There are a lot of salesman sayings, and, chances are, most were inspired by audiophiles. The eternal sufferers of audiophilia nervosa keep coming up with novel ways to attribute sonic and emotional characteristics to any piece of equipment — even when discussing things purely in the digital realm. One of the current fads is audiophile-grade network switches, like the Aurender NH10 Network Hub, coming in at a mere $4,700.

This piece of gear —which we presume is actually a network switch, rather than a hub — comes fitted with eight gigabit ports. Six of those are standard copper inputs, while the other two are SFP ports where audiophiles can plug in a transceiver for either fiber or copper. The product page remarks that, naturally, a fiber connection is electrically isolated. I was teeing up a joke about the existence of audiophile-grade SFP transceivers when, while proofreading, I found that life does truly imitate art. Oh, and that $4,700 doesn't even get you 10 GbE capabilities.

Four of the six copper ports on the Aurender switch have a total of seven electrical filtering stages behind them, while the remaining pair "only" has two. According to an article at Headphonesty, Aurender's designer said the team experimented with using over 10 stages, but eventually settled on seven "from listening comparisons." That's an interesting feature considering that the Ethernet standard already mandates electrical isolation for standard twisted-pair connections.

Aurender also says that it's using an OXCO (Oven-Controlled Crystal Oscillator) controlled by an FPGA for clock synchronization, and there's a BNC input on the back for an external source. From what we can tell from the board picture, the main chips include: a Realtek RT8370N switch controller ($5.5 at LCSC, an MV85 oscillator ($39 on eBay), and an AMD/Xilinx Spartan 6 FGPA ($8-15 depending on model). There are, no doubt, more manufacturing and materials costs to go from a collection of chips to an assembled switch, but presumably not enough to get anywhere close to the $4,700 asking price of the NH10.

This is all adorable, but the fact of the matter is that the hardware here cannot, by any reasonable definition, make any difference to the sound. TCP connections have built-in error correction. The Ethernet protocol includes Cyclic Redundancy Check (CRC), and there are several similar layers, up to the point where the data turns into an actual analog signal.

It's also up to whichever equipment is handling the playback to electrically isolate the actual DAC output stage, not at the network or switch level. And even affordable audio interfaces have signal-to-noise ratios that 1970s recording engineers would happily give up their LSD for.

Likewise, the whole conversation about jitter is pointless, though much like any audiophile myth, it's grounded in a piece of truth — just one that's completely irrelevant in this scenario. In a recording studio, you occasionally need to sync the clock across multiple pieces of gear, just like matching tape machines back in the day. For just the one piece of playback gear, however, it's pointless, and it's downright nonsensical at the network level.

Yet logic has never stopped some self-described audiophiles. One can but wonder what folks seriously looking at these pieces of gear would feel knowing that the studios where their precious music is being made use, for example, one bog-standard Ethernet cable to carry 4 balanced analog lines. Or how their favorite guitarist's pedals and amplifier in a famous recording session were held together with lamp cord, duct tape, hopes, and dreams.

It’s a tough time to launch an external SSD, with demand for flash and RAM at all-time highs thanks to AI hyperscaler demand. But content creators, videographers, and media collectors need more, faster, and roomier options, so Samsung has launched its first USB4 external drive, the Portable SSD P9.

It’s offered in 1, 2, 4, and 8TB capacities (but currently only in stock at 2TB as of this writing), with rated sequential read speeds up to 4,000 MB/s and write speeds up to 3,800 MB/s, a slim (0.3-inch) but simple boxy solid shell. It also includes one of the nicest-feeling sleeved cables I’ve come across (that’s also long for an external drive, at 16 inches). The Samsung P9 is a premium, pocket-friendly portable drive that’s speedy enough to potentially knock Corsair’s EX400U out of its top USB4 drive spot on our list of the best external SSDs.

It’s also quite expensive, starting at $339 for the 1TB model, $649 for the 2TB version we tested, and commanding a whopping $2,879 for the 8TB model. Those prices might seem extreme, given Corsair’s competing USB4 drive launched at $119 for 1TB in early 2025. But as we’ll see below in our comparison section, Samsung’s pricing isn’t exactly exorbitant compared to the current price of USB4-based competition – and many alternatives that launched last year are tough to find in stock.

Samsung P9 Specifications

Design and accessories

At 3.5 x 2.6 x 0.3 inches and weighing 0.21 pounds, the P9 is neither the smallest external storage drive, nor the lightest. But it’s slimmer than the company’s previous-generation T9 drive (which is 0.55 inches thick and roughly half as fast, at 20 Gbps). It ditches the rubber, textured, dust-collecting coating of the T9 for a metal shell on the P9 that feels very solid. The bottom of the P9 is coated in rubber to keep it in place on your desk.

There are no IP ratings for dust or wind resistance in Samsung’s spec sheet, and I don’t love the visible seam around the subtly rubberized bottom. But the P9 feels rigid and solid, to the point that I am pretty confident it could sustain more than its rated 2-meter drop rating.

There’s also a lot to like about the included cable, which is the only bundled accessory (unless you count paperwork). The cable is roughly 16 inches long, not counting the USB-C plugs on either end, and braided in a way that feels better than even other braided cables in my USB arsenal. There are even two Velcro-like hook-and-loop fasteners on the cable to keep any excess under control. Yes, it is just a cable, but I appreciate the ample length for us desktop PC users, and it is one of the nicest-feeling cables I’ve used.

Samsung Magician Software

Samsung includes a Samsung Magician Launcher link on the drive, but it’s really just a pop-up box that prompts you to download the latest version of the software. The app has widgets and sections for drive health and management, temperature and performance, diagnostics, monitoring, secure erasing or encrypting the drive (256-bit hardware encryption is supported), and more.

It’s one of the more feature-rich SSD toolboxes, and benefits from Samsung’s long history in the storage realm. But it also has a mobile-app-first design that makes it look big and clunky on a desktop, with rounded corners. On the 65-inch TV that I use as a monitor, the Drive Health gauge defaulted to something close to the size of my head, and toggling to the compact version hides nearly everything but that single gauge widget. While that is of course an extreme example, the software just has a big UI for the information it presents.

Comparison products

Samsung has a fair amount of competition on the USB4 drive front, but much of it is increasingly scarce, likely due to flash availability. Sandisk’s Extreme Pro is the most recent USB4 competitor we’ve tested, with the 2TB version selling for $549, or $100 less than the P9.

