Intel's shares plunged 30% on Friday, wiping out nearly $150 billion in market capitalization in a single day, the largest single-day loss in the company's history. The decline followed a disappointing financial outlook, largely driven by an anticipated drop of more than 20% in sales at Intel's client computing group (CCPG), the company's main cash cow. The declines quickly spread across the semiconductor industry. Although losses elsewhere were nowhere near as severe as Intel's, approximately $1 trillion in semiconductor market capitalization was wiped out on Friday, according to intraday estimates by Benzinga.

Fire sale

The PHLX Semiconductor Sector Index (SOX), which tracks the stock performance of 30 major semiconductor companies, is one of the key indicators of the industry's financial health. On Friday, the index plunged 9.14%, or 1,052.82 points, to 10,465.38 points as of 2:31 PM ET, as Intel's disappointing outlook triggered a massive selloff across the semiconductor industry.

Intel was by far the biggest loser, as other chip-related stocks, while Arm (-12.68%), AMD (-12.48%), Qualcomm (-12.14%), Applied Materials (-8.73%), ASML (-8.13%), Lam Research (-8%), Micron (-7.28%), and Broadcom (-7.1%) suffered considerably less. Then again, while Nvidia lost 5.66% of its market cap, this translates to around $270 billion, which is a massive amount of money. Paradoxically, Nvidia lost more market capitalization in absolute dollar terms than Intel.

In an unexpected turn of events, the downturn extended to server manufacturers and cloud giants too, as Dell (-12.67%), HPE (-8.10%), Supermicro (-6.96%), and Oracle (-6.88%) lost nearly 7% to 13% of their value. Reuters noted that investors increasingly question the scale of capital investments required to expand AI infrastructure as well as the sustainability of that spending.

Gloomy outlook

Intel’s client computing and physical AI group (CCPG) generated $8.1 billion in revenue during Q3 2026, down 5% year-over-year and 9% sequentially. Weaker demand and increased competition reduced client processor shipments by 14% year-over-year, which was partially offset by a 9% increase in average selling prices. CCPG accounted for nearly half of Intel's revenue of around $16.5 billion and the company's main source of cash. As strong demand for server processors only partially offsets declining client sales, Intel guided its Q4 revenue to be between $15 billion and $16 billion.

Intel expects the client market to deteriorate further in Q4 2026 and into 2027 as elevated memory prices and shortages of other components impact PC prices and demand. In general, Intel expects the client PC market to decline 10% in 2027 compared to 2026, which will inevitably have an effect on CCPG performance. While Intel expects its data center business to continue growing in 2027, industry-wide supply constraints will limit its ability to fully capitalize on demand.

2026 has been a mixed bag for Intel so far. On the one hand, the company achieved its highest market capitalization ever — $673.43 billion in mid-June — on growing sales of data center CPUs, strong sales of client products, and a return to profitability (if the $12.5 billion non-cash accounting charge associated with shares issued to the U.S. government is excluded). On the other hand, the company's capitalization has dropped by nearly 50% to $338.91 billion since mid-June (with $148.68 billion in just one day), as investors began to realize that the performance of Intel's CCPG heavily depends on memory prices, as customers and businesses tend not to like overpriced systems. Yet on the other hand, now that Intel sells fewer client processors, it can sell more expensive data center CPUs.

What about Apple?

Surprisingly, Apple (-1.66%), which only sells client products, was nearly unaffected by the performance of Intel's client computing group, as investors probably believe that the world's largest supplier of consumer electronics is more immune to memory prices than Intel. Ironically, if we count the A-series SoCs used in iPhones (which tend to outperform mainstream laptop CPUs), Apple sells substantially more processors than Intel, making Apple by far the world's largest supplier of microprocessors. Despite this, Apple's shares were largely unaffected by the semiconductor selloff.

There are several reasons for this distinction. Firstly, Apple's business model is fundamentally different. Intel sells processors to PC manufacturers, whereas Apple designs its own processors and sells them as part of finished products. Consequently, Apple captures revenue from the entire device rather than just the processor. Secondly, the two companies face different demand dynamics. Intel depends heavily on the PC market, while Apple's iPhone business follows the smartphone replacement cycle. Rising memory prices could affect both, but not necessarily to the same extent and at the same time.

There is an additional irony: Apple is also a major customer of TSMC, so its processor supply chain overlaps with those of AMD, Intel, and other semiconductor companies whose shares declined sharply.

While we should not directly compare Apple and Intel, the comparison illustrates that investors were not necessarily abandoning companies that design or use semiconductors, but were rather concerned about the profitability and growth prospects of these high-tech companies. And if we take a look at the situation from this point of view, the whole thing will start looking completely different.

Anthropic spent less than a third of its $8.9 billion first-half compute bill on serving customers, with most of the rest going into training, research, and running Claude internally, its S-1 filing shows. It has meanwhile signed up for hundreds of billions of dollars more in TPU and GPU capacity. By our math, it has meanwhile signed up for roughly $800 billion more in TPU and GPU capacity, and revenue per compute dollar jumped from $0.40 in Q1 2025 to $2.08 in Q2 2026, which the company links to capacity purchased 12–18 months ahead.

Anthropic’s IPO is likely to beat that of rival OpenAI, which filed confidentially before CEO Sam Altman said its own won’t come this year, amid widespread doubts about an AI bubble. Whether AI labs can cover what it costs to serve their models is an open question.

Anthropic appears to do so easily: it spent $2.4 billion serving customers in the first half of the year, versus $16.3 billion in revenue. Paying for what it has on order is more difficult. Its five compute deals with the biggest stated amounts would cost an estimated $103 billion a year on average once delivered, more than twice its revenue at Q2’s pace of about $46 billion a year. The company also warns that margins may compress as new hardware lands ahead of the revenue it will support.

The company has three main costs: the cost of revenue, which is the inference cost of running Claude for paying customers; R&D, which is mostly compute for training and research into new models plus any internal use; and sales and marketing, which covers the cut taken by channel partners and cloud platform resellers.

Comparing the first half of last year to this year’s, cost of revenue is up about 2.3x, but with revenue up 14x, that means Anthropic keeps an estimated 85 cents for every dollar after serving costs, up from just 12 cents. R&D is up about 5 times, with 66% or more of the compute going to it, and that’s the main source of its operating loss. Sales and marketing is up 16x, and doesn’t show up in cost of revenue, but its partner fees and marketing would lower what it keeps to 66 cents a dollar. The trend here is that serving Claude now more than covers its costs.

Serving has kept getting cheaper for customers since June: in September, Anthropic’s Opus 5.5 model cut costs per task by about 40% versus Opus 5, says the company, and Fable 5.1 cut the cost of typical workloads by about 25% against Fable 5; each came from “a combination of a lower price and improved efficiency,” made “while preserving our margins.”

As for compute, which runs through all three costs, Anthropic runs it as “a single, shared resource across all workloads” and doesn’t disclose how it decides the split between training, research, and serving. Serving was limited, as the company has “consistently operated in a compute-constrained environment where customer demand exceeds available compute,” which suggests serving costs were muted by a lack of supply, not just efficiency.

Anthropic runs a “multi-chip compute architecture across AWS Trainium, Google TPUs, Nvidia GPUs, and AMD GPUs,” without giving any percentage splits or GW measurements. For TPUs, it has five-year equipment leases with Broadcom for “TPU-based compute capacity,” with rent of “approximately $161.2 billion excluding interest”; some of that capacity came online this year, with more from 2027. Another $114.5 billion or more is with Google “between April 2026 and July 2033,” with more from Google and other TPU providers from 2028 to 2031, estimated to be in the $125–$150 billion range.

Trainium comes through Amazon, with a deal for “at least $110.0 billion between May 2026 and April 2036,” though the filing doesn’t split AWS spend by chip. Nvidia GPUs come through a series of deals, including “up to $120.5 billion … extending into 2029” with SpaceXAI, “at least $44.9 billion” extending into 2033 with Microsoft, “up to approximately $44.6 billion” also into 2033 with Nscale, and about $41.3 billion into 2034 with Lambda. There is also an AMD hardware supply agreement which, in aggregate, may “exceed $20.0 billion” if Anthropic takes the full initial capacity. These deals each have their own conditions for termination.

Anthropic’s minimum purchase commitments, which exclude equipment leases such as Broadcom’s, have gone from about $55 billion at the end of last year to about $265.6 billion by the end of Q2 this year. Since then, it has signed about $245 billion in new minimums, leases included, and TPUs are the biggest line overall. The Nvidia capacity, Microsoft’s aside, is also the easiest for Anthropic to walk away from.

With all these multi-year commitments, bought well ahead of delivery, expenses are paid and recognized “as compute becomes available to us,” the company says. That compute base “did not fluctuate with in-period demand,” so revenue per compute dollar increased as demand surged. When demand outruns that capacity, Anthropic buys short-term compute, which “typically carries a higher cost per unit.”

Our $103 billion estimate is straight-line, spreading each deal evenly over its term except SpaceXAI, which is at its full monthly rate, while payments ramp up as capacity is delivered. Also not included in the estimate is interest on the Broadcom leases. Compute also does not necessarily have to earn revenue, especially in R&D.

The filing has many blanks, such as the total commitment figure, the contractual obligations table, Q3 revenue, and Run-Rate Revenue, which an amended S-1 would normally fill in before pricing. No date for that has been given. Microsoft’s minimum starts in November, and SpaceXAI’s full delivery is expected in December, with non-cancelable periods ending in January and March 2027, after which either side can cancel on 90 days’ notice. More Broadcom TPU capacity and AMD’s first tranche follow next year, by which point most of these deals will be billing.

A new "Advanced Performance Extensions (APX)" option has been spotted in a version of Windows 11 made available to Windows Insiders on October 23, with the feature set to enable a boost in application performance on compatible chips. At the moment, those chips don't exist. But when they do, this feature is the one that you'll want to flick on if you're using one of them. The new toggle was reported by Neowin after it was first spotted by a poster on the X social network. The feature debuted in build 29295 as an Experimental build, so it's unlikely that it will make its way to the version of publicly available Windows 11 anytime soon.

Intel announced APX back in 2023, confirming that it features 16 additional general-purpose registers and three-operand instruction formats with a new data destination register for many integer instructions. Doubling the number of general-purpose registers from 16 to 32 will allow code compiled with APX to run with 10% fewer loads and 20% fewer stores than Intel 64's baseline, says Intel. APX has been available in the GCC compiler since version 14, with subsequent versions up to GCC 17, which is targeting a 2027 code freeze, adding additional support. LLVM and MSVC have preliminary support, as well. Although enablement has been going steady for the past two years, developers will still need to recompile their applications with the proper flags for APX-capable CPUs to leverage those instructions.

Not that there's any real need to rush just yet. The fact that no APX-capable chips are on sale yet means that enabling the feature in Windows 11 build 29295 does nothing currently. But it's clear that Microsoft is getting its ducks in a row ahead of time. Intel's Nova Lake Core Ultra 400-series chips are expected to be the first to feature APX support, but they won't break cover until early 2027. Even then, it's likely that the 28-core version will debut first, with the 52-core model made to wait until later in the year. These are consumer chips, of course, with Intel's Xeon 7 'Diamond Rapids' bringing APX support and up to 256 cores to the data center, also in 2027.

The good news is that you might not have to buy a new chip to enjoy improved Windows 11 performance. Five years after Windows 11's debut, Microsoft has already said that it's working to make its operating system play more nicely with machines with just 8GB of RAM. But what Microsoft gives with one hand, it soon takes away: an expansion of the Windows 11 Memory Integrity feature will reduce gaming performance on some systems.

AMD Director of Client Product Management Travis Kirsch sat down with a Japanese publication to share the backstory of the AMD Ryzen 7 5800X3D and its relaunch this year. Kirsch told MyNavi Tech+ [machine translated] that AMD CEO Lisa Su was one of the proponents of bringing back the groundbreaking X3D processor that first debuted in April 2022.

While some may think this was a simple relaunch of a four-year-old processor, the company had to do extensive re-engineering and update its manufacturing process with TSMC just to bring it back. The decision to relaunch it was well-timed, too.

While the world is suffering from extremely high DDR5 memory prices when it finally arrived in the middle of 2026, Kirsch said that “this was planned before changes in the memory market occurred, not as a countermeasure to DDR5 shortages,” and that it was “the final gift to local users who have used our AM4 for nearly a decade, offering systems that use DDR4 the last change to upgrade their PCs.”

Beyond the Ryzen 7 5800X3D, the Japanese publication also touched on AMD’s value offerings, or lack thereof. Four Ryzen 3 processors are available new today—one for AM5 and three for AM4—which raises the question of whether AMD is abandoning the entry-level market.

Kirsch said that while the company aims to offer a product for every price point, AMD is mostly focused on the premium, high-performance gaming market — we see this in the October Steam Survey results, with AMD closing in on Intel at 48.4% CPU share. As for the affordable CPU market, he said it’s no longer as big as it used to be, as laptops have taken over this segment.

Of course, any discussion with a tech executive these days would almost always touch on the memory chip shortage. “…there are things we can control and things we cannot. Market price trends are the result of everyone moving (and there’s nothing we can do about it),” Kirsch said.

“We are simply focused on providing consumers with choices in any situation. This is to ensure that consumers have the opportunity to purchase the best AMD PCs, regardless of the price.”

We often criticise companies for misleading marketing, which typically falls in the direction of deceitful overpromising. With the Ryzen 5 5500F, we have the opposite problem. Its name and branding undersell what AMD is offering here. It’s a marked improvement over the base Ryzen 5 5500, giving AMD better standing among the best budget CPUs.

The 5500F is a Zen 3 CPU from the Vermeer family of chips, packing six cores, 12 threads, and a boost clock of 4.4 GHz. It’s modest by the standards of the best CPUs for gaming, but it also comes in at a suggested retail price of just $100. Those prices have drifted up toward $120, though hopefully they’ll settle down around list price before long.

Along with a 200 MHz jump in boost clock speeds over the 5500, the 5500F critically comes with access to PCIe 4.0. The original 5500 came from the Cezanne family of APUs, which all use monolithic dies and are limited to PCIe 3.0. Although the 5500F lives in the Vermeer family alongside the main Zen 3 stack, it’s still limited to the 16 MB of L3 cache that characterizes Cezanne (Vermeer chips have access to 32 MB of L3 otherwise).

The chip squarely targets Intel’s Core i3-14100F, a quad-core CPU available for around $100 that offers 11% better gaming performance at 1080p on average compared to the base 5500. The new 5500F tightens that gap to just 2.9%, and it manages to outclass Intel in multithreaded performance while offering a 10% average jump over the base 5500.

AMD Ryzen 5 5500F specifications and pricing

AMD gave the Ryzen 5 5500F a bad name. The “F” suffix across both AMD and Intel is typically used to note chips that lack integrated graphics. And indeed, the Ryzen 5 5500F does lack integrated graphics. But so does the Ryzen 5 5500. In reality, the Ryzen 5 5500F isn’t a re-released CPU with the iGPU sliced off, as F-series processors usually are, but rather an updated Ryzen 5 5500 that comes with better specs and, in turn, better performance.

If there’s any chip that falls in the bucket of a re-released CPU with the iGPU cut off, it’s the original Ryzen 5 5500, not this new F-suffix variant. The Ryzen 5 5500 comes from the Cezanne family of Zen 3 CPUs. These chips use the Zen 3 microarchitecture, but they have only 16MB of L3 cache and are limited to PCIe 3.0. Out of the full Cezanne family, the Ryzen 5 5500 is the only chip that isn’t either an APU like the Ryzen 5 5600G, or a laptop chip.

The newer Ryzen 5 5500F is from the Vermeer family, the same as other Zen 3-based desktop CPUs like the Ryzen 5 5600X. That brings with it an update to PCIe 4.0, which is a huge boon for GPU and storage performance, as well as a bump from a maximum boost of 4.2 GHz on the 5500 to 4.4 GHz on the 5500F.

Although the Ryzen 5 5500F falls in the Vermeer family, it still carries some Cezanne DNA. It’s the only Vermeer chip to have 16 MB of shared L3; all other Vermeer chips have 32 MB of L3, at least, with X3D options scaling higher. Both families retain the same L1/L2 setup, naturally, as they share the Zen 3 microarchitecture.

Otherwise, the Ryzen 5 5500F retains the 65W TDP, and 88W platform maximum, and it comes bundled with AMD’s Wraith Stealth cooler. The Wraith Stealth cooler is plenty to keep the Ryzen 5 5500F cool under load, saving you some money on an aftermarket CPU cooler.

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The Ryzen 5 5500F is AMD’s best budget gaming CPU right now, at least assuming you don’t already have a kit of DDR5 laying around. That was also true of the 5500, though begrudgingly. Deals on CPUs like the Ryzen 5 7600X are common, but the exorbitant cost of a kit of DDR5 right now nullifies any real savings there. Although the 5500F is still second chair to Intel’s Core i3-14100F, the battle between the two is much closer now. Plus, the 5500F has access to PCIe 4.0, solving a big sticking point with the original 5500 and its PCIe 3.0 limit.

With the Core i5-14400 and Core i3-14100 in the charts below, we tested both with DDR4 and DDR5. As we saw in our Raptor Lake Refresh DDR4 comparison recently, the newer memory standard brings about a 15% improvement in average gaming performance at 1080p. The DDR5 numbers are mainly here for context. The true battle is between DDR4 platforms, given the high cost of DDR5.

We followed the same testing procedure for this review as we do with any other. We have full platform details at the end of this review. For gaming, we used the RTX 5090 FE and tested at 1080p with a mixture of High and Ultra settings. Undoubtedly, some of our readers will have feedback about the decision to use such a high-performance GPU with such inexpensive CPUs, but this is our standard process for all CPU testing, and the choice to use the RTX 5090 is less impactful than you might think.

As you can see from our $100 CPU shootout, where we tested the 5500 and 14100F with an RTX 5090 and with an RTX 4060, average scaling was largely the same between the two GPUs, with only the baseline performance moving down on the RTX 4060. You’re going to remain CPU-bound with these chips and just about any modern gaming graphics card. Using the RTX 5090 allows us to take these results and compare them all the way up the stack rather than throw them in the bin.

With an extra boost in clock speed and access to PCIe 4.0, the Ryzen 5 5500F comes out 8.6% ahead of the 5500 in our 16-game geomean at 1080p. It’s now just 2.8% behind the Core i3-14100F, though. As we’ll see throughout some of the individual game tests, the four-core setup of the Core i3-14100F is a real limitation. 1% low performance jumped 11.7% from the 5500 to 5500F, as well, resulting in smoother performance.

The Ryzen 5 5500 occupies the bottom of our chart, and that’s mainly due to availability. There aren’t a ton of CPUs available around $100, unless you’re interested in spending $98 on a brand new FX-8300 (don’t). It’s a battle between the Core i3-14100F and Ryzen 5 5500F at this price. In order to step up to that next tier of performance, you need to spend around $150, which is a hotly contested area between DDR4 options like the Core i5-14400F (we only had the more expensive, non-F version on hand) and Ryzen 5 5600, and DDR5 options like the Ryzen 5 7600X.

AMD has brought 3D V-Cache down the Zen 3 product stack, all the way down to the Ryzen 5 5500X3D, though you’ll spend about twice as much on that CPU as the Ryzen 5 5500F or Core i3-14100F.

Still, both of these chips play a great role in a new budget gaming build right now if you have future upgrade aspirations. Compared to the Ryzen 7 5800X3D and Core i7-14700K — our recommendations for gaming on these platforms — you can save around $200 up front and put it toward a nicer graphics card. Intel’s platform has the additional flexibility of a future DDR5 upgrade with a new motherboard, as well.

