT transparent reflections, indirect diffuse lighting, RT contact shadows, and RT debris.

Later, we would see full ray tracing – or path tracing – in games like Quake II RTX, Cyberpunk 2077, and more. In contrast to the hybrid ray tracing solution used in some games, path tracing accurately simulates light in a scene. It does this by sampling a wide range of potential light paths a single ray can follow. This method is also used by the film industry to generate photorealistic visuals in movies.

Path tracing is present in a number of modern games, where it can significantly enhance lighting realism depending on the implementation. In addition to this enhanced lighting, there have also been technological advancements in geometric complexity and density for games. Unreal Engine 5’s Nanite is a virtualized geometry system that can render high-quality and high-density assets in real time with pixel-scale detail and high object counts. Other game engines have similar technologies, such as Micropolygon Geometry in the Anvil Engine.

These advancements in geometric detail require new techniques to ray trace full-quality geometry. That’s where Nvidia's RTX Mega Geometry technology comes in.

What is RTX Mega Geometry?

The Microsoft DXR API was designed years ago, before the level of geometric complexity that can be found in modern games. In DXR, geometry is represented using a Bounding Volume Hierarchy (BVH), which can become expensive to rebuild in dynamic scenes with dense geometry and countless complex animated objects. Fully ray tracing such geometry may require frequent BVH updates, placing significant strains on performance. As a result, developers often rely on lower-quality proxy meshes for ray-traced effects. These simplified representations contain only a fraction of the original detail, leading to artifacts such as incorrect self-occlusion and low-fidelity shadows and reflections.

RTX Mega Geometry is a rendering technology that can significantly increase geometric detail in ray-traced games, allowing full-fidelity geometry to be traced without traditional trade-offs. RTX Mega Geometry adds an optional Cluster Acceleration Structure (CLAS), which generates batches of up to 256 triangles and is designed to be GPU-driven. This not only dramatically speeds up the process of rebuilding the BVH, but it also reduces the CPU overhead associated with BVH management.

While Mega Geometry is supported on GPUs as far back as the RTX 20-series, the RTX 50-series has purpose-built hardware for the technology. The fourth-generation RT Cores in Blackwell GPUs add two new engines: a triangle cluster intersection engine and a triangle cluster compression engine. Together, they double the ray-triangle intersection rate compared to third-generation RT Cores, while also reducing VRAM usage by several hundred megabytes when ray tracing dense geometry.

The benefits of this technology vary depending on how it’s used. When applied to existing assets, it can improve performance and reduce VRAM consumption. Alternatively, it can eliminate the need for the compromises mentioned earlier – such as proxy meshes – enabling significantly higher-fidelity results without the associated visual artifacts. The latter use case comes at the cost of performance.

RTX Mega Geometry in Alan Wake 2

Alan Wake 2, released in October 2023, showcases a range of modern rendering technologies. It uses mesh shading to handle highly detailed, high-density geometry and supports path tracing on PC, making it an ideal candidate for Mega Geometry.

Mega Geometry was added to the game in title update 1.2.8 in early 2025, and Remedy opted to use it on existing assets to optimize performance and VRAM usage, as opposed to further increasing geometric complexity. Testing on an RTX 4090 back in early 2025, I compared build 1.2.8 to the previous 1.2.7 release, which did not use Mega Geometry, and observed VRAM savings of about 1 GB along with a 13% performance increase at both native 4K and 4K with DLSS Quality, with max settings and path tracing enabled. These numbers are roughly in line with the figures shared by NVIDIA at GDC 2026.

RTX Bonsai Diorama Demo

The RTX Bonsai Diorama Demo released by NVIDIA was developed in the NVIDIA RTX Branch of Unreal Engine (NvRTX) 5.6, and showcases RTX Mega Geometry, path tracing, RTX Dynamic Illumination (RTXDI), DLSS Super Resolution, DLSS Ray Reconstruction, and DLSS Frame Generation. The main focus of the demo is the fully path-traced Nanite meshes in real time.

The great thing about the demo is that you can turn Mega Geometry on and off to compare image quality and performance. So that’s exactly what we will do.

The debug visualization in the screenshots below illustrates the precision of Mega Geometry when path tracing Nanite meshes and the substantial increase in triangle count when it is enabled.

Because Mega Geometry adds full quality Nanite geometry to the BVH, ray-traced shadows no longer exhibit the visual artifacts that are present in Lumen, such as missing or incorrect shadows. In the comparison below, you can see that every object in view has accurate, pixel-perfect shadows with Mega Geometry enabled.

Similarly, reflections are no longer plagued by the issues that result from using low-quality proxy meshes. In the comparison below, you can see missing leaves from the reflection within the center mirror when Mega Geometry is disabled. With Mega Geometry enabled, you get the full Nanite mesh.

Additionally, pay attention to the tree on the far left. With Mega Geometry off, you get incorrect self-occlusion. This is entirely resolved with Mega Geometry.

The technology clearly improves image quality, but how does it perform?

It is important to note that the level of geometric detail and density observed above with Mega Geometry enabled was simply not feasible in Unreal Engine 5 prior to Mega Geometry, even on high end GPUs like the 5090. This level of fidelity could not be attained at an acceptable level of performance. Having said, while Mega Geometry makes this possible at playable framerates on high-end GPUs, path tracing such high-fidelity meshes is still extremely demanding.