LaCie’s Rugged SSD4 launched a little over a year ago and performed very well on both Windows machines and Macs. But it’s listed as sold out or no longer available in many places. As of this writing, it was available at Micro Center and a couple of online outlets, for between $750 and $800 for the 2TB model.

Corsair’s magnetic-backed EX400U has long been our favorite USB4 drive, for its compact size, performance, and value. But Corsair’s drive is also becoming hard to find in stock. And, like everything else in this space, its price has risen as well, with the 2TB version selling for $692 when I wrote this.

For those who don’t absolutely need USB4 speeds, the latest iteration of Crucial’s X10, a 20 Gbps drive with effectively half the bandwidth of these competing USB4 drives, is selling for $399 for the 2TB model. It’s very good for a 20 Gbps drive, but obviously that’s a different performance class than USB4 (40 Gbps).

With all that perspective, the $649 2TB Samsung P9 still feels expensive — if the drive launched a little over a year ago, it would likely have been roughly a third of this price. And it is $100 more than its Sandisk competitor, but it’s still priced a little less than other, older options. Let’s see how it performs.

Storage testbed

In 2025, we updated our external storage testbed to an AMD Ryzen 7600X-based PC with an Asus ROG Crosshair X870E Hero motherboard, installed in Lian Li’s Lancool 217 case. This was done in part because we needed a system with native USB4 support for upcoming drives (like this one).

All the drives in the charts below have been re-tested on the new X870E system, with the exception of the final Iometer sustained sequential test. That benchmark is less about top speed and more about how long a drive can write before depleting any fast cache onboard. We also updated to CrystalDiskMark 8, rather than the older (and non-comparable) version 7 we used on the previous testbed.

Trace Testing - PCMark 10 Storage Benchmark

PCMark 10 is a trace-based benchmark that uses a wide-ranging set of real-world traces from popular applications and everyday tasks to measure the performance of storage devices.

Samsung’s P9 doesn’t start off our test suite looking its best. It (unsurprisingly) falls behind LaCie’s Thunderbolt 5 drive (which is currently priced at $1,999 for the 4TB model we tested), but it also lands behind USB4 drives from LaCie and Sandisk in PCMark 10. It did, though, fare better than Corsair’s USB4 EX400U here.

Transfer Rates — DiskBench

We use the DiskBench storage benchmarking tool to test file transfer performance with a custom 50GB dataset. We copy 4,617 files (images, videos, and software ISO files) to a folder on the test drive (write). Then, after leaving the system idle for five minutes, we run the same test in reverse, moving the test folder to a different location on our PCIe 4.0 testing drive.

Samsung’s P9 led the pack in this real-world write speed test. Although its read speed technically landed it in fourth place, it again easily beat Corsair’s USB4 drive, and was close to Sandisk’s drive, which was less than half as fast when it comes to writes in this test. Note the somewhat odd performance of LaCie’s TB5 drive here, which is capable of being faster on Apple hardware, but did not perform very well on our USB4 testbed in some tests.

Synthetic Testing: CrystalDiskMark

CrystalDiskMark (CDM) is a free and easy-to-run storage benchmarking tool that SSD companies commonly use to assign performance specifications to their products. It gives us insight into how each device handles different file sizes. We run this test at its default settings.

The Samsung P9 looks its best on this synthetic, best-case-scenario benchmark, landing in first place in both reads and writes. Most of the other high-end drives were close, save for SanDisk’s USB4 SSD, which is a few hundred MB/s slower on read speeds, but was still fast.

Sustained Write Performance

A drive's rated write specifications are only a piece of the performance picture. Most external SSDs (just like their internal counterparts) implement a write cache, or a fast area of flash, programmed to perform like faster SLC, that absorbs incoming data.

Sustained write speeds often suffer tremendously when the workload saturates the cache and slips into the "native" TLC or QLC flash. We use Iometer to hammer the SSD with sequential writes for 15 minutes to measure the size of the write cache and performance after the cache is saturated.

Samsung hasn’t disclosed SLC cache size for its P9 drive, whether it’s fixed or dynamic, or if it differs by capacity. In other words, our 2TB P9 drive may be at a disadvantage here, at least compared to the 4TB LaCie and Crucial drives in our chart. But regardless, the Samsung P9’s performance on this test is largely positive, if somewhat complicated.

For roughly the first minute, the P9 wrote close to its max spec, around 3,750 MB/s. It then dropped to a write speed that fluctuated between just below 2,200 MB/s and just above 2,400 MB/s, which is still quite fast. It maintained that speed range for the next 12 minutes of writes, before dropping into the 600-800 MB/s range.

Sandisk’s Extreme Pro USB4 drive maintained its initial speed, around 3,500 MB/s, for roughly three times longer. But when its cache was exhausted, it dropped lower, first to roughly 1,200 MB/s, and then to around 800 MB/s. Looking beyond our usual 15-minute test, the Sandisk drive stayed in the same 800 MB/s range after the 15-minute mark, until we stopped the test at 30 minutes. The Samsung P9, however, recovered a good chunk of its write speed after about 17 minutes, switching back into its “middle” write range of 2,200-2,400 MB/s, from then until the end of the 30-minute test.

Corsair’s EX400U was more consistent in this test, but its write speeds never topped 1,800 MB/s, and it frequently dipped below 1,600 MB/s. Samsung’s P9 is flatly in another class, even though these are both USB4 drives.

Bottom line

As much as $649 for a 2TB external SSD still feels like a lot, the Samsung P9 performed very well in our testing. It wasn’t always at the top of the charts, but it consistently beat Corsair’s EX400U, which costs a little more now, if you can find it.

Sandisk’s Extreme Pro USB4 costs $100 less at 2TB, and $340 less at 4TB (and the P9 wasn’t even in stock at that capacity when this was written). But Sandisk’s drive has been on the market longer, and I would expect the two drives' prices to land close to each other once the P9 has settled into the market — that said, they both very well could go up in price, given recent trends.

Regardless, Samsung’s P9 drive is faster in most scenarios, particularly when it comes to sustained write speeds, which are important to professional users. And Samsung’s drive is about a third smaller, making it more travel-friendly. So while you could easily get by with Sandisk’s drive and save some money, Samsung’s P9 is a better USB4 drive if you want the best, fastest option for serious storage demands.