Between the Core i3-14100F and Ryzen 5 5500F, Intel still holds a small edge in performance. Given how CPU-bound we are, that edge isn’t big enough to sway a buying decision, but the price is. The Ryzen 5 5500F has a recommended price of $100, but we haven’t seen it sold for less than $120. Neither the slightly higher price nor slight performance disadvantage are enough to sway things on their own, but together, they hurt the Ryzen 5 5500F’s place in the $100 CPU bracket.

That comes through clearly in our value geomean, where the Ryzen 5 5500 actually provides a better value than the new 5500F, due to the fact that it’s held onto its $90 price. The Core i5-14400 looks unsurprisingly bad here due to its $208 price tag. The Core i5-14400F is available closer to around $150 though, and it should provide identical performance with a discrete GPU.

With temperature and power, you can see the Ryzen 5 5500F takes better advantage of the 65W thermal design than the original 5500, climbing up to a 61W average in our test suite. Higher power draw is actually better in this case. We’re dealing with relatively low-power desktop chips, so if peak performance is the goal, we want every watt the thermal design can handle being used.

Given that the 5500F ramps up power, it’s less efficient as a result. Perhaps efficiency is important if you plan on using one of these CPUs around the clock in areas with high electricity prices, but in the context of gaming, the power difference isn’t big. It’s less than what a phone consumes with fast charging.

007 First Light benchmarks

007 First Light kicks off our individual game tests, and it happens to be one of the stranger results in our test pool. There was virtually no movement between the Ryzen 5 5500 and Ryzen 5 5500F, despite a jump in power with the 5500F. This is clearly an outlier in our suite, which will become clear as we go through the other games.

Baldur’s Gate 3 benchmarks

Baldur’s Gate 3 aligns more closely with our geomean, with the 5500F outpacing the 5500 by 7.2%. Intel still leads, however, with the Core i3-14100F beating out the 5500F by 5.9% and 5500 by 13.6%.

Cities Skylines 2 benchmarks

Cities Skylines 2 showcases an aspect of gaming performance that’s often overlooked, which is raw CPU compute. Here, we have a fully built city with a population of over one million people, stressing core count, clock speed, and memory capabilities. Although we only have a handful of chips here, the Core i5-14400 with DDR5 provides some important context for how this benchmark stresses different aspects of the system.

Crimson Desert benchmarks

Crimson Desert and its proprietary engine are remarkably well optimized, enough so to allow every CPU in our test suite to maintain a playable frame rate, even with Ultra settings. The 5500F is 7.8% faster than the 5500, though the Core i3-14100F still leads in performance, even when paired with DDR4.

Counter-Strike 2 benchmarks

Counter-Strike 2 shows the first major upset of our test suite, with the Ryzen 5 5500F winning out over the other CPUs we’re focused on; once again, the Core i5-14400 is mostly included for context. Although the 5500F beats out even the Core i3-14100F paired with DDR5, it suffers in the 1% lows, with even the Core i3-14100F paired with DDR4 offering better 1% low performance.

Cyberpunk 2077 benchmarks

One of the better showcases of the Ryzen 5 5500F, Cyberpunk 2077 shows the CPU up 9.2% compared to the base 5500. Intel still leads with the Core i3-14100F, though with a smaller 4.1% margin. Compared to the base 5500, the Core i3-14100F is 13.8% ahead.

The Blood of Dawnwalker benchmarks

The newest addition to our test suite is the UE5-based The Blood of Dawnwalker, and in particular a trot through a dense city in the middle of the game’s map, notorious for ramping CPU usage and introducing stuttering. The 5500F comes out on top by over 8% compared to the base 5500, but once again Intel leads with the Core i3-14100F.

F1 2024 benchmarks

With more modern CPUs, F1 2024 is normally a benchmark that skews heavily toward AMD, but this far down the stack, the opposite is true. Intel leads, even with a solid gain from the 5500F.

Final Fantasy XIV benchmarks

Final Fantasy XIV is balanced between AMD and Intel, though it heavily favors X3D CPUs. Without any of those in the mix here, the Ryzen 5 5500F falls behind the Core i3-14100F by 15%. There’s also little gained from moving to DDR5 with the Core i3-14100F.

Flight Simulator 24 benchmarks

Gaining a few frames in Flight Simulator 24 is nothing to sneeze at, and that’s exactly what the 5500F pulls off with a 9.6% lead over the 5500. Unfortunately for AMD, the Core i3-14100F is much faster in this title, with the 5500F trailing it by 18.9%.

Forza Horizon 6 benchmarks

Forza Horizon 6 shows more movement. The Ryzen 5 5500 already matched the Core i3-14100F in performance, allowing the 5500F to swoop in with a 7.8% lead. The Core i3-14100F with DDR5 unsurprisingly still leads, but this is a big feather in the 5500F’s cap.

Marvel Rivals

Marvel Rivals is an important benchmark, not only because the game is wildly popular, but also because it showcases exactly what AMD wanted to accomplish with the 5500F. The 14100F leads the base 5500 by over 12%, but the 5500F changes that story, leading the 14100F by 6.3%. This is presumably the target AMD set with the 5500, attempting to gain a performance advantage over the 14100F where the base 5500 originally struggled. And it hit that target in this case.

Onimusha: Way of the Sword benchmarks

Onimusha: Way of the Sword is the latest game sporting Capcom’s storied RE Engine, and it’s a title where the base 5500 and Core i3-14100F are in lockstep. The 5500F steps in to take the lead once again, beating the Core i3-14100F out by 6.9%.

Spider-Man 2 benchmarks

The notoriously CPU-heavy Spider-Man 2 jumps back to the pattern established by other titles in our test suite. The 14100F is over 20% ahead of the base 5500, and although the 5500F makes the battle closer, Intel still leads by 11%.

Starfield benchmarks

Starfield shows the Ryzen 5 5500F ahead of the 14100F, though only marginally, and with Intel coming out ahead with slightly better 1% lows. Still, this is another game where the 5500F successfully changes the power dynamic between Intel and AMD’s budget CPU offerings.

Warhammer 40K Space Marine 2 benchmarks

Finally, Warhammer 40K Space Marine 2 shows the 5500F matching the 14100F, whereas the base 5500 trailed by nearly 7%.

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The Ryzen 5 5500F is primarily a gaming CPU, clocked fairly low at a 4.4 GHz boost and packing just six Zen 3 cores. The six-core floor that AMD has maintained for several generations gives the 5500F a significant edge over the Core i3-14100F, which uses a true quad-core design, bypassing the hybrid design that Intel has used on its past several generations of desktop CPUs.

There aren’t a lot of quad-core chips on the market today, so it’s no surprise to see the Core i3-14100F at the bottom of the chart here, regardless of whether it’s paired with DDR4 or DDR5. The Ryzen 5500 already led Intel by 12.8% in our multi-threaded geomean, but the 5500F nearly doubles that lead to 24.2%. Compared to the 5500, the new 5500F is a clean 10% ahead in our multithreaded geomean.

The scales unsurprisingly flip looking at single-threaded performance. Intel usually leads in single-threaded performance anyway, but some context is important here. Zen 3 is much older than Raptor Lake, and those microarchitectural differences really show up in our single-threaded testing.

On microarchitecture, the Ryzen 5 5500F is 5% ahead of the 5500 in our single-threaded geomean, aligning almost perfectly with the 5% boost in turbo clock speed that the 5500F has. That’s a welcome bump, though keep in mind that a 4.4 GHz boost is still relatively low, and the 5500F only has access to 16 MB of L3. Other Vermeer CPUs, such as the 5700X, have 32 MB.

Rendering Benchmarks

CPU rendering workloads are intense, sustained tasks often pinning either an individual core, or all of the cores, at full utilization. Because they’re sustained and demanding, many of our rendering tests factor into the geomean above, and that’s a major driving force behind why tests like Cinebench are such a staple when measuring CPU performance.

For the headline tests like POV-Ray and Cinebench, the results fall as you’d expect. AMD leads in multi-threaded work, Intel in single-threaded work, and the 5500F ends up between 5% and 10% faster than the 5500, depending on the benchmark.

Encoding Benchmarks

Encoding workloads are similarly all-out for the CPU cores, and in heavy, multi-threaded video encoding via HandBrake, the 5500F is only marginally faster than the 5500. Particularly in these heavy video encodes, the fact that the 5500F has access to six cores matters more than anything else. That slight boost in clock speed helps it squeeze out an advantage; however, with any of these workloads, you’ll notice the 5500F struggles to get along, just like the Core i3-14100 and base 5500.

Single-threaded encoding via LAME shows an advantage for Intel, unsurprisingly, but the multi-threaded workloads are what matter here. As a demonstration, look at our VP9 HandBrake results. The 5500 actually ended up faster than the 5500F here, though by just 1 FPS, when the standard for these chips is managing just 4 FPS for this encode.

Creator App Benchmarks

The main CPUs we’re focused on — 5500, 5500F, and 14100F — aren’t the best choice when it comes to modern creative applications, particularly when it comes to the more demanding workloads in nonlinear video editors like Resolve and Premiere, as well as visual effects in After Effects. In Photoshop, the three ~$100 CPUs all hit a performance wall, though likely for different reasons, as you can see the DDR5-equipped 14100F run into the same bottleneck as the DDR4 version.

Web and Office Benchmarks

Web and office workloads are par for the course when it comes to the Ryzen 5 5500F. Although Intel retains a lead in our web and office benchmarks, the 5500F does a lot to close the gap compared to the 5500, at least in some tests. Looking at general web workloads through WebXPRT and Procyon, there isn’t much of a difference between the main chips we’re focused on.

However, the 5500F gains some ground in Excel with a 9.7% jump over the 5500. It was a massive 35% faster in Word, finally closing in on the 14100F, and it was 6.7% faster in PowerPoint. Even by the standards of budget CPUs, the Ryzen 5 5500 didn’t perform well in these applications. The 5500F puts AMD’s budget offering back in contention.

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

We run hundreds of tests on every CPU that comes across our benches, and not all of them are relevant to every chip. Here, we have a collection of more specialised workloads that don’t factor into our overall geomean. The tests are greatly varied here, including code compilation, compression performance, Java, chess engines, and cryptography, among other tests. We won’t be able to highlight all of them.

The most recognizable is Geekbench, showing a broader view of single-threaded and multi-threaded performance in a machine-gun-style benchmark suite that rips through different workloads in just a few minutes. What’s interesting is that Geekbench multi-thread shows the 14100F paired with DDR5 on top, likely taking into account the memory standard that isn’t represented in tests like Cinebench.

Another interesting test to highlight is memory throughput via WinSAT. This built-in Windows benchmark shows a clear performance wall for the DDR4 chips in our test suite. Of course, DDR5 provides much more throughput, but the interesting bit here is just how bottlenecked the throughput is with these late-stage DDR4 CPUs.

Elsewhere, there are a few broad trends that emerge. In security and cryptography workloads, AMD rules the roost. However, in many scientific workloads, Intel holds an edge. Again, these workloads aren’t particularly relevant for these CPUs, so we’d recommend placing more emphasis on the benchmarks in the sections above.

SPEC Workstation benchmarks

We run SPEC Workstation as part of every CPU pass, and although workstation application performance isn’t relevant to these budget desktop chips, it’s still interesting to see how these applications push against the limitations of such restricted CPU designs. Feel free to peruse, but don’t put too much stock in the actual rankings. These are unrealistic workloads for this class of CPU.

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In games, we saw the Ryzen 5 5500F consume more power than the base 5500, actually reaching toward its 65W thermal design. In applications, the opposite is true. The 5500F actually consumed slightly less power than the base 5500, particularly in all-core workloads where the 5500 pushes past its 65W thermal design.

In y-cruncher multi-thread with AVX enabled, the 5500F drew 14.6% less power on average compared to the base 5500 and Core i3-14100F. In Linpack, the 5500F shaved more than 20% of the wattage of the 5500, and in Handbrake using VP9, it cut 12%. We don’t use software monitoring for our power measurements. Results are gathered from the EPS cables themselves.

Looking at idle and active idle power measurements, the 5500F maintains Zen 3 low-power idle state, sipping just 7 watts during YouTube playback, dropping down to 6 watts at true idle. The 7600X provides a hint at where idle power draw has gone in the Zen 4/5 era.

As a result of lower power draw in some tests, it’s no surprise that the 5500F ends up more efficient than the 5500 in y-cruncher and Linpack. In Cinebench and Blender, however, the two CPUs are closely aligned in efficiency, with the 5500F actually coming out slightly less efficient in the Junkshop scene.

Our scatterplots are a good way to visualize efficiency. In Handbrake, you can see the 5500F provided better performance than the 5500 while consuming less power. In Blender, however, the two CPUs consumed roughly the same power, while the 5500F provided better performance.

Across all of our efficiency tests, the comparison for Intel isn’t great. Not only does the 14100F struggle in all-core workloads, it does so with higher power consumption, occasionally pushing above 80W.

Test Setup

As with all of our CPU reviews, we used as close to identical test setups as possible to isolate CPU performance. There are several steps we take with hardware to normalize results, such as using the same fan speed across each test bench, as well as tweaks we make to the software stack to represent true performance.

Our test images are based on Windows 24H2. We use the same Nvidia driver across both the RTX 2080 Ti and RTX 5090. Additionally, our test images never cross platforms, so chipset drivers on an Intel platform never see an AMD chip, or vice versa. Application versions are pinned where possible. For games, where pinning isn’t possible, we do regression testing in the event of an update, and if required, retest the pool of chips if the performance profile has changed.

Finally, we tweak the BIOS. Every system has access to EXPO/XMP, as well as ReBAR. Virtualization-Based Security (VBS) is disabled. For Intel systems, we use the default power profile, not more extreme power profiles that aren’t covered under warranty. Similarly, we disable AMD’s Precision Boost Overdrive (PBO), as it can push the processor outside warrantied specifications.

MORE: CPU Benchmark Hierarchy

MORE: AMD vs. Intel

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The Ryzen 5 5500F is a compelling chip right now. When memory, storage, and GPU prices are at an all-time high, it offers a simple entry point into the AM4 platform, which remains relevant for midrange gaming rigs, on the heels of AMD re-releasing the Ryzen 7 5800X3D. The 5500F solves the major issues with AMD’s previous budget offering, upgrading the PCIe standard to Gen 4 and offering gaming performance that can rival the Core i3-14100F.

Price is the only issue. As is the case with many lower-end SKUs, availability of the Ryzen 5 5500F has been spotty at MSRP. It’s sold north of $120 in many cases, while the Core i3-14100F is available for around $100. AMD has the upside of a 5800X3D upgrade in the future; Intel has the Raptor Lake Refresh stack and DDR5 options. The right choice between them largely comes down to what your future upgrade plans are, especially if inflated RAM and storage prices persist.

Gaming is a major focal point here. You can buy a much better CPU for $150 or $200, but going with a $100 chip such as the 5500F gives you that much more money to spend on a graphics card. Intel still leads in our 1080p geomean with the Core i3-14100F paired with DDR4, though only by 2.9%. That’s enough of a lead to still call it a lead, but we’re not far off noise levels.

Intel comes out ahead overall, but as you can see from our gaming benchmarks, the 14100F and 5500F swap places for the top slot between them from title to title. What was consistent was the uplift the 5500F showed over the 5500, often running ahead by around 7%, and by as much as 10%.

Although the modern dynamic between Intel and AMD shows Team Red ahead in games and Team Blue ahead in applications, the opposite is true here. The lowly quad-core Core i3-14100F can’t muster better multi-threaded performance than the Ryzen 5 5500, and certainly not the 5500F.

That’s despite the fact that the single-threaded performance of the Core i3-14100F is superior. The extra cores on the Ryzen 5 5500F pull their weight in threaded applications, though neither chip is built for much beyond basic office and web productivity. As a host CPU for a server, the nT performance of the Ryzen 5 5500F is a safer bet.

It’s a toss-up between recommending the Core i3-14100F or Ryzen 5 5500F; as mentioned, both have their advantages when it comes time to upgrade. Hopefully the price on the 5500F will come down. As it stands, the extra $20 is an annoyance more so than a dealbreaker, but it would nice to see the 5500F on level footing with the 14100F when it comes to price.

MORE: CPU Benchmark Hierarchy

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Intel and AMD are integrating their CPU optimizations for PyTorch into a unified library, offering tuning for both AMD and Intel chips through the oneDNN library. AMD has maintained a downstream version of oneDNN called ZenDNN, which is now moving into the open-source oneDNN, published by the UXL Foundation and driven by Intel. AMD also announced it's joining the UXL Foundation as a "steering member," which "influences the future of the UXL Foundation" in exchange for a contribution of $20,000 per year.

AMD says the move to unify these efforts under oneDNN was recommended by the x86 Ecosystem Advisory Group (EAG), which is a joint initiative that primarily exists between Intel and AMD and was established in 2024. The two companies have collaborated through the EAG previously, such as with the ACE extensions for x86 that we learned about earlier this year.

The oneDNN backend is used for CPU inference, and it's built to accelerate that workload for the latest Intel (and now AMD) chips in frameworks like PyTorch. When oneDNN was added to PyTorch as a backend in late 2023, it showed a 1.24x improvement with the Float32 data type, and 2.21x for the BFloat16 data type.

From the oneDNN GitHub, the library "detects hardware features at runtime" to generate optimized kernels for the platform, as well as provides low-precision data types. It also features optimized instructions for common AI and machine learning operations, such as matrix multiplication and convolution.

For developers, the move simplifies working with PyTorch across different systems, ensuring a single backend provides the proper optimizations for whatever hardware you're running. Although the news here is focused on the x86 guard, oneDNN is a cross-platform library that works on Arm and RISC-V architectures as well.

Intel originally developed oneDNN, built on top of previously deep learning libraries, before it was folded into the UXL Foundation. Intel was among the founding members of the UXL Foundation, alongside Arm, Qualcomm, Google Cloud, and others.

Earlier this year, AMD brought the previously RX 9000-exclusive FSR 4 upscaling tech to Radeon RX 7000-series graphics cards and promised an early 2027 release for RX 6000-series products. Christmas has come early for RDNA 2 and many other Radeon gamers, as Radeon honcho Jack Huynh has announced an FSR 4.1 release for Radeon RX 6000-series cards, Xbox Series X and Series S consoles, Ryzen Z-series handhelds, and machines with Ryzen AI Max and AI 9 chips today.

To accomplish this feat, AMD says it tweaked FSR 4.1's neural network model to support the INT8 shader hardware (as opposed to the higher-precision FP8 matrix acceleration hardware on Radeon 9000 cards). Additionally, the version specific to handhelds is slimmed down even further, to less than half the size of the full one.

AMD says that compared to FSR 3, games on the aforementioned GPUs and APUs will now deliver better image quality, all else equal. With Cyberpunk 2077 running in FSR Balanced mode at 4K, our quick testing with a Radeon RX 6900 XT shows that running FSR 4 costs just about 13% performance, a small price to pay for sharper and more stable visuals, especially in motion.

And the higher upscaling quality of FSR 4.1 might let gamers use Performance mode where they might previously have used Balanced, or so on, which might offset that performance cost.

There are more goodies in store, too. The Radeon team says that FSR Frame Generation now ought to have better frame pacing, resolving a longstanding complaint with the tech and potentially making for smoother gameplay with framegen enabled. Support for the Vulkan API with FSR 4.1 is set to arrive at some point, as well, a boon for some games and console emulators. Finally, AMD says FSR Ray Regeneration will also be coming to more games, too. The company showed the tech running in Warhammer 40,000: Darktide, and that integration is available now.