Test system

• AMD Ryzen 7 9800X3D
• 64GB (2x 32GB) 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 26200.8246)
• Nvidia Driver 596.21

On the 5090, the performance cost of enabling RTX Mega Geometry is 23% at 1080p, 24% at 1440p, and 21% at 4K. At a rendering resolution of 1440p or below, performance is above 60 FPS. This gives you the option of using frame generation to further increase motion clarity without significantly impacting perceived latency. Typically, you want to use frame generation with a base framerate of at least 60 FPS – ideally higher – so that the game still feels responsive.

On the RTX 5070, the performance cost is 27% at 1080p, and 26% at 1440p. Unfortunately, 60 FPS with Mega Geometry is not possible in this demo on the 5070 unless you use frame generation or DLSS with an internal rendering resolution below 1080p. This result is not entirely surprising, as standard path tracing is already extremely taxing on this GPU.

We included the 5060 here because the RTX Bonsai Diorama Demo developer guide listed this as the “recommended GPU.” Clearly, that must include the use of DLSS Super Resolution and Frame Generation, because without them, the 5060 averages below 30 FPS in this demo with Mega Geometry enabled. Indeed, with DLSS Super Resolution and Frame Generation at 1080p, the 5060 can exceed 100 FPS, but the resulting experience suffers in both image quality and input latency.

The Future of RTX Mega Geometry

At GDC 2026, NVIDIA announced that Mega Geometry would be implemented in the upcoming 2026 titles Control Resonant and The Witcher 4.

During their Future of Path Tracing presentation at GDC 2026, NVIDIA highlighted the RTX Mega Geometry foliage system coming to The Witcher 4.

The new level-of-detail (LOD) system for foliage selectively updates only the relevant parts of the scene based on camera movement, and represents level-of-detail in a manner that is efficient to ray trace. This is done without exhibiting traditional LOD pop-in.

The system leverages Opacity Micromaps (OMMs) for distant LODs, which are used as a simplified representation of the geometry that is lightweight in memory. On the RTX 40-series and 50-series, OMMs are hardware-accelerated.

Later in the presentation, NVIDIA showcased the system in a demo featuring a vast 5x5 km forest composed of roughly 60 million plants spanning over 200 species, including around 1 million trees. Notably, the entire scene runs without streaming, with all assets resident in memory. Every element is represented as full geometry – down to individual pine needles – with some of the largest trees reaching approximately 10 million polygons each. The scene is rendered with fully dynamic, path-traced lighting, and the tree assets were provided by CD PROJEKT RED.

What was surprising was the level of performance achieved in this demo. On the RTX 5090 at 4K using DLSS Quality mode (internal rendering resolution of 1440p), the demo ran at 80 FPS. This is nearly 18% faster than the Bonsai Diorama demo ran on the 5090 at 1440p.

On the RTX 4070 at 1440p using DLSS Quality mode (internal rendering resolution of 960p), it ran at about 58 FPS.

RTX Mega Geometry represents a meaningful step toward truly photorealistic real-time graphics. With advancements like the new LOD system for foliage and ongoing performance optimizations, it has the potential to enable scenes of unprecedented geometric complexity that can be rendered with fully dynamic, path-traced lighting at playable framerates on modern hardware.

A Bloomberg investigation on Friday shed some additional light on the indictment of Supermicro executives and employees tied to a $2.5 billion smuggling of restricted hardware to China. As it appears, the group allegedly used a Thailand-based government-related entity to route restricted Nvidia AI GPUs to none other than Alibaba itself, whose AI ambitions can easily absorb hardware worth far more than a couple of billion dollars.

Supermicro's alleged violations of U.S. export controls that ended up as shipments of restricted Nvidia AI accelerators to China and Russia have caught a lot of attention in recent years, as billions of dollars worth of hardware were shipped to American foes. The new Bloomberg report claims that Thailand-based Obon Corp. is the previously unnamed Southeast Asian intermediary referenced in the indictment, which claims that some of the hardware ultimately reached Alibaba.

The intermediary described in court documents as 'Company-1' was allegedly Obon, a Bangkok-based company connected to Thailand's sovereign AI initiatives, according to Bloomberg. The new firm further states that some of the systems sold through OBON may have gone to Alibaba, although the Chinese technology giant denied any involvement and said it had never deployed prohibited Nvidia hardware in its data centers.

The report notes that the servers reportedly included Nvidia H200-based systems, which fall under U.S. export restrictions intended to prevent China from obtaining top-tier AI compute hardware without government approval. By now, H200 has been approved for exports to China, though it has not reported selling them to China officially.

The original indictment accused Supermicro co-founder Yih-Shyan 'Wally' Liaw, Supermicro Taiwan sales manager Ruei-Tsang 'Steven' Chang, and third-party broker Ting-Wei 'Willy' Sun of organizing a large-scale diversion network that rerouted Nvidia Hopper-based AI servers. Prosecutors alleged that the group used a Southeast Asian front company, falsified documentation, and maintained inventories of dummy servers to conceal actual shipments of systems containing advanced Nvidia GPUs into China.

The alleged perpetrators used hair dryers to transfer serial-number labels from legitimate servers onto empty chassis to deceive inspectors and install the restricted hardware afterward, according to the allegations. The U.S. authorities estimate that the operation generated roughly $2.5 billion in sales beginning in 2024. Liaw and Sun were arrested, while Chang continues running for his life.

In general, the case raises concerns about the effectiveness of export-control enforcement across Southeast Asia. Nonetheless, as long as a market like China exists, the supply will always be there.