Intel has published an internal test driver with the "RPL-NEXT" label, presumably in reference to Raptor Lake Next CPUs that Tom's Hardware first reported on in June. On the same day as the driver was uncovered, shipping manifests from Vietnam were published by Club386, showing exports of CPUs labeled "Raptor Lake Next" dating back to August, complete with cache and clock speed information.

The driver was first spotted by @momomo_us on X, and we were able to find it by searching the name in Intel's software database. The file is locked (hence the padlock icon), and clicking on it will redirect you to an Intel login page. Given that and the "testbuild" label, it looks like this is an internal driver test that wasn't meant to be published.

Judging by the existing conventions, the driver package is for the Smart Sound Technology (SST), a audio digital signal processor integrated into the silicon since the Alder Lake days. Audio codecs like those of Realtek use SST for offloading duties like noise reduction, echo cancellation, low-power audio playback, and wake-on-voice without adding to the CPU load, and saving precious watts in the process.

For broader context, Raptor Lake Next is Intel's refresh of the Raptor family of CPUs, meant to plug into existing LGA-1700 motherboards. Given the currently insane DDR5 memory prices, gamers ought to be happy on two fronts: getting newer chips for their existing motherboards, and the ability to use more affordable DDR4 instead, an ability all but confirmed by Gigabyte's recent BIOS updates.

According to Club386's shipping manifests, there are so far four chip models en route from Intel's Vietnam facilities. Their specs suggest that they're replacements for extant Core i5 and Core i7 models, as a previous leak indicates that Intel doesn't yet have any plans for replacements for its Core i9-14900K chip.

As such, the listed models should top out with the 99DLMV part number, with 16 cores in an 8P + 8E arrangement, a meaty 3.5 GHz base block, and 30 MB of cache (presumably L3). This is the only model with a 125W TDP, and its base clock is higher than that of the Core i9-14900K, so it should be a speedy enough affair despite not having the high core counts of the halo models. Chances are it'll be a nice gaming CPU with pretty high turbo clocks, but only reviews will confirm that.

Interestingly, the 99DLMT has 20 cores (8P + 12E), but its much lower 65W TDP and 2.1 GHz base clock, which indicate that this model might be an efficiency-oriented productivity chip. In the table below, we added our guesses as to which models match existing chips.

There's no word about pricing, but we'd expect the new chips to ring in at roughly the prices of the existing models. As points of reference, the Core i7-14700 is currently $366, or $330 for the "F" variant without integrated graphics. At the lower end of the above table, the Core i5-14400 is sitting at $208, or only $161 without an IGP.

AMD's Zen 6 processors are out! Well, the EPYC 9006 family of server CPUs is out, anyway. These aren't chips that mere mortals like you and I can reasonably acquire, so there aren't really many third-party benchmarks out there yet, but somebody ran GeekBench 7 on one, and you know what that means: time for some wild speculation, such as the supposed 15% single-threaded IPC increase you might have seen reported this week. However, it isn't quite that clear yet. Well-known enthusiast and occasional leaker HXL (@9550pro) spotted the EPYC 9996 result, and now Russian enthusiast "three twenty six" (@326powah) has done a direct comparison with his Ryzen 7 9700X at the same clock.

Let's lay out the details: the AMD EPYC 9996 is an absolutely gargantuan server processor with 256 "Zen 6c" cores spread across eight "Monarch" CCDs with 32 cores apiece. Each CCD has 128MB of L3 cache, which is reportedly split into two 64MB domains for each 16-core CCX. This gives us 4 megabytes of L3 cache per CPU core, which happens to be the exact ratio that AMD has maintained since Zen 2. Meanwhile, 326's Ryzen 7 9700X is a desktop CPU with eight Zen 5 CPU cores and 32MB of L3 cache, giving it the same cache-per-core ratio yet an overall smaller local cache for the CPU cores, to say nothing of the 1GB of L3 cache on the full EPYC 9996.

Yes, 1GB of L3 cache. That enormous CPU is also served by a 1024-bit memory bus, likely running at 12,800 MT/s, giving it a colossal 1.64 TB/second of memory bandwidth. However, the specific benchmarks we're comparing here are single-threaded benchmarks, and as a result, they aren't likely to be bottlenecked by memory bandwidth on either machine; even 326's relatively pedestrian DDR5 memory at 6000 MT/s CL34 is more than sufficient for a single-threaded, lightly vectorized workload like Geekbench 7. Matching the CPU core clock rates at 4.1 GHz actually gives us a pretty decent core-to-core comparison of performance, even if all factors are not equal.

So how does it come out? Frankly, it's a massacre. That's true whether we look at the Windows 11 results he posted first or the CachyOS Linux results that he posted later, although the Zen 5 part doesn't get embarrassed quite as badly in Linux. The Dell PowerEdge R9815 server hosting the big EPYC part scored 2847 in the single-threaded test; 326's Ryzen desktop scores 2483 in Linux and 2318 in Windows.

Looking at the Gala-to-Honeycrisp Linux results, the biggest performance gulf is some 24% in the HTML5 Browser test, which is normally quite sensitive to memory latency. That could easily be caused by the massive L3 cache of the EPYC CPU. Other tests aren't so easily dismissed by configuration mismatches, though. The 19% gain in asset compression, the 21% gain in video encoding, and the 17% gain in photo editing all point to real architectural differences between Zen 5 and Zen 6 that seem quite promising for its desktop debut next year.

What's fascinating is that these results won't have been affected much by the considerable SIMD horsepower of the Zen 6 CPU core, as Geekbench—at least historically speaking—makes relatively light use of CPU SIMD, and in fact, this specific test is marked as "AVX2," meaning it definitely isn't using the muscular AVX-512 units present in either CPU. In fact, most of these tests are actually measuring CPU integer arithmetic and memory subsystem performance more than raw CPU number-crunching power, so Zen 6 coming out so far ahead here is really interesting.