To get all this goodness into your GPU, you can download the just-released Radeon 26.10.1 drivers from the AMD Adrenalin application or directly from AMD's website. The updated software also adds support for Call of Duty: Modern Warfare 4, Star Wars: Galactic Racer, and Final Fantasy Resonance. You can check out the full release notes here.

For owners of Xbox and Ryzen Z2-series handhelds, AMD says that an update from their manufacturers will be forthcoming, as those devices depend on OEM-specific drivers.

We're pleased to see that Radeon gamers are getting upgrades for their existing graphics chips along the lines of what Nvidia has been delivering throughout 2025, because the way things are going, it looks like it'll be around 2077 before there will be a new gaming graphics card launch. If you're an RDNA 2 gamer, go give FSR 4 a shot and see what you think.

An AMD engineering sample has made an appearance in a listing on OpenBenchmarking. According to a report by TechPowerUp, the chip could potentially be a part of AMD’s upcoming Gainsborough family and a possible candidate for the next-generation Steam Deck handheld console. As per the OpenBenchmarking listing, the chip comes with a six-core, 12-thread processor paired with 24GB of high-speed LPDDR5 memory.

The engineering sample with part number 100-000001930-12_Y was tested on an AMD GBR-FF6-SKT validation board, with the CPU running at clock speeds of 2.4 GHz. The system also features four 6GB SK Hynix memory packages, resulting in 24GB of LPDDR5 memory running at 9,600 MT/s. That’s a big jump when compared to the current Steam Deck, which comes with 16GB of LPDDR5 memory running at 6,400 MT/s, alongside a four-core, eight-thread AMD Zen 2 processor.

The benchmark listing also provides some clues about the processor’s underlying architecture. As per Notebookcheck, the sample’s CPU microcode revision corresponds to AMD’s Family 1Ah, model DCh. Linux kernel changes indicate that this model falls within the range reserved for newer Zen 6 processors, suggesting that Gainsborough could use AMD’s next-generation CPU architecture. However, there is no clarity or any confirmation whether it will use standard Zen 6 cores or the denser Zen 6C variant.

The integrated GPU is listed with a clock speed of 2,400 MHz, although its architecture and compute unit count remain unknown. The sample was tested using the GpuTest benchmark suite on Ubuntu 24.04 at 1024 x 768 resolution, resulting in scores of 3,871 in GiMark, 3,508 in FurMark, and 9,319 in TessMark. While the FurMark score is comparable to the original Stam Deck, we can’t really come to any conclusions at this point, as the tests were conducted on an engineering platform using development software rather than a finished handheld. For now, the results do not establish how the chip would perform in games, as power limits, cooling, driver maturity, and the final GPU configuration all contribute to the performance in a compact gaming device.

If these specifications carry over to a future Steam Deck, the additional CPU cores along with the larger and faster memory would provide a meaningful hardware upgrade. That being said, neither AMD nor Valve have confirmed a connection between the Gainsborough family and a future Steam Deck. Thus, it is best to take this with a grain of salt and wait until there is more concrete information in the future.

Arm announced last week that its AGI CPU, the company's data center CPU for agentic AI workloads, delivers twice the performance per rack as AMD EPYC 9755, calculated from chip performance and server-power assumptions measured across seven workloads. The claim stems from modeled rack results from tests aligned with Arm’s new CPU evaluation methodology, developed with support from Fujitsu, Meta, and OpenAI.

The results — verified in an Arm-commissioned independent analysis by Signal65 — do not establish the AGI CPU as the overall leader for agentic AI, as they apply to the selected processors, workloads, and configuration. They also use the specific Arm-developed evaluation methodology that Arm says should be the new standard for assessing performance. However, other chipmakers like AMD and Intel make performance claims based on different benchmarks. So, how is Agentic AI evolving CPU performance benchmarks, what does Arm propose to measure, and how do the different approaches compare?

Arm’s new CPU evaluation methodology

Agentic AI is changing the role of CPUs in modern AI data centers, requiring them to handle complex, multi-step workflows. Beyond inference, which the accelerator handles, AI agents execute tools, retrieve data, and maintain state within isolated environments, acting like virtual users. The CPU handles these critical surrounding workloads, from running those tools and serving database or API requests to preparing data and coordinating work for accelerators.

As these workloads scale rapidly with agentic capabilities, it becomes increasingly important to gauge CPU performance not just by how many agents can run concurrently, but also by how much useful work gets done. Arm argues that CPU performance is increasingly defined by how much useful work a system can sustain while staying responsive. Supporting more agents simultaneously offers limited benefit if their executions throttle or accelerators have to sit idle waiting for the CPU. Power, cooling, and physical space also limit how much hardware operators can deploy, extending the performance question to the rack.

Arm’s proposed methodology for evaluating CPU performance, developed with support from Fujitsu, Meta, and OpenAI, centers on representative agent workloads, repeatable CPU measurements, and validation against end-to-end task outcomes. In practical terms, the methodology identifies the tools and services an agent uses, measures their CPU performance under controlled conditions, and checks whether improvements help the agent complete its task. For example, a database test can establish how quickly a system handles transactions. An end-to-end evaluation would then examine whether faster database access actually improves the workflow that depends on it.

Executing the second aspect of the methodology, making these comparisons repeatable, presents another challenge, as an agent might choose different commands or take a different route through a task each time it runs. Model inference and remote services also introduce delays. Arm proposes replaying recorded agent actions to separate CPU performance from this variability, allowing different systems to execute a consistent sequence of work. Its whitepaper sets out a framework for selecting and interpreting these measurements, leaving the industry to develop an agreed benchmark suite and scoring approach.

To evaluate the CPU work described in its framework, Arm ran seven workloads — spanning tooling, agentic workflows, and reasoning/planning, plus Sandbench, which measures sandbox-creation overhead for agent execution — on its AGI CPU and AMD’s EPYC 9755. The tests combine established server applications with benchmarks focused on agent workflows.

The vLLM result measures the CPU work around model execution, not GPU inference throughput. Similarly, the report’s “reasoning/planning” category groups supporting CPU workloads and does not assess how intelligently a model reasons.

ARM AGI CPU vs AMD EPYC 9755

For the tests, Arm used two AGI CPU configurations because of hardware availability: a 128-core chip at 2.8 GHz with DDR5-7200 for Terminal-Bench 2 and SWE-bench replay, and a 136-core chip at 3.2 GHz with DDR5-8000 for the other five workloads. The AMD comparison used one socket of the 128-core EPYC 9755 with DDR5-6400. Both platforms ran the same benchmark scripts but used different software environments. Arm used custom Linux 7.1.3 builds, with Ubuntu 24.04 for most tests and Ubuntu 26.04 for SWE-bench, while AMD’s main recorded configuration used Ubuntu 24.04 and Linux 6.8, with settings varying by test.

At the chip level, Arm’s AGI CPU won the majority of comparisons when compared to its AMD counterpart in five of the seven tests. With the EPYC 9755 as the baseline, Arm led by 9% on Terminal-Bench, 13% on SWE-bench, and 97% on fastText, but lagged by 12% and 5% in MySQL and Milvus throughput, respectively. On average, the AGI CPU led by 20% (1.20x) per-chip advantage, calculated across the seven normalized performance ratios.

At the rack level, Arm’s modeled performance averages 1.99x AMD’s, with a lead in all seven workloads. The model uses rated server-power estimates of 950 W for the 128-core Arm configuration, 1,050 W for the 136-core version, and 1,700 W for AMD, including memory and other system components. After reserving about 8% of a 24 kW rack budget for networking and power distribution, this leaves room for 23 or 21 Arm servers versus 13 AMD servers.

For SWE-bench, the 2.00x per rack result was obtained by multiplying the roughly 1.13x chip result by 23/13. The larger gain comes from fitting more servers into the same power budget. Furthermore, these projections use modeled whole-server power, not throughput measurements from two fully populated racks.

Arm’s model also gives the AMD servers about twice as much RAM: roughly 2 TB against 1 TB for Arm. It allocates 4 GB per hardware thread, with each AMD core supporting two threads while each Arm core supports one. This puts the memory-power allowance at 336 W for AMD and 192 W for Arm. Signal65 also calculated what happens when memory is allocated per physical core. In this setup, AMD’s memory and power allowance falls, and Arm’s average modeled rack advantage drops from 1.99x to approximately 1.81x. The usefulness of the 2 TB AMD configuration depends on how much memory the workloads actually need, as SMT does not inherently require twice the memory.

To verify the findings, Signal65 remotely observed Arm’s test runs and examined the original logs, result files, scripts, and configuration records. A separate review team rebuilt the calculations with its own code and reproduced all seven results within 0.5%. However, Signal65 did not run a separate hardware rerun in its own lab. In addition, Signal65 could independently confirm BIOS and memory settings for only the EPYC 9965 system. These settings were unavailable for independent verification on the Arm and EPYC 9755 systems. Along with the software differences, these gaps slightly affect the certainty with which the results can be attributed to the processors themselves.

Arm’s approach vs AMD and Nvidia

While Arm believes its methodology should be the standard, it does not hold a monopoly on how the industry evaluates agentic CPU performance. For example, AMD promotes agents per watt, dollar, and rack. Footnotes on its EPYC 9006 page identify available CPU threads as a proxy for agent capacity, with actual throughput depending on the workload and system. Its separate workload analysis models a 100 kW rack and claims 2.37× performance for EPYC 9965 over Nvidia's Vera, using a geometric mean across six infrastructure workloads.

Nvidia, on the other hand, emphasizes Vera’s single-thread performance and memory bandwidth, and says a 256-CPU rack supports more than 22,500 concurrent CPU environments. These numbers describe different things and do not directly imply any specific advantage. Methodologies vary across manufacturers by workload, power assumptions, and aggregation methods, making direct CPU comparisons complex. The current comparison is against AMD's fifth-generation “Turin” processor with 128 cores. The company launched its latest sixth-generation EPYC 9006 “Venice” family this year, dedicated to agentic AI.

The DLSS-NR project on AMD by Daniel Blanco was first released on September 3, 2026, bringing DLSS 5 Neural Rendering to Radeon GPUs; in the latest 0.8.0 update, however, it makes all the main DLSS features available, featuring DLSS SR, Frame Generation, Ray Regeneration, and the newest DLSS NR model, along with more performance improvements.

While AMD has equivalents for most DLSS features like FSR upscaling, frame generation, ray regeneration, and anti-lag, it’s not as commonly supported by most games compared to Nvidia’s offerings. Even if players could use the AMD equivalent features, Neural Rendering is one that AMD just doesn’t have an equivalent for yet, which is why mods like DLSS-NR on AMD were made.

Daniel Blanco wanted to fill the gap with NR in its initial release, but in the latest update, he added all the DLSS features: DLSS Ray Reconstruction, Super Resolution 4.5, Frame Generation, and the latest 310.9.16 improved Neural Rendering build that we covered recently with modders using it on unsupported games. Interestingly, the update notes say it includes FSR 4.1.1 upscaling; AMD GPUs already use FSR, but having FSR 4.1.1 specifically gives the mod a consistent version of FSR to work with, instead of having to be compatible with the various implementations of FSR in different scenarios.

The mod currently supports three generations of Radeon GPUs: RX 9000, 7000, and 6000 (RDNA4, 3, and 2, respectively), in any DirectX 12 game that uses FSR, DLSS, or XeSS. You can install the mod by downloading the NeuralHub mod loader, which provides a UI for you to install it into the games it detects. You then enable FSR, DLSS, or XeSS in the game, and the mod will insert itself into that upscaler pipeline, allowing it to inject any of the settings you configured for the game in the NeuralHub; it even provides an overlay to tweak the DLSS settings without leaving the game.

With a few improvements from the first version, the developer says the output quality is very similar to what DLSS produces on Nvidia GPUs natively, except for “some effects that may not be working 100%.” In the developer’s own testing, he found it to be playable at 90-100FPS at 1080p on an RX 9070 XT, while saying that he’s making improvements every day, planning to match the performance of a 5070Ti.

Real-world results are mixed, however, as Reddit users report showing no performance loss over native FSR, while others experience losing single-digit FPS to up to 25% lower FPS in various games. The developer still has to account for many factors since there are a myriad of PC configurations, but the results look promising as he bridges the gap between AMD and Nvidia GPU features — though it won’t work with anti-cheat, unfortunately.

AMD is bringing a new reference rack-scale design to the data center ecosystem with Helion. It’s a standardized, 21-inch rack reference design that will complement the Helios rack AMD revealed at OCP Global Summit last year. This year, we have Helion, which AMD says can house up to 32,768 Zen 6 cores in a CPU-only deployment using the dense 256-core design available with the EPYC ‘Venice’ 9996.

The rack design is standardized, based on the Open Compute Project’s ORv4 specification, which is slightly wider and taller than a standard IT rack. Helion is designed to support 44 OpenU trays, which are 21 inches wide and 48mm tall, slightly larger than a standard EA1-310 tray. AMD says the reference design supports both air-cooled and direct liquid-cooled deployments.

The design is also compliant with OCP’s DC-MHS (Data Center Modular Hardware System) standard. MHS is designed to bring “interoperability between key elements of data center, edge, and enterprise infrastructure,” according to OCP.

Although AMD has renders of the design you can see in the presentation below, it won’t actually sell racks. This is a reference design that AMD is contributing to OCP, and OEMs and ODMs will actually bring that design to market. AMD didn’t share partners supporting Helion during a pre-briefing with the press. The company says CEO Lisa Su will announce partners during the lead keynote at the OCP Global Summit later today.

AMD also didn’t share deployment partners, though it suggested that Helios customers will also deploy Helion racks.

Unlike Helios, which is built for AI training and inference, Helion is a more flexible rack solution primarily focused on CPUs. In a CPU-only deployment, the design can hold up to 128 EPYC 9996 CPUs, bringing that impressive 32,768 core count per rack. This configuration would likely look something like an agentic AI sandbox system, which is then connected to an inference system.

This model for personal AI agents is in use today, both in Meta’s Muse and OpenAI Dots. Each user has a sandbox with a slice of compute from the host system, with the backbone of an inference server. Some workloads are handled on those CPU-only servers, such as building software, but the heavy-duty AI inference happens elsewhere.

Presumably, this is the model AMD is aiming at with Helion as hyperscalers build out CPU capacity on the back of agentic AI. However, the design is flexible, supporting up to 16 MI350P GPUs and 102 Tbps of networking, though at the cost of CPU capacity. This hybrid configuration is targeted at enterprises, says AMD, giving them an all-in-one rack for data management, networking, and AI usage.

AMD says the Helion rack will be available starting in the first half of 2027, likely riding the wave of Zen 6 deployments that are expected to start ramping up later this year.

Full AMD OCP 2026 presentation

A quarter century ago today, AMD launched its AMD Athlon XP processor family. These were highly performant processors based on the firm’s latest Palomino core, but ran at lower raw clock speeds than Intel rivals. Facing a marketing imbalance between perceived and actual performance, AMD mounted a serious campaign to explode the 'megahertz myth' with this generation of CPUs. Thus, it introduced new Athlon XP processors with a Performance Rating (PR) designation, alongside a slogan insisting “Performance matters more than MHz.”

Intel, with its Pentium 4 processors, was clearly winning the MHz race at the time, while a CPU’s clock speed had long been established by marketers as a key performance metric. Unfortunately for AMD, its CPUs of the era didn’t hit such high clocks, even though the application and gaming performance was just as good (if not better) than Intel's.

Thomas Pabst's view

Our tests from October 2001 noted that AMD wisely undersold its chips, using the newly devised PR naming system. Anything less and it would have faced strong opposition and derision. Our tests clearly showed that a new “AthlonXP 1800+ is able to beat Intel's flagship Pentium 4 2 GHz in the majority of benchmarks,” wrote the original Tom, Thomas Pabst, in a 13-page feature about AMD’s newest CPUs. Moreover, it was observed that “AthlonXP at 1533 MHz is able to reach or even beat Pentium 4 running at an almost 33% higher clock speed.” Pabst concluded that AMD’s clocks/performance situation forced this concerted stand against the MHz myth.

As we broke the news about AMD’s Performance Rating system, some almost straight-away alluded to it being a ‘Pentium Rating’ system, but it was very early days. We didn’t know whether it would become a long-term success. It was known that AMD planned to establish an independent institution to create a new performance measure that is fairer and more realistic than the current MHz system in the following year. But, of course, Intel wouldn’t be interested in validating that. Pabst concluded that “I might not like it too much,” but admitted AMD had little alternative marketing-wise in the Pentium vs. Athlon era at the beginning of the millennium.

Please stop, it hertz

The AMD PR system would be abandoned roughly five years after it was initiated. Subsequent AMD (and Intel) architectures stopped the rating from making practical sense as the market evolved. For example, Intel’s big MHz advantage was lost in the transition from Pentium 4 Netburst to Pentium M/Core chips. Then, the Athlon 64 was so well received by reviewers and enthusiasts that AMD probably felt it might be wise to finish with its inferiority complex PR system that tied it to its obvious rival. Lastly, by the end of the AMD PR era, the marketing fight was clearly going multi-core. CPU marketing and naming completely sidelined any hint at CPU clock speeds later in the noughties.

A little less than seven months since signing a memorandum of understanding (MOU) concerning memory supply and collaboration in various fields with Samsung, AMD's chief executive Lisa Su is visiting South Korea to secure additional supply of HBM memory for AI accelerators, reports Chosun.biz. Meanwhile, Samsung is seeking a broader partnership and 'hopes to turn its memory supply relationship with AMD into foundry' chip production orders, the report claims.

"We are going to talk about our broader partnership," said Lisa Su when asked by reporters about what she planned to discuss with Samsung's executives. "We have many partners at Samsung."

Before visiting Samsung headquarters, Lisa Su and Jack Huynh, senior vice president and general manager of AMD's Computing and Graphics Group, attended the AMD Gamer Day event where Su and Huynh answered some questions from South Korean journalists and called local memory makers 'important strategic partners,' something that reflects the significance of data center-grade DDR5 and HBM memory for the company's AI and data center businesses.

"Samsung Electronics and SK hynix are key supply-chain partners for AMD," Su said, Chosun reports. "AI demand is extremely high, so we are planning our long-term supply chain with our partners. […] It is important to plan three to five years ahead with our partners."

The non-binding MOU that AMD and Samsung signed this March covered four areas and remained in effect for a period of three years:

• Supply of next-generation memory products, including HBM4 and advanced DDR5;
• Co-development and optimization of memory solutions for Al and high-performance computing systems;
• Exploration of foundry manufacturing opportunities for the future AMD platforms;
• Co-optimization of advanced packaging and related semiconductor technologies.

While Samsung has become a principal supplier of HBM4 for AMD's Instinct MI400-series accelerators, expansion of collaboration beyond memory supply is considerably more complicated, as it involves considerable efforts to design chips for Samsung Foundry's process technologies as well as risks associated with a product ramp at a new contract chipmaker. Truth to be told, AMD already uses Samsung Foundry and UMC to make its "ICs in the form of programmable logic devices" however, moving production of more advanced products to Samsung is risky. Meanwhile, Samsung badly needs big customers like AMD, and the latter's dependence on HBM supply certainly gives the former leverage.

"If we transition the production of some of our products to new manufacturers, we may experience delayed product introductions, lower yields or poorer performance of our products," AMD wrote in its most recent Annual Report.