Obviously, you shouldn't take this as gospel that "Zen 6 has 15% higher IPC than Zen 5," though that's arguably a plausible conclusion; there are just too many confounding factors to say that so far. Indeed, another one of those factors is that this isn't the Zen 6 CPU core that we'll be getting in desktop CPUs. The EPYC 9996 is a high-density part that uses Zen 6c, the specialized dense core design meant for increased area efficiency at the cost of its ability to scale to high clocks. After all, 4.1 GHz isn't exactly a high clock rate these days, and particularly not for chips manufactured on a bleeding-edge 2nm-class manufacturing process.

That's the part that should get you excited. Zen 5 had a very modest IPC uplift over Zen 4 (including even some regressions), and combined with a similarly modest clock rate gain, it wasn't a very exciting release for most desktop users. Zen 6 seemingly may have a significant IPC advantage as well as, if rumors hold, a fairly extreme clock jump over the current-generation parts. If that holds, this may be another leap like from Core 2 to Core i7, and these parts are confirmed to be coming to an AM5 socket near you. We'll be waiting with bated breath for the launch early next year. Hopefully there's RAM to buy by that point.

Having jettisoned 4F² memory cells from its roadmap, Micron must use different methods to continue scaling its DRAM devices in the coming years to keep up with rivals planning to use smaller DRAM transistors towards the end of the decade. Instead, Micron intends to introduce wafer bonding with its upcoming 1ε DRAM process technology and adopt High-NA EUV lithography for subsequent generations. Meanwhile, the company is developing new types of memory, including vertical high-bandwidth memory (vHBM) and vertical edge inference memory (vEIM), which will be integrated directly on top of processors.

"DRAM is nearing atomic limits at this point," said Scott DeBoer, president and chief technology and products officer at Micron, during the company's event this week. "Although we have confidence in several more planar nodes, we are very focused on making sure that we introduce 3D DRAM at the optimal time from a cost and performance point of view."

Wafer bonding, High-NA EUV, and new materials

Micron's current 1γ DRAM process is already in high-volume manufacturing, whereas its successor, 1δ, is scheduled to enter volume production in the second half of 2027. The latter promises a mid-20% increase in bit density and is optimized for future AI memory products, including HBM5, vHBM, and vEIM. Beyond 1δ, Micron plans to introduce wafer bonding with its 1ε process, which is currently under development. However, the company has not disclosed how it intends to implement wafer bonding or what improvements it expects from the technology.

For subsequent generations — ζÅ and ηÅ — Micron plans to adopt High-NA EUV lithography (ζÅ, zeta angstrom, Micron's 1^st Generation sub-10nm-class DRAM node) and new materials (ηÅ, eta angstrom, Micron's 2^nd Generation sub-10nm-class DRAM node) to continue shrinking DRAM cells. For many of its upcoming fabrication technologies that will be used over the next five to 10 years, Micron is also collaborating with Albany NanoTech. Of course, as with all organizations like Albany NanoTech, we are mostly talking about fundamental, or pre-competitive, IP that could be used for DRAM production at some point.

 "Albany NanoTech, our announced focus on advanced lithography [is] really driving High-NA EUV roadmap for DRAM," said DeBoer. "In particular at Albany with our team there, focused on the next five to ten years."

Micron is also developing 3D DRAM technologies and lists two generations — 3D1 and 3D2 — in its roadmap already. However, the company has not disclosed its architectures or launch schedules, as it intends to introduce 3D DRAM only when the technology offers sufficient advantages in manufacturing costs, complexity, and performance over conventional planar DRAM.

"When we look at three 3D DRAM we have that on the roadmap, as I mentioned, and it is shown here in between one zeta and one eta," said Micron's CTO. "But in reality, this is a parallel path, and we will implement it [3D DRAM] in a fashion that is ideal for cost, complexity, and device performance."

Going vertical, becoming critical

Beyond developing new process technologies for its upcoming DRAM products, Micron is also working on all-new types of DRAM products that are tailored for very specific use cases, including vertical HBM (vHBM), vertical edge inference memory (vEIM), and various custom HBM (cHBM) implementations.

vHBM will place memory stacks directly on top of processors (such as AI accelerators and AI GPUs) rather than next to them. This approach promises substantially lower latencies and higher bandwidth thanks to shorter connections. However, placing memory above a processor creates significant thermal challenges and limits the number of memory stacks that can be integrated on top of an ASIC. Therefore, Micron expects vHBM to complement conventional HBM, which will continue to provide the bulk of memory capacity in many AI accelerators.

Another technology under development is vertical edge inference memory (vEIM), which shares architectural and packaging characteristics with vHBM but targets different applications. Whereas vHBM prioritizes maximum bandwidth for high-performance AI accelerators, vEIM is focused on energy efficiency for edge AI processors used in autonomous vehicles, robotics, and other power-constrained devices. Nonetheless, even the 1^st Generation vEIM targets formidable 2 TB/s bandwidth at <1pJ/bit energy, which is in line with what HBM4 currently offers (at 8 GT/s over a 2,048-bit interface). Micron intends to optimize these products with customers according to their bandwidth, capacity, and power requirements.

Both vertical memory architectures will require advanced packaging technologies, particularly hybrid bonding, which enables much denser connections than conventional microbumps. Thermal management will also be critical, especially for vHBM. To meet cooling requirements, Micron is developing specialized heat-spreading structures to transfer heat from hot regions of memory base dies through the DRAM stacks.

The company has not disclosed when vHBM, vEIM, or cHBM will enter commercial production. What is important about the development of such types of memory is that it indicates that future improvements in memory performance will increasingly depend on advanced packaging and closer integration with processors, which will require collaboration between DRAM makers and logic developers. In turn, this transforms memory from a commodity to a critically important ingredient of an ASIC design.

Modders have discovered a way to remove imposed half-speed AI performance limits on Nvidia RTX 20, 30, and 40-series GPUs with a firmware exploit, VideoCardz reports. Without the limitation, the RTX 4090 can achieve double its peak tensor rate, and matrix math can improve by up to 80% for the RTX 3090 Ti, with gains on other cards varying. Real workloads gain significantly less than the RTX 4090’s doubled peak would imply, and chatbot token speeds remain about the same, as that performance is dependent on memory bandwidth.

For all impacted GeForce generations, Nvidia imposed a limit that, per its own published specs, runs FP32-accumulate math at half each card’s FP16-accumulate rate. That does not apply to its Turing and Ampere pro cards. The unlock returns native matrix-math throughput to owners of the cards, which can speed up prompt processing and image generation.

Three separate projects offer generation unlocks, each with its own unofficial Linux module, while experimental Windows builds pursue a different approach. Card coverage varies by generation, with gpu-unlock handling Ampere and listing the GA102/GA103/GA104/GA106 series IDs. An Ada fork, gpu-unlock-ada, covers the RTX 4090 and, experimentally, the 4090 D, 4070 Ti Super, and the 4060 Ti 16GB. The turing-unlock project, adapted from gpu-unlock, works with the RTX 2080 Ti. See Table 1 for a breakdown.

How much faster the cards get

The peak doubling is for tensor rates, with the Ada fork developer’s RTX 4090 moving from 165.6 to 331.6 TFLOPS on FP16 and 165.5 to 330.6 TFLOPS on BF16. The gpu-unlock-ada README states that, in one independent owner’s matrix-multiply benchmark, cuBLAS GEMM medians only saw improvements of 12–34% and up to 20%, respectively. A separate data point, for an RTX 4070 Ti on Windows, saw larger matrix-multiply gains of +80.1% and +76.4%, the difference possibly caused by power limits.

In the matrix-multiply benchmark, a tested RTX 3090 Ti scored +35% for FP16, +80% for BF16, and +94% for TF32, based on a user’s test with a modified Nvidia driver. The gpu-unlock README lists BF16 matrix-multiply gains from user reports of +25–67% for the RTX 3090, +70–73% for the 3080 10GB, +56–59% for a memory-modded 20GB version, +73–81% for the 3070, and around +80% for the 3060 12GB, though it notes they are not directly comparable. The power limit “matters a lot”: the lowest figure, +25%, came from cards capped at 225 W. For Ampere, LLM prefill improved 14–36%, with diffusion and FlashAttention speeding up, but LLM decode and INT8 stayed “about the same.”

An RTX 2080 Ti with a 22GB memory mod, a Dell OEM card limited to 250 W, saw FP16 matrix-multiply improvements of +36% to +64% depending on size; BF16 is unaffected, since Turing has no BF16 hardware. A user’s variant of the card at 260 W saw a +59% improvement. A separate project, KohakUnlock, on a Leadtek 2080 Ti 22GB saw an 85% improvement on an instruction rate test, with a best matrix-multiply median of +53% against a second, locked card of the same model.

There is “not a claim of a 2× application/game speedup,” says KohakUnlock’s README. See Table 2 for a rundown of the numbers for all three generations. The turing-unlock README notes that the mod “may damage your hardware,” while KohakUnlock adds that it “can hang a GPU or host, prevent boot, corrupt data, or damage hardware,” so caution is advised.

How the exploit works

The explainer for gpu-unlock states that the rate limits are in two “speed selector” registers that the host driver can’t write, but Nvidia’s signed SEC2 “Booter” firmware has a stack buffer overflow which can be exploited to run code in “heavy secure” mode. This was discovered after Nvidia published a debug Booter encrypted with a known public test key. A single 4-byte write with the V67 payload opens the privilege mask so the host can set the full rate, and the module then resets the card before Nvidia’s driver binds it.

The underlying bug is described in Jon Pry’s “A Canary in the Crypto Mine: Defeating Stack Protection in a GPU Secure Coprocessor,” published on Zenodo in June. The stack overflow was found on the CMP 170HX in the Heavy Secure Falcon, and the V67 constants come from WildFlash1st/cmp90hx-unlock. The pre-driver timing gpu-unlock uses appear to come from WildFlash1st’s separate Windows EFI bootloader, cmp90hx-unlock-for-windows, while the best-known use of the exploit is the CMP Unlocker for the CMP 170HX. Zagitta, the maintainer of gpu-unlock, said on Hacker News that the project is their work but “the exploits … aren’t my ideas by any means” and that the unlock “just flips the 2 bits” needed.

Zagitta said that RTX 40 support is in progress and that forks are already unlocking those cards. Zagitta added that Hopper and Blackwell cards are “out of scope for this approach” at least.

The Ada fork says other boards “remain unverified” and that shared firmware “does not establish support for untested cards.” The turing-unlock project, likewise, has a list of untested Turing IDs. Gaps remain for GA103 and most Ada and Turing cards. None of the projects contains a roadmap, but data is being gathered, as gpu-unlock is asking GPU owners for compatibility reports.

Nvidia CEO Jensen Huang has put the annual cost of licensing the company’s AI software at around $2,000 per GPU to 'run all the software that Nvidia provides that runs agents on these AI factories,' according to a recent video of the comments (below), a pricing model that could generate $50 billion over five years under a proposed scenario involving five million paid licenses outlined by FourWeekMBA.

Huang discussed the pricing at GTC Berlin on October 22, where the company outlined its broader push to build an AI infrastructure business spanning chips, software and AI-agent security. “Software licensing will become increasingly a major part of our company’s business. The way that we license will be…for example, it’s about $2,000 per GPU per year to run all the software that Nvidia provides that runs agents on these AI factories,” said Huang.

The numbers add up quickly. At $2,000 per GPU each year, Nvidia would bring in $10 billion annually if five million GPUs were covered by paid licenses. Over five years, that would amount to $50 billion, provided customers kept renewing their subscriptions. The catch, however, is that Nvidia has not disclosed how many GPUs could be covered by the proposed $2,000 fee, or whether that’s its standard price. It’s also unclear which software the license would cover, or if there is overlap between products.

The distinction matters because Nvidia already charges for enterprise software. Its AI Enterprise platform is listed at $4,500 per GPU for a one-year subscription. Huang’s reported $2,000 figure is lower, but Nvidia has not confirmed that the two prices cover the same products or licensing terms. It should not be treated as a confirmed price cut.

The licensing discussion comes as Nvidia develops more of the infrastructure needed to deploy and manage AI agents in enterprise environments. These systems can use tools, access data, and execute tasks, creating new security and management challenges for businesses running them at scale.

On October 21, Nvidia announced its OpenShell Reference Architecture, a system that combines its Vera Rubin computing infrastructure, Vera CPUs, and BlueField-4 data processing units (DPUs) running Nvidia Sentry. OpenShell provides a secure runtime for AI agents, establishing boundaries around their actions and access to tools and resources. Sentry monitors agent activity independently and can quarantine an agent that attempts to cross those boundaries, according to Nvidia. The architecture is designed to bring security controls into the underlying infrastructure rather than relying solely on safeguards built into an AI model or application.