AMD has already started shipments of its Instinct MI455 accelerators with 432GB of HBM4 memory onboard as well as rack-scale Helios AI systems to interested parties.

"We have started shipping our next-generation MI455 and Helios systems," Su told journalists, according to Chosun. "These are all systems that use HBM4."

So, it looks like the company is negotiating for more memory supply. The question is, will it take a risk and adopt Samsung Foundry for something more serious than niche programmable chips in a bid to get more high-bandwidth memory and sell more expensive AI accelerators? Only time will tell.

AMD's upcoming EPYC 9006-series 'Verano' CPUs that are specifically designed for AI servers will use an all-new SB1 socket and will require different cooling systems than other processors in the lineup, according to a listing at Dynatron, a leading maker of server coolers, discovered by InstLatX64. The new SB1 socket will be smaller than SP7 and SP8 sockets for other Zen 6-based EPYC CPUs and will therefore have different power and cooling needs.

AMD's Verano is quite different from conventional EPYC processors. The CPU will feature up to 72 Zen 6 cores operating at up to 5 GHz and a massive 24-channel LPDDR5X memory subsystem that uses replaceable SOCAMM2 modules. AMD positions Verano as a host processor for AI servers, where CPUs primarily orchestrate workloads running on AI accelerators rather than provide maximum general-purpose performance themselves. Such specialization could explain why AMD developed SB1 instead of using SP7, which accommodates up to 256-core EPYC 'Venice' processors, or SP8, designed for models with up to 128 cores. Meanwhile, AMD has not disclosed SB1's specifications, dimensions, or capabilities just yet.

In fact, given Verano's highly specialized role as a host processor for AI accelerators, AMD may not need to offer a broad range of Verano SKUs typical of its general-purpose EPYC families. If Verano is deployed in systems with a predetermined number of Instinct accelerators, AMD could offer just one or a small number of CPU configurations to ensure a consistent ratio of CPU cores, memory bandwidth, and host-to-accelerator connectivity per GPU and simplify power, cooling, and system qualification, something that Nvidia does with its Grace and Vera processors.

If AMD decided to take a page from Nvidia's book, this explains why it intends to use a dedicated SB1 socket instead of using existing ones. Rather than supporting a broad range of CPU configurations compatible with SP7 and SP8 sockets and systems, SB1 could be optimized for one or a few CPU SKUs, their 24-channel LPDDR5X memory subsystem, and a particular system topology. Note that AMD has not announced how many Verano SKUs it plans to offer, so consider our thoughts speculation for now.

Dynatron's preliminary SB1-4U-Active cooler provides the first indication of what cooling Verano will require. The 4U unit measures 128.05 × 106.6 × 130.7 mm and uses an aluminum fin stack combined with a vapor chamber and heat pipes. The unit is equipped with a double-ball-bearing fan that operates at up to 6,000 RPM and delivers up to 91.7 CFM of airflow, which makes it a quite powerful device.

It is noteworthy that these specifications are virtually identical to those of Dynatron's J26 4U cooler for AMD's much larger SP7 CPUs, to the degree that even the dimensions are similar. This may either indicate that Dynatron reused the J26 design for SB1, or simply copied and pasted J26's specifications onto the SB1-4U-Active cooler's product page to use them as placeholders until the actual cooler is finalized.

For now, Dynatron does not specify the cooler's maximum supported processor power, so its listing cannot currently be used to determine Verano's TDP with confidence. Nevertheless, a large vapor-chamber-based 4U active cooler suggests that Verano will be a server processor with a rather high power consumption despite having considerably fewer cores than the higher-end EPYC 'Venice' CPUs for general-purpose workloads.

AMD plans to launch Verano in the second half of 2027.

If you're looking for a new graphics card over Prime Day, then you've no doubt got your fingers and toes crossed, praying that the universe aligns to actually offer some discounts on this much-sought-after bracket of PC hardware. One of the best deals we've spotted today is on a brand-new, current-generation, mid-range graphics card that packs 12GB of VRAM. The Asus ATS Radeon RX 9070 GRE GPU is available at Amazon for a deal price of $529.

Over the past 30 days, the price of this GPU has ranged from $529.99 to $589.99. The current maximum list price is $789.99, but that doesn't reflect the more realistic amount the card has actually been recently selling for. The MSRP launch price for the RX 9070 GRE was $549, so it's amazing to see a GPU that falls below that MSRP threshold in the current economic climate for PC components.

● Check out this deal at Amazon

With 12GB of GDDR6, the RX 9070 GRE sports bandwidth speeds of 18 Gbps on a 192-bit bus, producing 432 GB/s of memory bandwidth for speedy operation in both gaming and application use. Similar to the Radeon RX 9070 and RX 9070 XT, the Radeon RX 9070 GRE is still built on AMD’s RDNA 4 graphics architecture and uses the same Navi 48 GPU; however, the RX 9070 GRE features a cut-down version of the Navi 48 chip with 48 compute units compared to the RX 9070's 56.

AMD's Radeon RX 9070 GRE sits just behind Nvidia's RTX 5070 in our benchmarking results from our review of the RX 9070 GRE. We found the card to average around 120 frames-per-second at 1080p and about 86.6 FPS at 1440p across our 11-game raster-only test suite.

Combined with a modest power consumption of 220W total power draw, the Radeon RX 9070 GRE is a good GPU choice for 1080p and 1440p gaming, with ample VRAM for playing games on high settings at 1080p, but maybe pushing the limits of 12GB of VRAM when playing with higher settings at 1440p.

So if you're actively looking for a new GPU, then jump on the Asus ATS Radeon RX 9070 GRE for just $529.99; don't hang about, as these lower GPU prices will have the RX 9070 GRE flying off the shelves in the blink of an eye in the current PC component market. To see a graphics card on sale for under its launch MSRP is a very rare sight, and one of the best Prime Day GPU deals out there.

Nvidia is expected to launch RTX Spark devices later this week, following a not-so-subtle tease at the end of last week (and the chip’s announced fall release). Ahead of Microsoft’s event on Wednesday, October 7 (where the launch is expected) AMD has shared some benchmarks for its new Gorgon Halo chips — the range that will directly compete with RTX Spark devices. The extra insight comes a matter of days after the first Gorgon Halo devices launched, some of which cost upwards of $7,099.

Short of a few questionable Geekbench leaks, we haven’t seen any performance results for the RTX Spark yet, so AMD isn’t using it as a comparison point. Rather, it’s comparing the Ryzen AI Max+ Pro 495 to Intel’s Core Ultra X9 388H. These chips aren’t in the same class of device, though AMD would argue that it’s comparing its top-of-stack part to Intel’s top-of-stack part.

AMD used ComfyUI to measure generative AI performance. AMD averaged multiple runs of various models, comparing total throughput to Intel’s competition. AMD used its top-spec 192GB configuration of the Ryzen AI Max+ Pro 495 and compared it to the Core Ultra X9 388H in a system with 64GB of memory (Panther Lake supports up to 128GB).

The performance advantage ranges from 1.1x up to 32.2x, though the end point is a clear outlier. We searched for Yuve on Hugging Face and didn’t find any results. It’s possible this delta comes down to an optimization issue, or that it’s simply too big to run on the Panther Lake machine.

We don’t have gaming or general application performance, but we don’t expect a major swing compared to last-gen Strix Halo chips. Gorgon Halo is largely a refresh of that range.

Gorgon Halo isn’t getting into the ring with Panther Lake, however. It’s going mainly against the RTX Spark, and to a lesser extent, Apple’s larger M-series SoCs. This category of agentic PCs, as AMD calls it, is seemingly expanding, though it’s still far smaller than some of the hype around the RTX Spark would have you believe. AMD bragged in a prebriefing with the press about shipping “10s of millions” of AI PCs (read: laptops) before clarifying that it had slipped “over half a million” agentic PCs. Presumably, those are numbers for Strix/Gorgon Halo devices.

The matchup between Gorgon Halo and the RTX Spark has, up to this point, focused mainly on memory capacity. RTX Spark devices top out at 128GB of unified memory, same as the GB10 in the DGX Spark (the two chips are nearly identical). AMD, on the other hand, supports up to 192GB with Gorgon Halo. Higher capacity means running larger models locally, though at a lower performance level.

In the GLM 5.3 Flash with 320 billion parameters, AMD saw peak throughput of 20 tokens per second, though using Unsloth's UD-IQ4_XS mixed-quantization format. For context, we clocked peak token throughput on the DGX Spark running GPT-OSS 120B with 4-bit quantization at 64 tokens per second, and the last-gen Ryzen AI MAx+ 395 at 56 tokens per second.

Note that although GLM 5.3 Flash has 320 billion total parameters, only 18 billion are activated for each token. Similarly, GPT-OSS 120B is another mixture-of-experts model with 120 billion total parameters, though only around 5 billion are active per token.

AMD also shared Qwen 3.8 Flash Next performance, a multimodal MoE model with 125 billion main parameters, 51 billion embedding parameters, and about 4 billion parameters for multi-token prediction (MTP), with 5 billion parameters active per token. AMD says the Ryzen AI Max+ Pro 495 achieves up to 42 tokens per second with this model, once again using Unsloth’s dynamic 4-bit quantization and MTP.

That’s solid performance, but in both cases, “up to” carries a lot on its shoulders. The story of token throughput is told as the context length increases, showcasing what happens when someone actually runs these models locally, not just boots them up cold. Performance drops at higher context lengths, naturally, which could pose some issues for the larger models. If GLM 5.3 Flash provides up to 20 tokens per second, it could very easily decline into unusable territory as the context length increases.

We largely know what performance to expect out of the Ryzen AI Max+ Pro 495, and Gorgon Halo more broadly. It’s a refresh of Strix Halo, with notable spec changes being the bump up to 192GB of unified memory from 128GB, as well as a 100 MHz jump on boost clocks for the 495. Otherwise, the range is using identical core counts and microarchitectures as previous-gen Strix Halo chips.

With these proxies — Strix Halo for Gorgon Halo, and GB10 for RTX Spark — we can already get a good idea about how these parts will stack up. As you can see in our Ryzen AI Halo review (packing the Ryzen AI Max+ 395), AMD’s part universally underperformed compared to the DGX Spark in both time to first token and tokens per second across three models. More unified memory will allow you to run larger models, but that doesn’t mean those models will run faster.

The first Gorgon Halo devices are available for sale now, such as the Minisforum MS-S1 Max-P495. For the top-line configuration, prices sit around $7,000 right now, though we expect a broad range of prices once different devices are available, likely driving above that $7,000 mark.

Full presentation

Despite being in the midst of an unprecedented memory chip shortage, it seems that gamers are still willing to invest in their gaming PCs to extract the best performance out of their favorite titles. The September 2026 Steam Survey results show that 42.22% of the surveyed units now have 32GB of system RAM — a 4.77% increase compared to the previous month — while 16GB configurations have shrunk by 3.38%, falling to just 37.82%.

We’ve also seen increases in “weird” memory configurations — 24GB has grown to 2.56%, increasing by 0.34%, while 48GB inched up to 1.46% after a 0.26% increase.

This comes as a surprise, as some manufacturers have reintroduced laptops with 8GB of RAM even as Microsoft called 16GB the new “practical starting point,” and recommended 32GB as the future-proof “no worries” configuration for gaming. It should be noted, though, that the company quietly erased this suggestion after it released 8GB base models for its Surface laptops a few months later.

It’s quite possible that memory capacities were always destined to increase for gamers, especially as titles become more demanding. Minecraft, which hasn’t updated its system requirements for 17 years and is known for being potato-PC-friendly, even increased its recommended memory to 16GB earlier this year, forcing players on older systems to switch to the Java Edition or play retro games instead. Because of that, the memory shortage may have merely postponed the inevitable reign of 32GB RAM on gaming PCs.

Another metric we’ve been following in the survey results is AMD’s slow but relentless march toward taking away Steam Survey market share from Intel. Team Red’s 48.37% market share across all platforms is the highest we’ve seen so far this year, with Team Blue now at just 51.63%. The May 2026 Steam Survey showed AMD at a little under 45% — at this pace, it’s possible that it will overtake Intel in just a matter of months.

If we break it down by operating system, 52.59% of Windows users are on Intel, while 47.41% use AMD. Intel may have an advantage here compared to the overall result, but it’s just a tiny margin, and the trend shows that AMD is gaining ground month after month. The difference between Intel and AMD is more glaring when it comes to Linux users, with an overwhelming 66.18% preferring Team Red over Team Blue’s 33.71%.

The Steam Survey is far from scientific and may not even reflect the broader movement of the overall PC market. But with Steam reporting a peak of more than 38 million concurrent players at the time of writing, the survey still offers a useful snapshot of what’s happening in the gaming PC market.

OpenAI’s new Jalapeño ASIC is being deployed internally alongside AMD EPYC Turin hosts, each with 1.5TB of memory. SemiAnalysis described the rack-scale deployment of Jalapeño following the reveal of the chip, which we asked Richard Ho, VP and Head of Hardware at OpenAI, about in an interview. Ho told us that the decision to use Turin was “pragmatic,” describing Nvidia’s new Vera CPU as “a little bit behind… on that maturity level.”

“The way we approached that design was really in terms of de-risking and being able to do that design fast. Vera, as a standalone, is a little bit behind on that maturity level. The Turing device is strong. It did what we needed to do, and partly our partners had some experience with it,” Ho told Tom’s Hardware Premium. “For the Jalapeño program, we were trying to make very pragmatic decisions. We wanted to be aggressive on the goals of the performance and the cost, but we didn’t want to take unnecessary risks. That felt like a good design decision that would fit within the parameters of how we make these design decisions."

There are many Arm-based CPUs on the market, many of which are deployed internally at different hyperscalers, such as Google Cloud’s Axiom and AWS’ Graviton, but Vera and Arm’s own AGI have been described as agentic CPUs, purportedly accelerating the complex reasoning involved in agentic loops compared to their x86 counterparts from AMD and Intel. We asked Ho about this dynamic, and why Turin was the right choice given the close working relationship between OpenAI and Nvidia, who responded with the quote above.

Arm has long touted the virtues of the AArch64 ISA compared to x86, going as far as to claim that its own AGI CPU provides more than twice the performance of modern x86 platforms. That claim is based on internal estimates, not real benchmarks, however. The company has been naturally bullish on AGI’s adoption in the market, though even with an impressive $2 billion in commitments, analysts say the market penetration will still be in the low single digits after two years.

With the explosion of server CPU demand this year and evolving agentic workloads, Nvidia has been at the forefront of messaging, comparing its Arm-based Vera to the x86 competition, boldly claiming a 1.8x improvement over a competing AMD Turin chip; a figure that’s extracted from an overall benchmark suite showing Vera just 3% ahead of AMD’s EPYC 9755.

Many semi-custom Arm designs, from Graviton to Azure’s Cobalt, have focused on core density and efficiency for cloud workloads. Vera and AGI are a shift toward messaging against peak performance. In early Vera benchmarks, Nvidia’s CPU looks impressive, though we’ve yet to see the chip in action in a wide variety of workloads, much less benchmarked against AMD’s upcoming Venice CPUs or Intel’s Diamond Rapids.

What’s interesting about OpenAI’s decision to use Turin is that it’s one of Arm’s deployment partners for AGI, as well as among the list of customers “exploring the Vera CPU,” according to Nvidia. OpenAI, other frontier labs, and hyperscalers keep a wide variety of hardware in their fleet. Pairing Jalapeño specifically with Turin came down to reducing risk, with Ho pointing to the maturity of the platform.

Broadly, x86_64 is more mature than AArch64; ARM has been around since the mid-1980’s, though a proper 64-bit extension didn’t arrive until 12 years after it was introduced on x86. And although Arm has worked its way into data centers over the past two decades, there’s still a much deeper x86 foundation reaching back several decades.

It doesn’t seem Ho’s comments were specifically on the delineation between AArch64 and x86, however. Rather, the comments are focused on the dynamic between Turin and Vera, with the latter being Nvidia’s first foray into a custom CPU core for the data center. Although the early benchmarks of Vera are impressive, it nonetheless represented an unnecessary risk for OpenAI’s rack-scale Jalapeño deployment.

Ho’s comments about OpenAI’s partners having experience with Turin expose where the thinking for the hardware team was at, as well. There are some differences in the practicality of servicing the host system between Turin and Vera, most notably the fact that Vera is board-mounted while Turin chips are socketed; swapping chips isn’t common in a server regardless, but it’s easier with Turin.

Given that OpenAI has a fleet of hardware available, it’s possible Jalapeño will be deployed with a different host system in the future, potentially paired with Arm’s AGI or Nvidia’s Vera. For now, however, Turin was the right choice.

A pre-launch Geekbench 7 result, shared on X by INIYSA as one of OpenAI’s dots (it's answer to Meta's Muse), shows a multi-core score of 9,435, with indications of the hardware used by the new autonomous agent. The VM hardware appears to be a single nine-core slice of an AMD EPYC 9V74 with 9.73GB of memory, run on Ubuntu for the leak and Debian for post-launch runs. Our check of Geekbench 7’s public database found six runs on that configuration uploaded since launch, ranging from 1,512 to 1,614 single-core and 8,135 to 8,991 multi-core. Dots, powered by GPT-6 Astra, launched at OpenAI’s DevDay on Tuesday for Pro and Business Premium users.

OpenAI bills the autonomous agents as having “their own cloud computer, their own browser, and the apps you’ve connected” in its introduction. This is not a new concept: Cursor says its cloud agents get their own virtual machines; SpaceXAI says every Grok Bot shares one persistent cloud computer; and Meta’s Muse gives each agent a sandbox.

Maddie D. Reese posted on X on launch day the apps her dot said came preloaded. The lineup includes Chromium, Blender, GIMP, Inkscape, Kdenlive, Godot, FreeCAD, OpenSCAD, KiCad, QGIS, ParaView, 3D Slicer, with Python, Node.js, and Git. In the same reply, the dot said its cloud computer runs “Debian Linux.”

The post went up the evening of launch day, captioned “OpenAI dots Geekbench 7 Score,” with a screenshot showing a single-core score of 1,667 and multi-core of 9,435. The result in the screenshot shows that it was uploaded Sept. 25, or four days before the launch. The 9,435 is almost 5% higher than the post-launch best and about 10% higher than the median. The pre-launch run is potentially a bit of an outlier, but performance remains within the same ballpark. It is uncertain who ran the original benchmark.

Tom’s Hardware previously reported that rival Meta’s Muse runs on AMD EPYC Turin with two cores and 8GB per sandbox. The 10 Muse runs in Geekbench’s database have median scores of about 1,041 single-core and 1,394 multi-core. The dot’s post-launch runs, with median scores of 1,570 and about 8,550, put it at about 1.5x the single-core and 6x the multi-core score.

Some of this gap is accounted for by the nine-core vs. two-core configuration; the rest of the gap likely comes from a difference in clock speed, partially offset by Muse’s newer architecture. Geekbench lists a 2.6GHz base clock for the dot’s EPYC 9V74 against 1.5GHz for Muse’s EPYC 9D25.

Muse’s runs also report 7.75GB of memory. Our independent run for this article came back with a single-core score of 1,000 and a multi-core score of 1,433, in line with the other Muse runs.

Data center CPU demand for always-on agents has surged as high-core-count CPUs are needed at sustained load. It is unknown whether the dots, as tested, hold their cores while idle. Such agents are rising in popularity: Muse reportedly passed 500,000 daily active users, and SpaceXAI plans standalone Nvidia Vera CPUs for Grok’s agentic workloads. It may only be a matter of time before a new CPU arms race begins. OpenAI has already said that, in the future, users will be able to add more dots and “scale the output of each dot by ... increasing its speed.”