Nvidia had previously introduced its Open Agent Safety Platform in September. The newer reference architecture builds on that effort, extending the approach to enterprise infrastructure and edge systems.

Other companies are also incorporating these controls into their products. Anthropic is integrating OpenShell and BlueField hardware with Claude Managed Agents to give businesses additional control over what their AI agents can access inside execution sandboxes. Salesforce has developed a Slack Admin Bridge for OpenShell that lets administrators review agent access requests, approve or reject permissions, and monitor activity directly in Slack.

The proposed software pricing fits Huang’s wider argument that Nvidia is becoming more than a supplier of GPUs. The company has expanded into networking, systems, enterprise software, and infrastructure designed to run AI workloads. Speaking on the BG2Pod podcast recently, Huang said, “One of these days, people might not categorize us as a chip company anymore.” He pointed to Nvidia’s presence across industries including healthcare, automotive, telecommunications and life sciences, where the company provides broader technology stacks rather than chips alone.

That said, Nvidia has not said when the $2,000-per-GPU fee would take effect or which software it would cover. It also remains unclear how the proposed pricing would fit into the company’s existing enterprise software business.

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.”

If you are wondering why the GeForce RTX 5090, despite being one of the best graphics cards, has evaporated from retail shelves, the answer lies in China’s industrial conversion factories. A newly surfaced video reveals the staggering scale of the country’s grey-market AI operations, showing industrial workshops dismantling brand-new GeForce RTX 5090 graphics cards to repurpose them for the AI boom.

So, what exactly is a GeForce RTX 5090 doing in China when the graphics card is not even officially available there? The answer is simple. They are there to be transformed into AI workhorses. The recently leaked footage offers a glimpse inside these Chinese workshops, where skilled technicians meticulously desolder the pricey flagship’s GB202 silicon and GDDR7 memory chips. They then transplant the components into a dual-slot blower design tailored for server use.

The GeForce RTX 5090 blower graphics cards will ultimately end up in high-density server racks where they will become the backbone of massive AI compute clusters. The scale and efficiency of these operations are impressive, with production lines converting shipments of brand-new GeForce RTX 5090 graphics cards, from Nvidia's custom partner models to the chipmaker's highly coveted Founders Edition. After testing and validation, workers would repackage these modified GeForce RTX 5090 graphics cards and ship them to clients, likely data centers or AI labs.

Many of these Chinese factories are scattered throughout the country. The conversion process is massive in scale, and probably thousands of GeForce RTX 5090 graphics cards are being repurposed every day. Middlemen in these grey-market supply chains are constantly hunting for GeForce RTX 5090 stock to fuel these operations.

Nvidia has reportedly halted production of the GeForce RTX 5090 and is, in all likelihood, redirecting the valuable silicon to higher-margin professional GPUs like the RTX Pro 6000 Blackwell. At the same time, a vast network of Chinese conversion factories continues to operate at full speed. Redirected supply and aggressive grey-market recycling have nearly wiped out GeForce RTX 5090 stock from U.S. retailers.

Custom GeForce RTX 5090 graphics cards now start at an eye-watering $8,500. However, a new workaround has emerged to sidestep the stock shortage and inflated prices: prebuilt gaming systems. Sometimes these GeForce RTX 5090 prebuilts cost less than a standalone GeForce RTX 5090, while offering a fully assembled system with a manufacturer's warranty.

If you had told me a few months ago that buying an entire gaming system would be cheaper than a single high-end graphics card, I would have called you insane. Yet here we are. In today’s chaotic market, prebuilt systems often offer better value than standalone graphics cards.

Micron's next-generation 3D NAND, which will enter mass production in 2H 2027, is set to offer three significant advantages: it will double storage density, increase I/O performance by 50% compared to the company's current-generation NAND memory, and decrease power consumption, the company revealed at an event this week. To achieve these aggressive goals, Micron plans to take a page from YMTC's book and adopt wafer-on-wafer bonding. Meanwhile, Micron is also developing new materials and denser memory cell architectures to extend 3D NAND scaling beyond G11.

"We had mentioned we will bring in wafer-on-wafer bonding technology at the right time when it’s cost-effective, and it brings in capability that is important for the product specs at the time, and this is the right timing for that technology," said Scott DeBoer, president and chief technology and products officer at Micron, during the company's event this week. "So this G11 technology is the world's most advanced NAND. It will ramp in the second half of next year, [and] it is based on wafer-on-wafer bonding technology."

G11: Over 400 layers and wafer bonding

Micron's G11 3D NAND represents a substantial advancement over its current G9 (N160) generation. The company expects the new memory to achieve approximately twice the bit density of G9 (3D TLC 21 Gb/mm² => 3D TLC 42 Gb/mm²?), which means a dramatic increase compared to Kioxia's BiCS10 or Samsung's V10; increase I/O speeds by up to 50% (3,600 MT/s => 5,400 MT/s?); and reduce data transfer energy consumption per bit by more than 25%.

These improvements should benefit both conventional high-capacity SSDs for client and data center applications and emerging AI-oriented storage devices, which require greater bandwidth and energy efficiency.

One of the key changes introduced with G11 is wafer-on-wafer bonding, which enables Micron to manufacture different parts of its NAND device on separate wafers using different process technologies — a new 3D NAND node to build a NAND array and a logic fabrication process to make peripheral circuits and I/O — and subsequently bond them together. The company has used CMOS-under-array architectures for several generations. Still, wafer bonding provides additional flexibility to optimize memory arrays and peripheral logic independently, which means more capacity and performance if all goes as planned.

Another important innovation is the transition to more than 400 NAND layers. Micron has not disclosed the exact number of active wordline layers or the number of memory decks used by G11, but the company says the technology will feature an industry-leading memory cell pitch, which suggests that its density improvements will come from both additional layers and smaller cell dimensions.

Micron expects to disclose more technical details about G11 in 2027, closer to the start of high-volume manufacturing in the second half of next year.

Beyond G11: New materials and denser memory cells

Without any doubt, Micron will continue scaling 3D NAND along all three dimensions rather than simply increasing the number of layers going forward. While conventional 3D NAND scaling initially relied primarily on adding more memory layers, future generations will also require reductions in cell dimensions along the X and Y axes to improve bit density while keeping manufacturing complexity in check.