When Nuvacore, a new CPU startup founded by legendary CPU and system architects Gerard Williams, John Bruno, and Ram Srinivasan, emerged from stealth earlier this year, it promised to "rewrite the rules of silicon," but did not say how it planned to do so. On Thursday, the company finally broke its silence and revealed that it is taking an unusual development approach that allows it to design a significant portion of its CPU core IP before committing to a particular instruction set architecture (ISA).

Traditionally, CPU developers start development of a new processor project with a particular ISA — such as Arm, RISC-V, or x86 — already selected. Although modern high-performance processors translate instructions into internal micro-operations and therefore separate the ISA from much of the underlying execution pipelines, the instruction set still influences numerous architectural decisions, including instruction decoding, register handling, memory ordering, and, of course, software compatibility.

Nuvacore says its Core First approach reverses at least part of this process. Instead of designing WarpCore around the requirements and limitations of a predetermined ISA, the company's engineers are developing a significant portion of the foundational CPU IP independent of a particular ISA. To a large degree, one can compare such an approach to the development of a car around its engine and not trying to fit an engine into an already developed platform.

"Rather than beginning with the constraints of an existing architecture and iterating from there, we are starting with the core itself," the company said in its statement.

As a result, the team may be able to better focus on the core's microarchitecture and optimize it for performance, power efficiency, and sustained workloads typical of modern data centers and AI infrastructure, the target application for the company. Nuvacore intends to select an instruction set later based on what works best for the systems that it and its partners plan to build.

There are obvious limits to how ISA-independent a CPU design can be. Eventually, WarpCore will need front-end logic designed around its chosen instruction set, and those architectural requirements will inevitably affect other parts of the processor. Nevertheless, substantial pieces of a modern CPU — such as execution units, branch-prediction units, data paths, caches, and portions of the memory subsystem — can be developed and evaluated before every ISA-related implementation decision is finalized.

In addition to not disclosing its ISA, which is arguably the biggest unanswered question surrounding the project, Nuvacore also has not disclosed the project's schedule, configuration, manufacturing process, power, or performance targets, though given the lack of the ISA commitment, one could say that the remaining details are not that important.

For now, the only thing that Nuvacore discloses about WarpCore is that it is "a new class of general-purpose CPU designed specifically for the sustained performance and power-efficiency requirements of AI infrastructure and contemporary data centers."

AMD's ambidextrous strategy returns?

Nuvacore's approach is not entirely without precedent. Under CEOs Rory Read and Lisa Su, AMD spent part of the 2010s pursuing an "ambidextrous" strategy intended to let it address x86 and Arm customers by sharing substantial processor and platform IP.

Arguably the most detailed part of the initiative was AMD's SkyBridge platform, announced in 2014. Under SkyBridge, AMD envisioned pin-compatible 64-bit Arm and x86 systems-on-chips that were to use AMD's own Puma+ x86 cores and Arm's Cortex-A57 cores with common platform infrastructure. Separately, AMD developed its custom 64-bit Arm K12 core under Jim Keller that was supposed to share microarchitecture features with Zen. Ultimately, due to lack of resources, SkyBridge was ultimately scrapped, while K12 never became a commercial product as AMD only pursued x86 Zen cores. The difference is, of course, that Nuvacore appears to be taking the idea further by deliberately postponing the ISA decision for WarpCore.

Since Nuvacore is still just a startup, we can only wonder whether its business plan includes marketing of CPUs at all. Nuvia, which was also founded by Williams and Bruno along with Manu Gulati, was acquired by Qualcomm and ultimately shaped the company's Snapdragon X Elite SoCs. In that light, its approach could give the company considerable commercial flexibility.

By developing much of its WarpCore design without tying it to a particular ISA, the company could potentially adapt the technology to the requirements of a future customer or partner. An Arm licensee could use the underlying core technology for an Arm implementation; another customer could choose RISC-V or another ISA. An established x86 vendor could potentially acquire or license the underlying microarchitecture and create its own x86 CPUs if it needs to.

Nuvacore, of course, has not indicated that such a transaction is its objective, but keeping WarpCore ISA-agnostic for as long as possible potentially broadens the number of companies to which its CPU technology could be valuable.

All in all, the Core First announcement tells us considerably more about how Nuvacore intends to develop WarpCore than what the processor itself will eventually look like. But if the company really does keep its ISA options open until relatively late in development, WarpCore represents an unusual attempt to separate development of a high-performance CPU microarchitecture from one of the decisions that normally defines a processor project from its earliest stages.

AMD has agreed to acquire AI model research firm World Labs in an all-stock purchase worth around $8.2 billion. World Labs co-founder Fei-Fei Li will join AMD as executive vice president and chief scientist, reporting to CEO Lisa Su. The deal will be finalized once it passes the usual regulatory hurdles.

Su says building compute platforms for the next generation of AI requires “a deep understanding of how models are evolving,” and Li says advancing the technology “requires close collaboration across model research, systems and compute,” and wrote in a separate post that World Labs needs to get “closer to the hardware,” without which AI is “hobbled in efficiency.”

Before founding World Labs, Li had already established herself as a luminary in AI research and development. She led the vital ImageNet project in the 2010s and has served as the chief scientist of AI and machine learning at Google Cloud and the director of the Stanford Artificial Intelligence Laboratory. Thanks to her many contributions to the field, she has been dubbed the "Godmother of AI" by several institutions.

World Labs develops “spatial-intelligence models that generate, reconstruct and simulate interactive 3D environments,” which are useful in robotics and simulation applications. Its world models build or simulate 3D scenes rather than being text-focused like LLMs. The company’s first commercial product was Marble, launched late last year, which creates persistent, downloadable 3D worlds from source material.

AMD and World Labs had already been working together to optimize training and inference for its models, and AMD had invested in World Labs’ $1 billion funding round in February. During Su’s keynote at CES in January, Li said that part of World Labs’ model ran on AMD's Instinct accelerators, and her team used both Instinct hardware and the ROCm software stack to achieve performance improvements for their applications. This tuning experience positioned World Labs as one of AMD’s showcase customers, and AMD says the deal will “help shape its future technology roadmaps.”

World Labs is AMD’s second-largest deal after FPGA designer Xilinx, which came out to about $50 billion at the close in 2022. AMD's other big buys have been smaller: ATI for $5.4 billion in 2006, AI systems designer ZT Systems for $4.9 billion in 2025, and networking solutions developer Pensando for $1.9 billion in 2022.

AI titan Nvidia was also an investor in World Labs in the round earlier this year. However, Nvidia has already been developing Cosmos, its own family of open-source world models. It agreed to buy Hugging Face, a platform for hosting and distributing open models, earlier this month for $12.93 billion.

World Labs' team will continue to do model research. The companies say that the deal will strengthen an “open AI ecosystem,” per the release, and World Labs said in its own post that it remains committed to “widely accessible open models.”

Atlas, World Labs’ latest world model, will power future versions of its Marble product, the company says. Li’s co-founders Justin Johnson and Ben Mildenhall will continue to work with Li in leading World Labs, including after Li takes on the new role at AMD after the expected close of the transaction by the end of the year.

Nvidia officially rolled out DLSS 5 earlier this month, bringing its new Neural Rendering technology to supported games for RTX 50-series GPU owners. While early testing has shown improvements in image quality and rendering, the technology is very resource-intensive, resulting in significant drops in frame rate. That, however, has not stopped modders from experimenting with DLSS 5 and attempting to bring the technology to AMD Radeon GPUs.

A GitHub project called DLSS-NR-on-AMD, designed to run DLSS 5 Neural Rendering on AMD's Radeon RX 9000 and RX 7000 series GPUs, is already seeing a rapid improvement in performance. It uses a ground-up, full reimplementation of the neural network runtime for AMD GPU architectures. As per the developer, the project currently works with DirectX 12 games that use FSR, with Cyberpunk 2077 and GTA V Enhanced among the tested titles.

Testing done by YouTube channel Ancient Gameplays shows Cyberpunk 2077 running at over 80 FPS on a Radeon RX 9070 XT without DLSS 5 Neural Rendering. Enabling the unofficial implementation, however, caused performance to drop around 11-12 FPS. Not only is that unplayable, but it also highlights just how much optimization was still needed to make the technology practical on AMD hardware.

Development has been rather quick, as an Alpha 0.3.3 version was released with a claimed 23% performance improvement, followed shortly by Alpha 0.4.0, which reportedly added another 42% improvement over version 0.3.3. The changes essentially amount to roughly a 74% performance improvement in just 24 hours. The project has also become easier to install thanks to the AMDNR launcher that can automate much of the setup process, meaning that users no longer need to manually copy and replace DLL files for each game. The launcher also supports different runtimes and provides additional options through the OptiScaler interface.

Ancient Gameplays tested the latest Alpha 0.4.0 build in Cyberpunk 2077 at 3440 x 1440 resolution and found the Radeon GPU reaching around 50 FPS. That is a substantial improvement over the roughly 30 FPS achieved with the earlier build, although it remains well below the performance of the game without Neural Rendering enabled.

There is still a long way to go before DLSS 5 on AMD hardware can be considered a practical alternative to native implementation. The project remains in alpha, which means performance and compatibility can vary considerably depending on the game and GPU. That said, the developer has informed Ancient Gameplays that they are working on another major update, which should bring a substantial performance boost on Radeon GPUs.

Meta's new AI agent Muse is powered by AMD EPYC Turin host systems, with each sandbox sporting two dedicated cores and 8GB of memory. Blogger Evan Hoffman and analyst Tae Kim both discovered that Muse will run some rudimentary Ubuntu commands if prompted, passing along the output to help identify things like the specs of the host system. More concerning is that Muse seems able to execute commands that might be unsafe, with Hoffman claiming that Muse offered to set up SSH to Muse's private VM.

Both Kim and Hoffman asked Muse about the VM's specs, and in both instances, Muse revealed that it's running on AMD EPYC 9D25 CPUs, a high-density Turin chip with up to 128 cores (two of which are generally fused off or reserved). The VMs are running on Ubuntu 24.04 and using Linux kernel 7.0. The systems hosting Muse don't include GPUs. The AI agent revealed that Meta uses separate GPU servers for inference, isolating the agent to CPU-only sandboxes.

The agent suggests that each user gets their own private sandbox that's persistent, which allows us to do some math on how many people an individual tray can host. Assuming a 2P system that offers up to 510 vCPUs with 2TB of memory, hosting up to 254 Muse users. Muse has reportedly passed over 500,000 daily active users as of a few days ago, which would come out to somewhere around 2,000 server trays with dual EPYC 9D25 CPUs and 2TB of memory.

This is just some rough napkin math; don't take it as law. It's possible Meta has CPU-only servers deployed with multiple different chips to host Muse, and it's also possible there's overhead in the configuration. Turin chips support up to 6TB of memory with high-density DIMMs, for instance. Still, EPYC hosts seem popular for this use case, mainly because of their core density, as even a dual-core sandbox can add up quickly when multiplied across hundreds of thousands (or even millions) of users.

Muse isn't completely open. Hoffman shared an example where an attempted command failed due to improper permissions when Muse tried to query the kernel buffer. Presumably, sudo (admin) commands would be blocked as well.

However, there might still be some security loopholes. Hoffman says that Muse offered to set up SSH into the private Muse VM. With a reverse SSH tunnel — where the destination machine initiates the connection, bypassing the firewall — an attacker may be able to execute more damaging commands.

Meta's David Singleton says this is intended behavior, however, describing Muse as "a free computer in the cloud." Meta has an extensive white paper on the security architecture of Muse published on its research website.

A Chinese tech firm’s crowd-funded project has touched off a firestorm over U.S. export controls after an analyst spotted a heavily restricted, military-grade AMD chip in its design selling for pennies on the dollar. The discovery — and the analyst’s subsequent call for a treason investigation — puts a sharp spotlight on how easily dual-use silicon can bypass strict U.S. national security sanctions through third-party supply chains ... despite corporate denials of direct sales.

Dylan Patel, the head of top semiconductor analysis company SemiAnalysis, has discovered that China's Puzhi Electronic Technology is crowdfunding development of a system based on AMD's Zync UltraScale+ XCZU47DR RFSoC, which is a U.S. export-controlled dual-use component. He called on the government to investigate AMD for treason.

"AMD found a business opportunity in dumping U.S. military chips for ¼ of the cost in China," Patel wrote in an X post. "U.S. list price is $36K for this chip, with $4K – 5K to U.S. companies at volume, but it is getting quoted $1K in China to crowdfunding campaigns. AMD needs to be investigated for treason. It is not just export violations, but it is literally selling military end use components to an adversary for less than your home country."

In a statement to Tom's Hardware, AMD denied selling or shipping the chips directly into the restricted region. The company says it investigates suspected diversion cases to determine whether any violation of law occurred, although it did not explicitly confirm that it had opened an investigation into this particular case.

"AMD is committed to full compliance with all U.S. and global export regulations and has a clear policy requiring our distributors, resellers, and customers to do the same," a spokesperson told Tom's Hardware. "Any shipment into restricted regions is a direct violation of our policy. This recent instance is unrelated to any direct AMD sales or shipments. We investigate all suspected diversion cases and if we find any violation of law, we will report it to relevant authorities and cease all business with the company."

AMD told Patel the same, according to another X post he made as a follow-up on the matter.

AMD's Zynq UltraScale+ XCZU47DR RFSoCs pack four general-purpose Arm cores, two Cortex-R5F real-time cores, an FPGA with 930,000 gates, and DSP engines with 4,272 DSP slices. It also has eight 14-bit analog-to-digital converters (ADC) capable of up to 5 GSPS and eight 14-bit digital-to-analog converters (DAC) operating at up to 9.85 GSPS to receive, process, and generate RF signals in real time without relying on separate data converters.

Devices based on Zynq UltraScale+ RFSoCs are used for software-defined radios, radar and phased-array systems, wireless and satellite communications, electronic test equipment, and other applications that require high-bandwidth, low-latency signal processing. Puzhi Electric officially positions its upcoming systems based on the Zynq UltraScale+ RFSoCs for 'professional engineers' and 'advanced researchers in universities,' though such systems can be used for completely different applications.

AMD's Zynq UltraScale+ XC-series RFSoCs are designed for commercial and industrial applications, but AMD also offers separate XQ-series defense-grade RFSoCs for aerospace and defense applications, although there the XCZU47DR does not have a direct XQZU47DR counterpart. Yet, the closely related ZU48DR is available in both XC and XQ versions. The latter adds defense-oriented qualification, ruggedization, and support rather than fundamentally different processing capabilities.

Therefore, while the XCZU47DR is technically aimed at civil, commercial, and industrial applications, the chip is a dual-use component featuring a 3A001.a.14 ECCN classification under the U.S. Commerce Control List (CCL) and therefore its exporting, re-exporting, or transferring normally requires a BIS export license to non-allied destinations (e.g., China) on anti-terrorist and national security concerns. This means that any shipment to China requires a license, but in practical reality, that license will almost certainly be denied. However, there is a license exception that allows shipping such items to commercial companies from the Group B countries, which means legitimate exports to dozens of states from where such goods could get to China illegally.

This might explain how Puzhi obtained its XCZU47DR devices, but it does not explain the enormous apparent difference between the prices available to Chinese and American buyers. The $1,000 figure, however, is Patel's reported price for the chip rather than a publicly advertised retail offer.

Xilinx, which AMD later acquired, introduced its 3^rd Generation Zynq UltraScale+ RFSoC family, including the XCZU47DR, in February 2019, and the devices reached production status in 2020, meaning that they have been on the market for almost six years now. Xilinx and then AMD have sold the unit to tens, if not hundreds, of companies in different countries, so determining the origin of the units that Puzhi has might be difficult.

It should be noted that lead times for XCZU47DR at various resellers like Avnet and DigiKey are 40 to 52 weeks, which indicates that the components are in high demand in the U.S. and Europe. Meanwhile, Puzhi claims it can ship its system based on the RFSoC on November 6, 2026.

AMD has started to add support for GDDR7 memory and several new graphics IP blocks to its open-source Linux kernel driver, which indicates that software enablement for the company's next-generation standalone GPUs is underway, reports Phoronix. While AMD does not identify the upcoming architecture, the changes are likely tied to its RDNA 5 project — but they don't necessarily herald an imminent launch.

AMD's existing Radeon RX 9000-series graphics processors based on the RDNA 4 architecture use GDDR6 memory, so the addition of GDDR7 identification to drivers is arguably the most explicit confirmation that AMD is setting the stage for its next-generation discrete Radeon graphics processors based on the RDNA 5 architecture.

AMD also submitted patches that enable IH 8.0, a new version of its Interrupt Handler IP block, as well as NBIF 7.10, the latest revision of the company's New Bus Interface. Several smaller patches make additional preparations for the new hardware. These changes follow earlier Linux driver work involving Display Core Next 6 (DCN6) as well as GFX 13.0.x, suggesting that AMD is gradually upstreaming support for multiple components of an upcoming GPU architecture. Yet, while enablement of IH8, NBIF 7.10, DCN6, and GFX 13.0.x clearly point to new graphics hardware, it does not necessarily point to new discrete GPUs, unlike the mention of GDDR7.

As revealed in August, 2025, Laks Pappu, Senior Fellow at AMD, is the lead architect for AMD's next generation datacenter GPU and discrete graphics platforms. Pappu was building next-generation "competitive 2.5D/3.5D chiplet-based and monolithic graphics SoCs on various packaging technologies," according to his LinkedIn profile before it was edited to remove those disclosures.

Essentially, Pappu's profile indicated that AMD's next-generation GPU architecture could support multiple physical implementations — including multi-chiplet and monolithic — depending on performance, cost, market requirements, and AMD's willingness to compete in certain market segments

AMD has already used a multi-chiplet design with its Navi 31 GPU, an implementation that kept graphics processing hardware on a large Graphics Compute Die (GCD), but disaggregated memory interfaces and caches into smaller Memory Cache Dies (MCDs). A more ambitious implementation could potentially distribute graphics processing resources between multiple dies, although Pappu's profile did not disclose how AMD intended to partition its future GPUs.

Such an approach would be considerably more complicated than separating memory and cache functionality. Multiple compute dies would require high-bandwidth, low-latency connections as well as mechanisms for synchronization and coherency, while software would ideally continue to see the set of chiplets as a single graphics processor.

Based on conventional GPU development cycles of roughly 2.5 to 3.5 years, RDNA 5 could already have been approaching tape-out or early post-tape-out stages when the information surfaced in August 2025, which means that the company is already likely to be testing the new GPUs internally.

Officially, AMD hasn't disclosed any details about its RDNA 5 architecture nor launch schedule, so take these developments with a grain of salt. For now, all we know for sure is that AMD is working on standalone RDNA 5-based GPUs, and they're likely to use GDDR7 in at least some configurations, assuming the AI-driven memory crunch doesn't choke supply of those chips even further for consumer applications.

AMD's market cap has crossed the $1 trillion mark for the first time, following a rally in its share price over the last week. At market close on Friday, AMD's share price was around $557. On Monday morning, shares immediately jumped to $607 on the market open and have continued to rise, finally pushing AMD over the $1 trillion mark.

Saša Marinković, AMD's senior marketing director, shared the milestone on X. Since posting, AMD's share has fluctuated a bit, bringing the market cap down below $1 trillion for brief periods. Undoubtedly, the buzz around the milestone will cause some turmoil in the share price throughout the day, though it should eventually stabilize.

Just a week ago, AMD was quite a ways off hitting the trillion-dollar milestone. AMD's share price has risen by around 29% over the past month, and 21% of that jump came in just the last five days. On Monday alone, AMD's shares jumped around 9% within the first few hours of the market opening.

If you're unfamiliar, market cap is a shorthand for understanding the value of a company. It looks at the number of outstanding shares multiplied by the share price. It's not necessarily tied to revenue or profit, at least not directly. Rather, market cap is a read on the value of a company in the eyes of Wall Street, fluctuating as the share price does.

AMD joins a club of fewer than two dozen companies around the world that have passed a $1 trillion market cap, including SK hynix, Amazon, Microsoft, Apple, Nvidia, Broadcom, and Micron. Although AMD has now joined the club, it's still far behind its rival in the AI accelerator space, Nvidia, which sits at a market cap of around $5.4 trillion currently.

However, AMD was able to beat Intel to the milestone. Intel's market cap currently sits at around $648 billion. Interestingly, Intel has actually seen a larger rally in its share price over the past month. Share prices have risen 37% in the past month, with 25% of that growth coming in the past five days. Similar to AMD, Intel opened on the market Monday morning with a 13% jump.

Following AMD's Q2 earnings, where it beat revenue expectations by 2%, shares traded down, creating an opportunity to hold. That's paying off now as both AMD and Intel shares jump.

Although AMD's AI accelerators have made inroads into the data center, Nvidia still largely dominates that market. AMD's unique positioning comes from its CPUs, which have become a focal point of agentic AI data centers over the past year.

AMD's new Ryzen 5 5500F and Ryzen 5 7500 are available for sale, though the prices are higher than AMD originally suggested. On Amazon, the Ryzen 5 5500F is available for $120, while the Ryzen 5 7500 is listed at $210, both $20 more expensive than AMD's suggested retail pricing. Both are sold directly by Amazon, suggesting we'll see slightly higher prices for these two chips than AMD originally suggested.

• Get the AMD Ryzen 5 5500F from Amazon
• Get the AMD Ryzen 5 7500 from Amazon

AMD revealed the budget CPUs nearly two weeks ago, and despite launching on that date, the chips haven't been available for sale in the U.S. until now. The Ryzen 5 5500F is particularly interesting, as the $90 Ryzen 5 5500 has continually been among Amazon's best sellers in CPUs. Although the Ryzen 5 5500 and 5500F sound similar, there are actually quite a few differences between the two CPUs.

Both are six-core, 12-thread chips using AMD's Zen 3 architecture, but the 5500 falls under the Cezanne family, while the 5500F falls under Vermeer. The 5500F comes with PCIe 4, compared to PCIe 3 on the 5500, as well as a higher 4.4 GHz boost clock — the base 5500 tops out at 4.2 GHz. These changes apparently allow the 5500F to achieve higher performance, somewhere in the range of 5% to 10%, in games. We'll be getting the CPU in the Tom's Hardware lab to test the performance ourselves.

Although Zen 3 is aging, it has become an ideal home for budget builders as the RAM pricing crisis continues to surge. In addition to the Ryzen 5 5500F, we saw AMD re-release the Ryzen 7 5800X3D earlier this year to combat rising DDR5 prices.

We took the Ryzen 5 5500 (non-F) out for a spin earlier this year for a budget $100 CPU shootout. Generally, it underperforms the Intel competition at this price, but a 5% to 10% jump would close that gap. If performance holds up, the Ryzen 5 5500F may have a shot at our best CPUs for gaming list with its low price.

The Ryzen 5 7500 is easier to parse. It's identical to the 7500F, just with integrated graphics. It comes with six Zen 4 cores for a total of 12 threads, and unlike the 5500, it exclusively supports DDR5 memory. The 7500 comes with a boost clock of 5 GHz and supports PCIe 5. Like the 5500F, it has a 65W TDP and comes bundled with AMD's Wraith Stealth cooler.

AMD originally announced the Ryzen 5 5500F at $99 and the 7500 at $190, though the current Amazon listings are both $20 higher than that — $120 and $210, respectively. At the time of writing, the CPUs are only available at Amazon in the U.S.; Micro Center and Newegg don't have listings available. When other retailers pick up the chips, prices could come down.

This isn't the first time we've seen oddly high prices on new AMD releases at Amazon. Earlier this year, the Ryzen 9 9950X3D2 went up for sale on Amazon prior to release, selling for $1,000, $100 above MSRP. After the launch dust settled and listings went up at other retailers, the pricing dropped back down to $900. Hopefully, we'll see something similar happen here.

Huawei's impressive next-generation Ascend 900-series AI accelerators will be offered only in China, not internationally, as the company struggles to meet domestic demand amid capacity constraints, the company announced this week. While the upcoming Ascend 960-series neural processing units (NPUs) could rival some of AMD's and Nvidia's existing AI GPUs, demand for these units outside of China was not guaranteed anyway.

"Since we do not have enough capacity to even satisfy the ​demand in China, we do not have a plan to expand into the international market in a fully-fledged way," said Eric Xu, rotating chairman of Huawei, on the sidelines of the company's Huawei Connect conference, Reuters reports. He added that Huawei supplies limited volumes to 'some countries where demand is particularly strong,' though he did not elaborate.

Huawei this week unveiled its latest AI accelerator roadmap, revealing major training and inference performance gains for its next-generation Ascend 960, 970, and 980 NPUs over the existing Ascend 910C and Ascend 950-series. The Ascend 960DT and 960PR are set to increase their FP8 training performance to 2 PFLOPS and their FP4 inference performance to 4 PFLOPS and 8 PFLOPS, respectively, in 2027. Meanwhile, their successors, Ascend 970 and Ascend 980, are projected to increase their FP4 performance to 14 PFLOPS and 28 PFLOPS, respectively, in the coming years.

Huawei Ascend vs Nvidia AI GPUs

*Preliminary data
S/D - Sparse and Dense
T/I - Training and Inference

But while the upcoming Ascend NPUs will be considerably faster than their predecessors, particularly for inference, they will remain well behind Nvidia's previous- and current-generation accelerators, at least in raw compute performance. Huawei's 2027 Ascend 960DT is projected to deliver 2 FP8 TFLOPS for training, compared with Nvidia's 4 FP8 TFLOPS for the H200, released in 2023. The Ascend 960PR is expected to offer 8 FP4 PFLOPS for training, which is far behind Nvidia's B300, which delivers 15–20 NVFP4 PFLOPS. Even the Ascend 980, targeted for 2029, is projected to reach 7.2 FP8 PFLOPS and 28 FP4 PFLOPS, well below Nvidia's R200, which is on track to deliver 17.5 FP8 PFLOPS and 35/50 FP4 PFLOPS this year.

Such a massive performance difference with leading AI hardware will reinforce Huawei's reliance on massive system-level scaling rather than chip-for-chip performance to compete with Nvidia. But massive system-level scaling comes with massive power consumption, which will make Huawei's next-generation Atlas SuperPoDs and SuperClusters considerably less competitive in markets that can access hardware from AMD or Nvidia.

Huawei is in an interesting paradoxical situation. On the one hand, its integration efforts like near-package optics (NPO) clearly free up capacity on 'older' nodes that can be used for other components of AI platforms. But on the other hand, SMIC's inability to ramp production on 7nm and 6nm-class nodes limits Huawei's ability to supply its AI hardware anyway, which is why it can barely meet demand.

Then again, while Huawei's Atlas SuperPoDs with up to 15,488 Ascend 960 NPUs can deliver up to 30 FP8 EFLOPS and 120 FP4 EFLOPS performance by far exceeding the capabilities of Nvidia's NVL72 clusters with a 72-GPU scale-up world size, their performance-per-watt is poised to be dramatically lower compared to Nvidia's architectures, which means that demand for such hardware outside of China will be limited at best. That said, a global AI hardware push doesn't make much sense for Huawei right now. What perhaps does make sense is offering cloud access to its hardware to various academic and research customers to popularize its CANN software stack.

A PC enthusiast has showcased their new all-AMD build on social media, packing a Ryzen 7 9800X3D and Radeon RX 9070 XT. That’s an awesome combo to behold, paired with 32GB DDR5-6000 during the AI-RAM-pocalypse. However, this build has become headlineworthy entirely due to its steampunk-inspired aesthetics. If Thomas Edison and George Stephenson had teamed up to build a gaming PC, it might have looked like this. Meanwhile, the weight of Redditor voting suggests that most think it looks like some kind of espresso coffee machine.

The crafty PC builder behind this new battlestation is Old-Mate-Fetus. Key to its visual appeal is the extensive use of copper cooling apparatus and wood. The images clearly show this open-build PC made with a custom liquid loop using copper pipes, elbow joints, and welds. These pipes meander around the build, feeding the Alphacool GPU block, the Heatkiller IV CPU block, and circulating around a large radiator up top. A copper design feature that really stands out, though, is the “reservoir made from an old Primus Blowtorch with sight gauge fitted to it.” Nice.

Old-Mate-Fetus sits the PC on a base/backing frame they also handmade using a dark hardwood with an antique finish, and brass screws. We can’t see it in the photos, so it's probably pretty safe to guess that the Corsair 850W SFX power supply is hidden in the wood base. The builder says that they also made custom cables from the PSU to the various components.

Custom PC component list:

• AMD Ryzen 7 9800X3D
• Gigabyte Aorus Elite B650M Wi-Fi
• Gigabyte Radeon RX 9070 XT Gaming OC
• 32GB Klevv DDR5-6000 CL28 (wanted 64GB)
• AlphaCool GPU Block
• Heatkiller IV CPU Block
• AlphaCool DDC pump with custom enclosure
• Corsair 850W SFX power supply
• Noctua Industrial 120mm Fans

If you are thinking the Old-Mate-Fetus design has some Billet Labs influence, and that it would be appreciated by them, “you are correct,” confirms the London-based copper pipe welder in the comments. The builder of this all-AMD machine warmly accepted the compliment. Redditors also joked about this new gaming PC possibly being the ultimate Steam Machine.

Following the launch of AMD's EPYC 'Venice' CPUs in July, AMD extended the performance claims for its upcoming generation of server chips on Friday. The high-level claim hasn't changed. AMD still says a 96-core, high-frequency Venice chip is around 20% faster than Nvidia's 88-core Vera in SPEC CPU 2026's Integer Rate test. However, the company went into far greater detail about the benchmarks in a new white paper.

There are several configuration differences depending on the benchmark throughout AMD's white paper, and although we'll call out those differences here to the best of our ability, we don't have all of the details. For the Vera comparison, in particular, AMD is mixing data from different sources, and in some cases, using different major releases of the GNU Compiler Collection (GCC). That can have a substantial impact on performance, so keep your salt shaker handy.

First up are results in SPEC CPU 2026 with the intrate test, looking at total throughput. These are older numbers, gathered in July with GCC 15.2. The intrate test runs multiple copies of an application on the same CPU, and the SOP is to run one copy per thread. Presumably, that's what AMD did here, but the white paper doesn't clarify, even in the footnotes.

The 256-core 9996 is 2.37x faster than the Intel Xeon 6980P and 2.24x faster than Vera according to the slide. The white paper clarifies the mystery 9006 CPU is the 256-core flagship. Perhaps most impressive is AMD's gen-on-gen comparison. According to these results, the 9996 is around 78% faster than last-gen's 192-core EPYC 9965.

Although the high-level results bring in data from Intel and AWS, much of the white paper focused squarely on the comparison between Venice and Vera. AMD broke down the individual subtests of SPEC CPU 2026 intrate in the white paper, which you can see below.

The comparison looks good for AMD, naturally, though there are a few wrinkles in the configuration. AMD is testing a down-cored EPYC 9996, dropping from 256 cores to 96 cores. It made no mention of power budget, but when AMD originally shared SPEC numbers, the 96-core model had access to the same 600W as the 256-core model — AMD's 96-core, high-frequency Venice SKU tops out at 500W. More consequential is the compiler, however. AMD is using GCC 16.1 and comparing the results to the ones Nvidia shared in its Vera white paper. Nvidia used GCC 15.2.

Michael Larabel over at Phoronix has a nice write-up about the difference between GCC 15 and 16, but the short story is that there are performance differences, not always for the better. GCC 16 takes longer to compile due to better optimizations, hence the lower scores on the GCC and LLVM compilations above. However, that leads to faster binaries. By how much depends on the flags, software, and a whole host of other factors. Regardless, it's not best practice to compare benchmarks using two different compiler versions. It makes sense that AMD used GCC 16.1 — it includes support for Zen 6 — but ideally Vera would also be on GCC 16.1.

Speaking of Phoronix, AMD pulled some data for the publication's initial, controlled testing of Vera. Above, you can see the Stream, an industry-standard benchmark for measuring memory bandwidth. Again, AMD is using a down-cored 9996 from 256 cores to 96, and offering it a 600W power budget. Still, this is an impressive showing, as Vera absolutely clobbered the competition in the publication’s original Stream results. Here, AMD is ahead by about 18%, with per-core performance about 8% ahead.

Breaking out of Vera, AMD also showed performance in cloud workloads, including database, Java, and cryptography. Once again, the gen-on-gen comparison stands out, as AMD was already leading in these workloads with its last-gen chips. AMD ran these tests itself, rather than relying on third-party data, though the Graviton5 results came from an AWS cloud instance.

Similarly, in HPC workloads, AMD furthers its lead over Intel's flagship Granite Rapids-AP offering. Intel's next-gen data center CPUs, codenamed Diamond Rapids, are set to be released next year.

Finally, we have "agentic AI workload performance," which uses actual benchmarks for comparison, despite what the names in the chart above suggest. From left to right, AMD used NGINX, TPCx-AI kit, FAISS, TPC-H and TPC-C, and a replay of a multi-persona agent. For TPC-H and TPC-C, AMD says it derived workloads from those benchmarks, so the results here aren't comparable to published results.

Although looking at benchmark results is always interesting, it doesn't say much in the context of a server deployment, at least at the scale that AMD is targeting. Peak performance is only one of the major factors that go into server deployments, after all, and even then, performance can vary wildly depending on what software you're running and how it's built.

Still, Venice looks impressive, perhaps more so in the gen-on-gen comparison than any competitive comparison. Hopefully that bodes well for AMD's future Zen 6 rollout on consumer desktops, but we'll have to wait until Team Red has more to share before drawing any conclusions on that front.

Microsoft has issued an out-of-band update for its recent Windows 11 patch, which has caused a number of bugs and issues. The September 2026 update was just released last Tuesday, and although it packs a number of new features and fixes nearly 1000 security flaws (commonplace in this day and age), there are also a few unfortunate regressions.

The 25H2 update finally reintroduces a movable taskbar, just like we've had since Windows 95, with an option to make the height smaller for compact displays. Likewise, the Start menu now has multiple configurable layouts, and you can toggle each main section on or off. Microsoft also revamped Windows Search — perhaps to finally be useful — and users can now choose to only have it display local results. Explorer got a handy tweak in the form of using KB, MB, GB size indicators, as well.

The update has also surfaced some serious bugs. First off, PCs with AMD Radeon GPUs are crashing, apparently due to the update provoking driver instability. Reinstalling the driver doesn't appear to help, and the reports unfortunately cover most contemporary AMD graphics cards. Microsoft did not mention AMD GPUs specifically in its latest update.

Microsoft noted that it has fixed an issue with Remote Desktop Services where RDS might become unstable, causing connection and sign-in failures.

Microsoft is also aware of an issue with audio output and microphone input going dead. Additionally, there are seemingly reports of audio devices starting up with a botched configuration, like tweaked 3D audio settings or speaker setups. The apparent workaround seems to be putting audio in a standard 2.0 configuration, but Microsoft has now addressed this issue in the emergency patch.

Explorer may display a black screen after logging in, leaving you with a perfectly functioning operating system but no visible UI. The File History backup feature is reportedly not detecting external drives, effectively making it useless. Of particular concern to enterprises, systems administrators, and homelabs, the Remote Desktop Service is also experiencing issues. Last but not least, Microsoft says it has addressed an issue where Claude Cowork is nonfunctional due to the update breaking HC-managed Linux VMs with Plan9 shared folders

Owners of HP and Lenovo systems are also advised to consider holding off on this update. Ever since the August 2026 patch (and now, cumulatively, with the September update), there are reportedly serious issues on both camps. On the HP side, there are instances of the update triggering BIOS corruption, leading to a failed install with no ability to recover the OS — though seemingly the OEM has published a new BIOS revision, so it's hard to say which side is to blame. Meanwhile, Lenovo users might have their machines black-screen or shut down out of the blue, seemingly due to power mismanagement.

While it's heartening to see that Microsoft has significantly increased its Windows development speed and is seemingly listening to customer feedback, a string of bugs after a major feature update are still common.

It's back: one of the best deals on a brand-new, current-generation, mid-range graphics card that packs 12GB of VRAM. There is a little hoop to jump through via Newegg to receive the discount, but it's more than worth it to slash $70 off the card and bring the price back down to its all-time low. AMD's Gigabyte Gaming Radeon RX 9070 GRE GPU is available at Newegg for $499. All you need to do is click on the "Extra Discount Available" link and enter your email address to receive the promotional code. Once you do that, you bring the price of this graphics card all the way down from its $569.99 list price. It's a very grim time for shopping for PC component upgrades, so to see an actual deal on a GPU that takes it below its MSRP in today's inflated market is a rare sight indeed.

● Check out this deal at Newegg

The RX 9070 GRE was initially made available to the Chinese GPU market and received a few changes from the original RX 9070 XT. The available VRAM was cut from 16GB to just 12GB of GDDR6, but it still sports bandwidth speeds of 18 Gbps on a 192-bit bus, producing 432 GB/s of memory bandwidth in gaming and applications. The Radeon RX 9070 GRE is still built on AMD’s RDNA 4 graphics architecture and uses the same Navi 48 GPU as the Radeon RX 9070 and RX 9070 XT. The RX 9070 GRE features a cut-down version of the Navi 48 chip with 48 compute units compared to the RX 9070's 56. Using just 220W total power draw, the RX 9070 GRE has an Identical power footprint to the standard Radeon RX 9070 GPU, making it quite power efficient and not needing a huge power supply to run.

We benchmarked the Radeon RX 9070 GRE in our extensive review, putting it through its paces in our suite of games. We found the card averages a cool 120 FPS at 1080p settings and 86.6 FPS at 1440p across our 11-game raster-only test suite. This is a good GPU choice for 1080p and 1440p gaming, with the RX 9070 GRE packing ample VRAM for high settings at 1080p, but pushing ultra settings at 1440p may use up the 12GB of VRAM. AMD's Radeon RX 9070 GRE sits just behind Nvidia's RTX 5070 in our results chart that you can view below.

If you're actively looking for a new GPU in the current PC component market, you're more than aware of the considerable price hikes across the GPU lineups from both AMD and Nvidia. To see a graphics card on sale for under its launch MSRP is a very rare sight, and I personally did not expect to see this kind of deal again outside of a large sale event like Prime Day or Black Friday. So if you're looking for a competent card for 1080p and 1440p gaming, then jump on the Gigabyte Gaming RX 9070 GRE for just $499.99.

Modders have slashed the cost of running FSR 4 on AMD’s RDNA 2-powered BC-250 by nearly half, with a new implementation cutting the upscaler’s processing time from 11.51 ms to 5.92 ms at 1440p. Detailed in a VideoCardz post, the latest work builds on the community’s ongoing effort to turn AMD’s unusual PlayStation 5-derived crypto-mining board into a capable Linux gaming machine, while moving the FSR 4 optimizations from a custom Mesa modification into a portable FidelityFX DLL.