To achieve this, Micron is developing what it describes as breakthrough high-mobility materials, ultra-dense cell architectures, and more energy-efficient devices and data paths. These technologies could improve transistor characteristics, enable further reductions in memory cell dimensions, and reduce the energy required to move data within NAND devices.

"Beyond G11, we have a strong roadmap, not going to go into great detail on it today, but really focused on new materials densifying the cell architecture, and continuing to focus on that XYZ scaling going forward," said DeBoer. "[…] The current industry direction and Micron’s direction is scaling both by adding layers [and] also by shrinking the cell dimensions."

The company has not disclosed specific architectural details, density targets, or production schedules for its post-G11 generations, though its roadmap suggests that future NAND scaling will increasingly depend on innovations in materials, cell architecture, and peripheral circuitry rather than layer-count increases alone. Meanwhile, since the number of active layers is arguably the easiest way to increase storage density, we would not expect the race towards the highest layer count to slow down substantially in the coming years, especially given strong demand for 3D NAND-based storage.

SK hynix early on Friday announced that it had decided to abandon plans for a potential initial public offering (IPO) of Solidigm, its U.S.-based enterprise SSD subsidiary, citing unfavorable stock market conditions and semiconductor share price trends. At the same time, SK hynix confirmed it plans to build a new fab for Solidigm in the U.S. to address growing demand for enterprise SSDs. Although an IPO could have helped finance a new fab in the U.S., SK hynix claims that its subsidiary’s expansion remains a priority.

Solidigm specializes in high-capacity data center SSDs based on floating gate 3D QLC NAND memory. As AI infrastructure deployments accelerate, demand for high-capacity storage increases, whereas Solidigm's existing manufacturing capacity is barely sufficient to address its projected needs. Consequently, SK hynix believes that Solidigm requires additional production facilities in the U.S., although it has yet to disclose the planned fab's capacity, investment requirements, or construction schedule. Such a facility could also strengthen SK hynix's American manufacturing footprint, which is important, given the current environment and on-shoring trends.

SK hynix had considered multiple options — including direct investment, a pre-IPO funding round, and IPO of Solidigm — to finance capacity expansion. An IPO would have enabled SK hynix to raise capital from outside investors without taking on more debt. Furthermore, it could have revealed the true value of the subsidiary, which SK hynix believes is not properly reflected in its own market capitalization. In addition to financing the expansion, the proceeds could have been used for dividends, share repurchases, and share cancellations.

However, SK hynix says that increased market volatility and the ongoing correction in semiconductor stocks have made an IPO less attractive. As a result, the company believes that current market conditions would prevent Solidigm from achieving a valuation that adequately reflects its growth prospects. Consequently, it has discontinued its review of both pre-IPO financing and an IPO, even though it will continue to evaluate alternative funding mechanisms.

The cancellation of the IPO raises an obvious question: why would SK hynix abandon a financing mechanism that could provide billions of dollars for Solidigm's expansion just as demand for enterprise SSDs is at a record high and set to increase further over the next couple of years? After all, constructing a modern 3D NAND fab requires tens of billions of dollars, and external financing could reduce the burden on SK hynix's balance sheet and preserve capital for other projects (e.g., new capacity elsewhere).

One possible explanation is Solidigm's exceptionally strong profitability. Micron's enterprise storage division recently reported a non-GAAP gross margin of 90%, and given Solidigm's unique position in the market (it controls 21.1% of the enterprise SSD market together with its parent company), its margins may well be higher as it sells exclusive products. If extraordinary margins are sustainable over the next two or three years, its operations could substantially boost SK hynix’s consolidated profitability and generate considerable cash for future investments. Given these circumstances, SK hynix could potentially finance Solidigm's U.S. manufacturing expansion through a combination of internally generated cash and debt even without diluting its ownership. Financing the entire project with cash alone may also be possible, even though such an approach would be less likely given the massive capital requirements of advanced semiconductor production facilities nowadays. In any case, it is natural for SK hynix to prefer retaining full ownership of a highly profitable subsidiary to selling part of it at a valuation it considers inadequate.

The latest board to land on our test bench is a small-form-factor Intel option, the Gigabyte Z890M Aorus Elite Wifi7 Ice. This Micro ATX motherboard costs only $209 on Amazon and packs most of the ATX version's features into a smaller package. The board is optimized for Intel’s Core Ultra 200S Plus processors and pairs best with Micro ATX chassis, but its best feature is its looks. It’s one of the better-looking Micro ATX options, especially if you’re looking for a white-themed build.

The Z890M Aorus Elite offers three M.2 sockets (2x PCIe 5.0) and four SATA ports for storage, 2.5 GbE and Wi-Fi 7 (160 Hz) for networking, and a basic audio solution. The rear IO delivers nine USB ports total, including one 40 Gbps Type-C port (with DisplayPort capability). All of that is typical fare for the form factor. You also get two full-length PCIe slots (one reinforced) and heatsinks covering all M.2 sockets, giving the board a more premium look than its direct competition. It also adds two RGB lighting zones, one by the VRMs on the left and the other under the chipset heatsink, adding glow to your chassis.

Overall, performance in our testing was average, with the board doing well in some tests and slightly below average in others. For gamers, it performed well in our 3DMark tests and in real games. In short, there’s nothing to worry about from a performance standpoint. The Z890M Aorus Elite also supports AI features, including AI Perfdrive, which offers customizable BIOS performance presets for one-click CPU improvements.

Below, we’ll examine the board's performance and other features to determine whether it deserves a spot on our list of the best motherboards. But before we share test results and discuss details, here are the specifications from Gigabyte.

Specifications of the Gigabyte Z890M Aorus Elite Wifi7 Ice

Inside the Box

The box includes the usual accessories. You get two SATA cables (white), a rubber pad, an extra thermal pad for M.2, an EZ connector for the front panel, and an installation guide. The collection here is sparse, but typical for the price point.

Design and Features of the Aorus Elite WiFi7 Ice

For what tends to be a budget motherboard class (and typically, well, ugly), the Aorus Elite WiFi 7 Ice is an attractive Micro ATX SKU. Where its peers don’t offer complete heatsink coverage on the bottom half, this one does. It also uses a large heatsink for the primary M.2 socket, unlike its peers. It also has integrated RGB lighting (under the VRM and chipset heatsinks) for an extra bit of flair. All in all, it’s one of the better-looking Micro ATX motherboards around.