According to testing shared by the developer, FSR 4.1.1 running at 2560 x 1440 with a 1706 x 960 Quality input required 11.51 ms using the original shaders, compared with 5.92 ms using the latest v4.0.0-rc9 release. At 4K, processing time reportedly dropped from 25.72 ms to 12.08 ms, while 1080p fell from 7.13 ms to 3.93 ms. The developer also reports that the optimized implementation produced byte-identical images to the original shaders in controlled testing, suggesting that the performance improvement comes from executing the same workload more efficiently, and not reducing image quality.

The BC-250 is particularly interesting in this context because it is based on much older RDNA 2 graphics hardware. FSR 4 relies heavily on machine-learning workloads and accelerated low-precision integer operations that are far better suited to newer AMD architectures. On the BC-250, those operations have to be handled through alternative instruction paths.

Earlier community work tackled the problem in Mesa, optimizing the INT8 dot-product operations used by FSR 4. Instead of relying on a much more expensive fallback sequence, the modified implementation used a more efficient mathematical path based around signed 24-bit integer operations. One representative shader reportedly fell from 64,269 instructions to 37,613.

The latest fork takes that work a step further by shifting the optimizations into a FidelityFX DLL. This removes the requirement to run a specially modified Mesa build, potentially making the optimized path easier to use with an existing OptiScaler installation or games with compatible native FidelityFX implementations.

Native Windows support, other GPUs, and frame generation have not yet been qualified, as the developer tested the BC-250 on Linux using standard Mesa and GE-Proton. The practical upper target for the board is roughly 1440p, as FSR 4 still consumes 12.08 ms at 4K even after the optimization.

The achievement is the latest chapter in the BC-250's unusual story. ASRock built the board for cryptocurrency mining systems around PlayStation 5-class AMD silicon, with six Zen 2 CPU cores and 24 RDNA 2 compute units enabled by default. With the mining market's collapse, individual boards began filtering onto the second-hand market for well under $150, and enthusiasts have since assembled a mature Linux gaming ecosystem around them, complete with custom firmware, GPU governors, CU unlock tools, cases, cooling solutions, and distro-specific fixes.

We recently put the BC-250 through its paces and found that community-developed tools can unlock all 40 physical RDNA 2 compute units on compatible boards, up from 24 enabled by default, while separate firmware work can restore the two disabled Zen 2 CPU cores and take the chip from six cores to eight.

The ecosystem still comes with limitations. In our testing, the BC-250’s aging Zen 2 CPU became a substantial bottleneck at 1080p and 1440p in some games, even with the GPU fully unlocked. The board also has only 16GB of shared GDDR6 memory, which caused some titles to crash due to memory issues at 4K and made frame generation harder at higher resolutions. While FSR 4 will not erase those limitations, halving the upscaler's per-frame cost gives a once-discarded mining board significantly more headroom to spend elsewhere.

With the ongoing memory crisis driving up the price of RAM and other components, it is arguably one of the worst times to build a new gaming PC. However, bundle deals can be a good way to offset some of those inflated prices. Speaking of which, we’ve spotted an incredible AMD bundle over at Newegg that includes the AMD Ryzen 7 9800X3D, an Asus TUF X870E motherboard, and 32GB of Corsair Vengeance RGB DDR5-6000 RAM for $1,109.99, offering savings of around $150. The bundle also includes a 240mm Cooler Master AIO liquid cooler and a copy of Onimusha: Way of the Sword as free gifts.

• Check out the deal in Newegg

The Ryzen 7 9800X3D is an 8-core, 16-thread processor based on AMD’s Zen 5 architecture. With a 4.7 GHz base clock and up to 5.2 GHz boost clock, the highlight feature of the chip is its 3D V-Cache technology that helps in lowering latency and giving a boost in overall gaming performance. If you’re looking for the best gaming CPU for a high-end build, the Ryzen 7 9800X3D should be at the top of your list.

The Asus TUF Gaming X870E-Plus motherboard should be a suitable pairing for the 9800X3D as it offers premium features including a robust power delivery system, dual PCIe 5.0 M.2 SSD storage slots, and solid connectivity. The motherboard supports Wi-Fi 7, 2.5Gb Ethernet, dual USB4 (40Gbps) Type-C ports, and front USB 20Gbps Type-C connector with up to 30W PD Fast-charge. It also offers enlarged heatsinks for the VRM, M.2 storage and PCH, as well as tools to overclock and fine tune various features.

Last but not least, the bundle includes a Corsair Vengeance RGB kit with two 16GB DDR5 modules running at 6000 MT/s, with a CAS latency of CL36 and timings of 44-44-96. The memory features black aluminum heat spreaders with a patterned finish, along with RGB lighting across the top of each module. It also supports both Intel XMP and AMD EXPO profiles, making it easy to apply pre-configured memory overclocking settings.

If we look at individual pricing, Ryzen 7 9800X3D is currently $469, while the Corsair RAM kit and Asus motherboard are listed at $499.99 and $289.99, respectively. You also get a CPU liquid cooler worth $79.99 and a copy of Onimusha: Way of the Sword worth $69.99. That puts the combined value at around $1,408.96, making the $1,109.99 bundle price a saving of nearly $300. If you're planning a high-end AMD gaming PC, this bundle is definitely worth exploring.

Architectural enhancements and significantly higher clock speeds enable Apple's A20 Pro application processor (AP), used in the company's latest iPhones, to deliver not only a substantial generation-to-generation performance boost but also to outperform leading desktop CPUs from AMD and Intel by up to a whopping 32% in the single-thread Geekbench 7 benchmark, setting the record for the highest single-thread performance. While high-end PC CPUs still have more oomph for multi-threaded workloads, the tiny A20 Pro is still faster than mainstream laptop CPUs even when many threads are involved.

Fastest smartphone SoC

Apple's A20 Pro system-on-chip (SoC) delivers 4,006 points in single-thread and 11,460 points in the multi-thread Geekbench 7 benchmark, which represents a 23.3% higher ST performance and 27.1% higher MT performance compared to the immediate predecessor, the Apple A19 Pro, according to an early submission (which may or may not demonstrate performance of actual A20 Pro-based products, so take the results with a grain of salt).

The new SoC delivers the highest generation-over-generation performance improvement for Apple's smartphone processors in years and is currently the highest-performing mobile AP. Furthermore, the A20 Pro beats AMD’s 16-core Ryzen 9 9950X3D by 26% and Intel’s Core i9-14900KS by 32% in single-thread performance.

When it comes to the single-thread Geekbench 7 benchmark, Apple's A20 Pro outperforms its closest rivals — Qualcomm's Snapdragon 8 Elite Gen5 (SM8850) and Xiaomi's XRing O3 — by 31.5% - 33.7%. In fact, both SM8850 and XRing O3 perform on par with Apple's two-years-old A18 Pro. The six-core A20 Pro also beats the eight-core SM8850 by 12.2% in multi-thread workloads in Geekbench 7 and offers roughly similar multi-thread performance to the 10-core XRing O3.

Compared with other flagship smartphone processors, Apple's A20 Pro holds a commanding lead in Geekbench 7. It is 76% faster in single-thread and 48% faster in multi-thread performance than MediaTek's eight-core Dimensity 9400, while it nearly doubles the performance of Google's eight-core Tensor G5, with advantages of 99% and 96%, respectively. But the most striking gap of A20 Pro is with Huawei’s Kirin 9050 Pro: Apple's flagship is 290% faster in single-thread and 139% faster in multi-thread Geekbench 7 workloads.

A great laptop CPU

While Apple's A20 Pro continues to feature 'only' six cores like many generations before it, this time around the processor packs two 'super' desktop-class general-purpose cores running at up to 4.93 GHz, four efficiency cores running at lower clocks, and a memory interface that delivers +50% higher memory bandwidth compared to its predecessor (allegedly using a 96-bit memory I/O).

The architectural enhancements of advanced CPU cores running at nearly 5 GHz, along with a more capable memory subsystem, not only enable a massive generational performance uptick, but also allow the chip to offer unbeatable single-thread performance and massive multi-thread performance that is comparable to that of laptop CPUs, including previous-generation laptop CPUs from Apple.

Indeed, Apple's A20 Pro is 7% faster than M5, 20% faster than M4, and 43% faster than M3 in single-thread performance. Its six-core design cannot match its multi-thread performance, trailing the 10-core M5 by 39% and the 10-core M4 by 27%. Yet, it is only 5% behind the eight-core M3.

When compared to Intel's Panther Lake, the A20 Pro is 48.7% faster in single-thread performance than the flagship Core Ultra X9 388H, yet the 16-core Panther Lake processor is 63% faster in multi-thread workloads. Against lower-end Panther Lake parts, the A20 Pro is 74% – 88% faster in ST workloads and even leads the Core Ultra 5 325 and Ultra 5 332 by 3% and 64%, respectively, in multi-thread benchmarks.

The particularly striking results of Apple's A20 Pro are the 26% – 33% single-thread advantage over flagship AMD and Intel desktop CPUs, though the desktop processors remain dramatically faster in multi-thread workloads.

First 2nm smartphone SoC

When Apple transitioned to TSMC's N3B (3nm-class) process technology from N4 (4nm-class) with its A17 Pro SoC back in 2023, the new processor was barely 9.8% faster in ST and 6.8% faster than its predecessor A16 Bionic. By contrast, with its first 2nm smartphone SoC made on TSMC's N2 node, Apple offers a massive performance boost over the A19 Pro produced on N3P.

Indeed, Apple's A19 Pro packs two 'desktop-class' 'super cores' whose design is 'driven in part by increased front-end bandwidth, a new cache hierarchy, and enhanced branch prediction,' as Apple described its 'super cores' inside the M5 processor earlier this year. Such architectural enhancements obviously massively increase performance in single-thread workloads at the cost of increased die size, transistor count, and power. Apparently, N2 enabled Apple's designers to squeeze two desktop-grade CPU cores into a smartphone SoC.

Speaking of M5, it is noteworthy that A20 Pro delivers 7.1% higher single-thread performance than M5 while running at a clock speed that is 7.1% higher than that of M5, which is probably a good indicator that Apple's A19 Pro uses the same 'super cores' as M5.

While some may consider using PC-grade general-purpose CPU cores in a smartphone chip an overkill, Apple is known for using and supporting PC technologies in its mobile SoCs (NVMe, PCIe, DisplayPort-over-USB-C, hardware virtualization, etc.). Keeping in mind that Apple also uses A-series SoCs inside iPads and inexpensive laptops, it makes a great sense to have these technologies in its smartphone application processors. With desktop-grade cores inside the A20 Pro, the company greatly expands use cases of these CPUs while also solidifying their position in traditional segments that they will address in the coming quarters.

Without any doubts, Apple's transition to TSMC's N2 starts with a massive general-purpose performance increase, driven by 'fat' super cores and a memory subsystem featuring 50% more bandwidth compared to the A19 Pro. Over the next few weeks, we are also going to learn how Apple upgraded the GPU, NPU, and other aspects of the A20 Pro, and we are going to find out whether the upgrades are as impressive or incremental. In any case, so far, the A20 Pro looks very good.

Discrete graphics card shipments for desktop PCs in Q2 2026 totaled 12.5 million units, the highest number since Q1 2022 despite record-high prices and cratering shipments of desktop CPUs, according to findings from Jon Peddie Research. The result highlights a broader trend that shows that unit sales of standalone GPUs for gaming have so far remained immune to rising prices, perhaps because gamers are expecting even higher prices in the coming quarters.

The industry shipped 12.5 million standalone graphics cards for desktop PCs in the second quarter of 2026, up around 5.9% sequentially and 7.8% year-over-year. 12.5 million add-in boards (AIBs) is the highest number of graphics cards sold in one quarter since the first quarter of 2022, when the industry shipped 13.38 million AIBs.

It is particularly noteworthy that 2026 is shaping up to be better for unit sales of desktop graphics boards than 2025 despite raising prices. For the first half of 2026, 24.3 million desktop AIBs were shipped, up significantly from 20.8 million graphics cards supplied in the first half of 2026. JPR analysts also note that only around 14 million desktop PCs were sold during the quarter, which — given an unusually high 89% attach rate — largely means that the majority of AIBs shipped during the quarter were aimed at gamers buying in retail and not at PC makers.

"Defying common wisdom, high-end AIB sales spiked as prices increased," said Jon Peddie, president of JPR. "Our theory is consumers rushed to buy AIBs before the prices went any higher, as the war in Iran is driving prices up in all segments."

Having shipped about 11.25 million discrete GPUs for desktop computers in Q2 2026, Nvidia remained the undisputed leader of the market with around 90% market share. AMD controlled roughly 8% of the market, shipping about one million discrete desktop GPUs, while Intel's share increased to 2% on shipments of several hundred thousand units. Meanwhile, Jon Peddie Research notes that market share changes were negligible during the quarter: AMD’s overall AIB market share decreased by -0.16% from the previous quarter, Intel's market share increased by 0.3%, and Nvidia's market share decreased by -0.1%.

For Nvidia, the quarter was particularly good as it sold the highest quantity of discrete GPUs for desktop PCs in a single quarter since Q3 2017, when it sold approximately 11.72 million units. By contrast, sales of AMD's standalone graphics cards have been floating below or around one million units per quarter for nearly four years now, with only three quarters being exceptions (Q3 2023, Q4 2023, Q4 2024). Still, one million is higher than the around 700 thousand discrete desktop GPUs the company sold in Q2 2025.

In total, Nvidia shipped approximately 17.365 million discrete graphics processors in the second quarter: roughly 11.25 million units went to desktops, and around 6.115 million units were installed into notebook and compact PCs. Since both AMD and Intel have quietly quit the market for standalone GPUs for mobile PCs, their shipments to this market segment were essentially zero.

Biren Technology, a leading supplier of AI accelerators from China, posted massive nearly 2,000% revenue growth in the first half of 2026 amid skyrocketing sales of non-Nvidia AI processors in the country, according to Jon Peddie Research. Sales of the company's products began to climb rapidly in the second half of 2025 after American companies led by Nvidia stopped supplying their AI GPUs to the People's Republic due to export control measures.

Biren reported first-half revenue of $183.9 million, up 1,998% year-over-year from around $8.665 million in the first half of 2025. The company's gross profit rose to $78.552 million, and gross margin increased to 42.7%, but it still lost $56.2 million primarily because it continued to invest in new products, including AI accelerators, optically-interconnected rack-scale solutions, and software. Biren's revenues started to climb in the second half of 2025, so for the whole year its sales reached $154.17 million as its market share of AI accelerators in the country was below 3%, according to TrendForce.

For those who follow China's AI and GPU markets, Biren Technology is certainly a familiar name as the company's products are well documented and appear to be competitive with those developed by AMD and Nvidia on paper. The company has developed at least three high-end AI GPUs — the BR106, BR110, and BR166 — and is currently working on BR20X, BR30X, and BR31X accelerators, according to JPR. Biren has also built its own Birensupa software stack meant to compete against Nvidia's CUDA and is working on a rack-scale solution.

In reality, demand for domestic AI accelerators has always been relatively low in China, as even cut-down versions of Nvidia's leading AI GPUs provided better performance and software stack than solutions developed in China. While Nvidia charged $12,000 - $15,000 per H20 AI GPU when it sold these products in the PRC, it still supplied some 2.2 million AI accelerators to the country in the first half of 2025, when it could still ship them until the Trump administration's export controls kicked off in May, according to TrendForce. By contrast, Biren shipped thousands, maybe tens of thousands of AI accelerators throughout the whole 2025. Even today, Biren's shipments are minuscule compared to Nvidia's in 2025.

Without a doubt, Biren's financial improvement is real and impressive, but it is coming from an extremely small base in the first half of 2025, so the 1,998% 1H 2026 growth figure makes Biren sound much larger than it actually is. While Biren is growing at an enormous rate, with $183.9 million in revenue, it is still a relatively small accelerator supplier in absolute terms.

What remains to be seen is whether Biren can secure enough manufacturing capacity from SMIC or other suppliers to compete with larger Chinese AI accelerator vendors, such as Huawei, Kunlunxin, and Cambricon. The company certainly has more financial resources than it did a year ago and faces less formidable competition from AMD and Nvidia amid U.S. export restrictions and China's own bans on American AI hardware. But having competitive designs is only part of the equation: Biren now must manufacture enough accelerators to satisfy customer demand and substantially increase its market share.

Intel is reportedly set to hike CPU prices by 10%, according to a new Digitimes report. Citing supply chain sources, the outlet says the increase follows two others, one in the first quarter of 2026 and another in July, among some server and client CPUs. Notably, the sources didn't say which products the price increase applies to, though presumably, the increases would come through Intel's mobile and server businesses before desktop client. Citing industry sources, DigiTimes also reports that Intel is set to launch "major annual products" in March 2027, with AMD following up with launches of its own between June and July.

The increases come on the back of Intel seeking higher gross margins for its products as the PC market shrinks. This is a story we've heard directly from Intel in the past. In its most recent earnings call in July, Intel chief financial officer David Zinsner attributed a 13% YoY increase in Intel's client revenue to higher average selling price, not a higher volume of sales.

Although the Digitimes report doesn't clarify which products will see a price increase, server and mobile seem like the most likely candidates. Intel's most recent Panther Lake calls for high-speed LPDDR5X-7467 memory as a minimum, and last-gen Lunar Lake CPUs have on-package memory. Naturally, higher memory prices put more pressure on fully built systems like laptops more so than socketed, standalone desktop processors.

On the server end, there's been an unprecedented increase in demand for server CPUs on the back of agentic AI workloads. That demand led to several consecutive records for Intel's share price, even without any major product announcements. Earlier in the year, Wall Street estimated the server CPU market would rise to around $120 billion by 2030 (currently around $30 billion). Now, those projections go up to as high as $220 billion.

According to the report, Intel is set to launch a major new annual product in March 2027, followed by AMD between June and July. Last week, a leaked Intel roadmap showed the company's next-gen Nova Lake desktop CPUs entering mass production in Q4 2026 with a release in Q1 2027, lining up with DigiTimes' report.

Although the timelines line up, the rumor mill has suggested an early Q1 launch for Nova Lake. It's worth noting that the DigiTimes report doesn't make mention of which product Intel will launch in March. This year, for instance, Intel launched its Xeon 600 CPUs for HEDT in March.

Perhaps more interesting is the AMD timeline. We already know of one major AMD product launch in the second half of 2027, which is Venice-X. Those are Zen 6 server CPUs with AMD's 3D V-Cache, packing up to 1,152 MB of L3 cache on the chip. Otherwise, that timeframe seems to point to AMD's next-gen desktop CPUs with the Zen 6 architecture, codenamed Olympic Ridge.

AMD launched its Venice server CPUs earlier this year, the first sporting the Zen 6 architecture. We haven't heard anything official about Zen 6 in the desktop yet. That's strange given AMD's last several releases. There was about a two-year gap between Zen 3 and Zen 4, as well as Zen 4 and Zen 5, on desktop. We've just crossed the two-year mark for Zen 5, so assuming AMD keeps a similar launch cadence, we'd expect to hear something sooner than June or July or next year.

That same explosive demand in server CPUs could have changed AMD's launch plans, however. Given that we haven't heard anything official about Olympic Ridge at this point, a launch in June or July isn't out of the question.

AMD announced what it calls "the most powerful workstation in the world" at IFA 2026, dubbed the Threadripper Halo Station. The machine includes a Threadripper Pro 9995WX with 96 Zen 5 cores, dual liquid-cooled Instinct MI350P accelerators "with a path to four," 2TB of DDR5, and 288GB of HBM3E with up to 576GB supported. AMD claims the workstation is capable of running trillion-parameter models.

Taking all of the components together, the street price should come out to over $100,000 with just the core components: memory, CPU, and dual GPUs. Configured higher, and with supporting storage, power, and cooling, the workstation could very easily climb over $150,000.

It's essentially a server tray reconfigured into a tower, with an EPYC host replaced with a 96-core Threadripper. AMD didn't share many details about the machine outside of the specs, though it appears to be a system design that AMD's OEM partners will ultimately build and ship. AMD has yet to announce any partners supporting the machine.

The Threadripper Pro 9995WX at the heart of the machine is a 96-core, 192-thread Zen 5 chip that can boost up to 5.4 GHz. It ships with 384 MB of L3 cache and has a TDP of 350W. It's hard to find Threadripper Pro standalone chips in general, but the 9995WX clocks in at around $11,000 to $12,000.

The MI350P accelerators come with 128 CDNA 4 compute units built on TSMC N3. Each accelerator packs 144GB of HBM3E memory, giving the system 288GB of HBM3E. AMD says there's a "path to four," opening up the possibility of two more accelerators bringing 576GB of HBM3E to the system. You'll need plenty of power to feed the GPUs, as each accelerator is rated for up to 600W.

Although AMD says it can support up to four accelerators, the workstation shown off at IFA only has room for two, both of which are liquid-cooled, alongside the Threadripper host. AMD doesn't sell MI350P accelerators on their own in traditional consumer channels, but the estimated price is somewhere around $20,000 per accelerator.

At a system level, the Threadripper Halo Station includes 2TB of DDR5 memory, which is the maximum capacity supported across the eight-channel memory configuration of the Threadripper Pro 9995WX. AMD supports up to DDR5-6400 on the Threadripper, though it made no mention of speed during its IFA presentation. Regardless of speed, 2TB of DDR5 costs about $50,000 right now.

AMD has yet to set a price or release date for the Threadripper Halo Station, though we'll likely hear more about the design from AMD's partners in the near future. An extremely expensive workstation isn't out of the question. The Lenovo ThinkStation P8, for instance, which uses Threadripper Pro CPUs as a host, clocks in at $334,463 right now, maxed out with 2TB of DDR5 and dual Blackwell accelerators.

Sales of discrete graphics processors for consumer PCs were up both sequentially and year-over-year in the second quarter despite soaring prices caused by component shortages, according to a newly released report by Jon Peddie Research. Although PC CPU shipments dropped in Q2 2026 year-over-year amid seasonality and shortages, sales of standalone graphics processors for consumer computers were up 12.2% sequentially and 14.1% YoY, the best market dynamics in some time.

Sales of graphics processing units for consumer PCs — which include integrated and standalone GPUs for desktops and laptops — totaled 75.5 million in the second quarter of 2026, up 10.4% quarter-over-quarter and 1.1% year-over-year, primarily driven by notebooks. This happened as the consumer CPU market contracted by 1.1% YoY amid a massive sequential drop in desktop CPU shipments and a significant rise in mobile CPUs shipments. Desktop GPU shipments declined by 4% quarter-over-quarter, while notebook GPU shipments surged by 16.8%, JPR claims.

But despite declining desktop PC unit shipments and modest growth in notebooks, unit shipments of discrete GPUs increased by 12.2% sequentially and 14.1% year-over-year in Q2 2026, according to JPR data. Jon Peddie Research does not publish absolute numbers of standalone graphics processors shipped in the second quarter, but our estimate is that around 20 million discrete GPUs were sold by AMD, Intel, and Nvidia in Q2, based on attach rates and Nvidia's market share and dynamics.

The results indicate that demand for PCs with discrete graphics remained remarkably resilient despite soaring component prices and slowing demand for desktop PCs. However, JPR's shipment data does not reveal whether the increase was primarily driven by gamers buying graphics cards, stronger demand for gaming notebooks, or other factors.

"The second quarter is typically down compared to the previous quarter," said Dr. Jon Peddie, president of Jon Peddie Research. "This quarter, discrete GPUs increased by 12.2%, even while a global memory crisis sent component prices soaring, driven by a mix of supply-side positioning, artificial demand shocks, and localized market dynamics."

Jon Peddie Research has yet to publish its complete desktop AIB report, which is expected later this month and will include market shares for AMD, Intel, and Nvidia; yet it is safe to say that the latter has maintained its undisputed leadership.

As for the overall consumer PC GPU market, Intel retained its leadership with a 56% market share as it increased shipments of consumer CPUs in Q2 2026. Nvidia came second with 23%, which is not bad at all considering that it only ships discrete GPUs. AMD came third with 21% share, up significantly from 14% in the same quarter a year ago, as it managed to gain seven percentage points of the consumer GPU market YoY amid growing sales of its consumer CPUs.

TIME published its 2026 TIME100 AI list last week, with one notable omission: Jensen Huang, one of eight TIME-designated “Architects of AI,” whose GPUs power the training infrastructure for all frontier AI models and whose company has just reported one of the largest sets of quarterly earnings in American corporate history. AMD CEO Lisa Su is missing too, while Ben Affleck, Senator Bernie Sanders, and Paris Hilton all managed to clear a bar that the heads of the industry’s two dominant GPU makers apparently couldn’t. Aside from TIME’s Architect of AI and joint Person of the Year designation for 2025, Huang has featured on every previous edition of the TIME100 AI. This year, however, Nvidia’s sole entry is Josh Parker, the company’s head of sustainability.

Broadcom CEO Hock Tan, Micron CEO Sanjay Mehrotra, SMIC co-CEO Liang Mong Song, and Huawei HiSilicon president He Tingbo all appear on the 2026 list, joined by Cerebras’ Andrew Feldman, CoreWeave’s Michael Intrator, and Nscale’s Josh Payne. Together, the roster includes Nvidia’s HBM supplier, two of its biggest GPU cloud customers, its custom-accelerator rivals, and China, which is trying — and so far struggling — to replace Nvidia altogether.

Parker’s profile, which appears under the Thinkers category, focuses on data center energy and water consumption, alongside Nvidia’s tripling of Scope 3 emissions in two years, and the Rubin platform’s shift to 100% liquid cooling. “Nvidia is at the center of the AI revolution,” Parker told TIME.

TIME editor-in-chief Sam Jacobs wrote in the list’s accompanying article that selection was led by editor Ayesha Javed, and that the 100 honorees represent the year’s “key storylines and who, in our opinion, are having the most influence in driving these developments.” Now in its fourth year, this edition of the TIME100 AI appears to have focused especially on featuring the new additions to TIME’s community of AI leaders, with Mark Zuckerberg, Demis Hassabis, Sundar Pichai, and Satya Nadella representing four other honorees, arguably deserving of a space on this year’s list, churned out.

Su’s strong TIME back catalog makes her omission all the stranger still. The magazine named her its 2024 CEO of the Year, put her on the 2024 AI list and the main TIME100 in 2025, and included her among December’s Architects of AI.

Nvidia’s second-quarter results, reported August 26, totaled $96.2 billion in revenue, including $89 billion from data centers, up 117% year-over-year. The company became the first to cross a $5 trillion market cap last October, and posted a $57 billion record quarter three weeks later.

AMD has been the dominant force in DIY PC building CPUs for several years now, thanks to the advent of Zen 3 and great chips like the Ryzen 7 5800X3D, and more recently its potent Ryzen 7 X3D SKUs like the 9800X3D. Now, just days after AMD touted that it continues to occupy all 10 slots in the Amazon CPU best-sellers list, a couple of Intel CPUs have broken into the list for the first time in months, as spotted by WCCFTech.

The two chips in question aren't surprising if you know ball. Coming in at number six is the Core Ultra 7 270K Plus for $290 USD; Intel's most recently released desktop CPU, and at nine we have the workaday Core i7-14700K for $312, a steady seller since its launch in 2023. It offers less performance in gaming than many of the other chips in the top 10 (including the cheaper 270K Plus), but it has the advantage of being able to slot into both aging LGA 1700 systems as well as new builds with DDR4 memory. That's also likely why the Ryzen 5 5500 continues to stay near the top of the chart at #2, while the Ryzen 5 5600X and Ryzen 7 5800X3D (in its 10th Anniversary guise) also rate high. As for the Core i7-14700K, we actually recommended it over the Ryzen 7 5800X3D in our review of the 10th Anniversary re-release of that chip for people who are building new DDR4 machines.

The Core Ultra 7 270K Plus appearing this high is heartening for Intel's sake, though. If you haven't kept up with Intel's CPU releases, this chip is a course correction from the first-generation "Arrow Lake" processors, offering outstanding productivity performance and very solid gaming performance, just a few percentage points off of the beloved Ryzen 7 7800X3D that sits one position above it in the rankings. Put frankly, the Core Ultra 7 270K Plus beats everything else in the top 10 for both single- and multi-core performance save for the $569 Ryzen 9 9950X3D, which is in an entirely different price class from the $290 Intel chip (though discounted quite significantly at $569, 19% off the $699 list price)

It's clear that gaming continues to be a top driver for the DIY market. Five of the chips in the top 10 have been on our list of the Best CPUs for Gaming either now or at some point, including the number one seller, the Ryzen 7 9800X3D. AMD's 3D V-Cache continues to be unbeatable in gaming, even if the Arrow Lake 'Plus' parts do their best to close the gap with extremely high single-core performance. It's not single-threaded speed that's the bottleneck anymore, though, and not for some time; the limitation in gaming frames is multivariate as it has ever been, but on the CPU side, it's largely down to memory performance these days, and that's exactly why AMD's 3D V-Cache chips dominate.

Of course, if you're reading Tom's Hardware, you probably don't need me to tell you that. But it's interesting to look at the pricing of the parts that are moving the most units. The Ryzen 5 5500 is a tame processor, but if you need a gaming PC for the absolute bottom dollar, it's hard to beat six Zen 3 cores with a CPU cooler for $84. The Ryzen 7 7800X3D seems an absurd choice next to the much faster Ryzen 7 9800X3D for less than $100 more, but the gaming performance is really pretty close, and you're likely to desire a drop-in Zen 6 processor upgrade late this year or early next year, so why spend the extra $85 now?

That CPU upgrade angle warrants consideration. Any Socket AM5 processor has a path forward, and that's not the case for any extant Intel platform nor for Socket AM4, despite the fact that Intel is apparently releasing new LGA 1700 chips eventually. Ultimately, memory pricing is probably driving a lot of these choices, but in the upgrade context, it's not quite as surprising to see five and a half of the top ten CPUs on platforms that require DDR5 memory—the 'half' being the Core i7-14700K, naturally.

You absolutely can build a DDR4 machine using the Raptor Lake Refresh CPUs, but the performance penalty can be significant; in our testing, we found that it was actually worse than just running a single DDR5 DIMM. It's the PC builder's Sophie's Choice: buy a last-generation CPU to save significant cash on the RAM, or suck it up and spend out massively on a system that offers the best performance now.

Pricing is naturally also a factor; the Core Ultra 7 270K Plus launched at the comically low price of $299 in comparison to the $589 Core Ultra 9 285K, which it performs very close to, so $290 isn't much of a discount there. Meanwhile, the Core i7-14700K's $311.99 price tag is 16% off of Amazon's list price of $370.99, but it's a bit larger markdown from Intel's $419 recommended customer price. Still, if pricing is your primary motivator, it's hard to ignore the $330 Ryzen 7 7800X3D (27% off list), at least as long as gaming is your main concern. There's the 5800X3D 10th Anniversary, too, but again, the Core i7-14700K actually offers better minimum framerates and vastly superior productivity performance, especially if you're willing to do some memory tuning.

Clearly, gamers have accepted that memory pricing isn't coming back down any time soon, and that the time to buy is now before it gets even worse. The shortage isn't expected to abate between now and late 2028; if you're keen to build a new machine in the in-between, make sure you keep an eye on our Deals posts to save yourself from bleeding too much at the checkout.

The second quarter of 2026 was quite favorable for CPU suppliers, as unit growth was 10% sequentially, with data center and laptop processor shipments more than offsetting declining sales of desktop CPUs and lower-end products for embedded and IoT applications, according to a new report by Mercury Research. AMD continued to gain market share, so its unit shipments and share reached a new record during the quarter; Intel managed to increase shipments of its client and data center CPUs; whereas Apple sold a boatload of processors in its popular MacBook Neo laptops. Overall, the report describes the desktop X86 CPU market as "ugly."

The sky is blue for CPU (for now)

"In spite of a decidedly gloomy outlook on client processors from the suppliers for the second quarter, actual results for both x86 and Arm CPUs were up strongly in the second quarter of 2026, with sequential quarterly growth of the total market exceeding 10%, far in excess of normal seasonal trends which call for a slight decline in the quarter," said Dean McCarron, principal analyst at Mercury Research. "Behind this growth was a large increase in Intel's CPU supplies, especially in mobile client, after a couple of heavily supply-constrained quarters, and continued strong ramps for AMD's products. […] Arm shipments also appeared to be strongly higher in the quarter as well."

While the CPU market was up quarter-over-quarter (QoQ) mostly because AMD, Apple, and Intel increased their shipment volumes, on a year-over-year (YoY) basis, the CPU market contracted in terms of units. However, the decline was primarily driven by significantly lower IoT, SoC, and embedded shipments — largely due to AMD's shrinking game console business — as well as a substantial drop in desktop CPU volumes. At the same time, shipments of data center and notebook processors grew strongly.

Excluding IoT, SoC, and embedded products, both AMD and Intel substantially increased CPU shipments sequentially, but AMD grew faster and gained unit share in every major segment, so the company now controls 30.7% of the overall x86 processor market, its highest share ever, according to Mercury Research. With IoT, console SoCs, and embedded CPUs included, AMD now controls 34.1% of the x86 processor market. Intel continues to lead, but AMD's growth is impressive.

"AMD's total unit shipments and total market share reached new record highs in the second quarter of 2026, with a sequential share gain of 0.7% and an on-year gain of 6.5%," McCarron said.

Client CPUs: AMD gains share as Intel increases shipments

Performance of the client x86 CPU market was a mixed bag in the first quarter as sales of desktop CPUs declined badly, whereas shipments of laptop processors grew significantly. Intel remained the clear volume leader with 69.7% of client CPU shipments, but lost share both sequentially and year-over-year. AMD continued to gain ground in Q2 2026 as its unit share reached a record 30.3%, up from 29.6% in Q1 and 23.9% in Q2 2025.

AMD gained share in both client categories. Its desktop unit share rose from 33.2% to 34.9% QoQ, even though AMD itself shipped fewer desktop CPUs; Intel's shipments declined even faster. In notebooks, AMD increased its share from 28.3% to 28.9%, even as Intel expanded production capacity and shipped millions more CPUs.

In general, the results for the quarter suggest that Intel's improved client CPU supply helped to meet demand from PC makers and led to a client PC market rebound, the company could not stop AMD's share gains.

Desktop CPUs: The ugliest segment of the market

Hit by limited availability of graphics cards and high prices of components like motherboards, memory modules, and SSDs, the desktop CPU market was particularly weak in Q2 and contracted by over 20% YoY as well as quarter-over-quarter due to seasonality. Both AMD and Intel suffered significant annual shipment declines, but AMD held up better, according to Mercury Research.

Despite dropping desktop CPU unit shipments and overall market weakness, AMD increased market share in Q2 2026. AMD's desktop CPU unit share upticked to 34.9%, up from 33.2% in Q1 and 32.2% in Q2 2025, while Intel's share fell to 65.1%, from 66.8% sequentially and 67.8% a year earlier.

During the quarter, AMD gained 1.8% QoQ and 2.7% YoY in unit share because declines in its shipments were considerably smaller than Intel's. So, while normally we say that AMD is gaining desktop share because of strong sales of its latest Ryzen CPUs, in this case AMD's success was driven by slower declines than rapid gains.

Mobile CPUs: Sales of laptops are growing

The mobile CPU market segment performed completely differently from the desktop CPU market segment. Mobile x86 CPU shipments grew significantly quarter-over-quarter and were also modestly higher YoY. Mercury Research says Intel added millions of units of mobile CPU capacity during Q2, which helped close the supply-demand gap that had constrained the company in previous quarters. Yet, AMD's shipments increased at nearly the same pace as Intel's, which enabled it to capture 0.6% of the market.

AMD's mobile CPU unit share rose to 28.9%, up from 28.3% in Q1 and from 20.6% in Q2 2025. Intel remained dominant with 71.1% of shipments, down from 71.7% sequentially and 79.4% a year earlier. As a result, AMD gained a modest 0.6% sequentially, but a much more impressive 8.4% YoY increase.

Server CPUs: +20% year-over-year

Demand for server CPUs increased for both traditional data center processors — AMD EPYC and Intel Xeon — and CPUs used in networking and storage applications, so x86 server processor shipments posted nearly 20% YoY growth and moderately strong sequential growth. AMD continued to gain market share and now commands over 1/3 of the server CPU market, according to Mercury Research. There is a catch, though: due to Intel accounting peculiarities, AMD's unit share is artificially low and so is Intel's own dollar share.

In Q2, AMD’s server CPU unit share increased to 34.5%, up from 33.2% in Q1 and 27.3% in Q2 2025. Intel remained the volume leader with 65.5% of shipments, but its share fell from 66.8% sequentially and 72.7% a year earlier. While some may say that AMD's gains are slow (not too slow at +7.3% YoY), there is an explanation behind that slow growth.

Mercury Research notes that its broad server share calculation somewhat disadvantages AMD because Intel's edge and networking processors are now reported within its Data Center and AI (DCAI) business, so in reality, AMD's unit share should be higher. If the comparison is narrowed to EPYC versus Xeon processors for servers, AMD's unit share reaches 46.4%, up a substantial 2.9% QoQ and 9.2% YoY, which puts AMD very close to Intel in the core data center CPU market. Meanwhile, if CPUs for edge and networking applications are ignored in Mercury's analysis, Intel's dollar share would increase considerably.

Mercury Research indicates that server CPU supply constraints could limit gains in Q3, but in Q4 sales of data center-grade processors will increase noticeably both compared to Q2 and Q3.

Summary

After a weak Q1, the CPU market rebounded strongly in Q2 2026 as unit shipments grew more than 10% sequentially. The market growth was driven by rising notebook and server CPU sales, which more than offset a sharp decline in desktops, according to Mercury Research.

AMD's performance was stellar as it gained ground in every major segment even as Intel substantially improved processor availability. Despite improved availability of Intel client and data center processors, AMD still outgrew Intel and reached record overall and client CPU unit shares.

Desktop remained the major weak spot due to high component costs and generally lower demand as enthusiasts pulled in their purchases to 2025, greatly lowering sales of high-end hardware in 2026. Shipments of desktop x86 CPUs fell more than 20% YoY, whereas mobile and server volumes increased.

In core data center processors, AMD's EPYC share approached Intel’s Xeon share, which highlights how dramatically the competitive balance in the server market has shifted.

In addition to its normal product and technology roadmaps, AMD has effectively made its 'X-by-year' efficiency programs a recurring engineering roadmap. Back in 2025, the company unveiled its 20x2030 initiative that promised to increase energy efficiency of its rack-scale AI solutions 20 times by 2030. Back then, AMD envisioned that its 2026 rack-scale AI systems will be 3X more energy efficient than its 2024 machines. However, the new estimates published on Tuesday indicate that its latest solutions are 4X more efficient compared to the 2024 baseline.