Zooming in on the top half, starting on the left, we get a better look at the Aorus eagle design, along with the RGB feature. The VRM heatsink below has a lot of mass and surface area, so it does a good job keeping the MOSFETs below running in spec. Above that are the two “UD” (solid pin) 8-pin power connectors (one required) for the processor.

Past the CPU socket, the next thing we run into is the four DRAM slots with the locking mechanism at the top (where there’s room). Gigabyte lists support for up to DDR5-9200(OC), which is plenty fast for the platform. Surprisingly, our fastest kit (DDR5-8800) didn’t play nice with this board, but the DDR5-8200 kit worked fine. As always, for best results, stick to the memory QVL.

Next to the RAM slots on the left are the first two (of six) 4-pin fan headers. Each header supports PWM and DC-controlled devices. Each header supports up to 2A/24W output, which is plenty, especially for a smaller chassis with fewer fans. Gigabyte Control Center (GCC) and the BIOS control the fans via the Smart Fan 6 applet.

Above the DRAM slots is the Q-LED feature. Four LEDs, CPU/Boot/VGA/RAM, light up during POST. If a failure occurs during that time, the offending RGB stays lit, giving you a general idea of where the problem may be. Next to it, in the upper-right corner, are three simple buttons: power, reset, and Q-Flash.

Down the right edge, you'll find the first (of three) 3-pin ARGB headers. The other two are along the bottom edge. GCC and the RGB Fusion app inside control these headers and the integrated lighting, offering users plenty of canned LED effects and customization. Below that are the 24-pin ATX connector to power the board, another 4-pin fan header, the front-panel USB 3.2 Gen 2 (10 Gbps) connector, and a 19-pin front-panel USB 3.2 Gen1 (5 Gbps) header. Between those is a front-panel HDMI output, making it easy to add secondary displays for monitoring or further chassis customization.

Power delivery on the Z890M Aorus Elite WiFi7 Ice is capable, but it doesn’t quite reach the level of "robust." The board has 15 phases, 12 of which are dedicated to Vcore. Power comes from the dual 8-pin EPS connectors and is controlled by the OnSemiconductor NCP81537 8-phase controller (teamed configuration). From there, power moves on to the OnSemi NCP302155 60A DrMOS MOSFETs and then to your processor. The 720A available isn’t a lot, but it can handle the Core Ultra 7 270K Plus, the Core Ultra 5 250K Plus, and even the Core Ultra 9 285K — though I’m not sure how hard I’d push it overclocking the 285K or 270K Plus. Just be sure to keep air flowing through your chassis, as these components will get warm under sustained heavy use.

On the bottom half of the board, starting on the left edge, we spy the audio solution. The Z890M uses the budget Realtek ALC897 codec, plus a few dedicated audio capacitors (yellow and black). While one of its direct competitors has a better one, this codec is fine for most users, and there's no reason to avoid it unless you're making music with the board or consider yourself a PC-focused audiophile.

In the middle of the board are two full-length PCIe slots. The primary slot, using Gigabyte’s PCIe UD Slot X reinforcement) connects through the CPU and runs at PCIe 5.0 x16 speeds (no bifurcation, FYI). The second slot at the bottom sources its bandwidth through the chipset and runs up to PCIe 4.0 x4. There’s plenty of bandwidth for expansion; just make sure your graphics card doesn’t cover the second slot if you need to use it.

Between and above the PCIe slots are three M.2 sockets. The top socket, under the beefy EZ-Latch heatsink (made good contact, note), connects through the CPU and is the main PCIe 5.0 x4 (128 Gbps) M.2 socket. Under the plate-style heatsink (also using EZ-Latch along with EZ-Click to secure the M.2 without screws) are two more M.2 sockets. Both sockets connect via the chipset, support 80mm devices, and run up to PCIe 4.0 x4 speeds. The bottom socket supports up to 110mm modules, while the middle socket supports the more familiar 80mm. If you need the additional speed or redundancy RAID offers, the board supports RAID0/1/5/10 modes for NVMe SSDs.

We've also captured several images of the ICs that make this motherboard work, including Realtek Ethernet and audio, ASMedia (for the front HDMI), and OnSemiconductor MOSFETs/PWM controller.

Moving right, past the chipset heatsink and the other RGB lighting element, we spot a couple of Thunderbolt headers and four SATA ports (supporting RAID0/1/5/10 modes). At the bottom of the board is a slew of headers, offering the typical connectivity in this area, with nothing worth calling out.

Below, we’ve listed all the connections across the bottom of the board.

• Front panel audio
• (2) 4-pin RGB header
• 3-pin ARGB header
• (2) USB 2.0 (480 Mbps) headers
• (2) 4-pin system fan headers
• SPI TPM header
• 2-pin reset jumper
• 2-pin Clear CMOS jumper
• Front panel header

The rear IO area is pretty sparse compared to high-end boards, but it uses some venting to help keep the VRMs running cooler. On the left (in white) are four USB 2.0 ports, followed by four USB 3.2 Gen 1 (5 Gbps) ports in blue. Below those is the DisplayPort (v2.1) output. Next to the blue USB ports is your sole Type-C port. In this case, it's USB4 (not Thunderbolt 4) at 40 Gbps and supports DisplayPort output as well. To the right, you'll find the 2.5 GbE port and, below that in red, the only USB 3.2 Gen 2 (10 Gbps) Type-A port. Finally, on the right, are the quick-connect Wi-Fi 7 (160 Hz) connectors and audio stack: dual 3.5mm jacks for mic and line-out, plus an SPDIF optical output.

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Firmware

Gigabyte’s updated “UC BIOS 2.0” defaults to Easy Mode. It’s logically laid out and displays a wealth of system information, including processor, RAM, fan speeds, and several selectable options such as XMP profiles, RAM tweaks, Re-Size BAR support, Smart Fan 6 access, and more. The Aorus Elite WiFi7 Ice uses a white background with the ‘Aorus orange’ accents and black text, creating a high-contrast, easy-to-read screen similar to the Aorus Infinity, but with a white background instead of Aorus branding. The BIOS also offers different themes in EZ mode via a dropdown if you want to change it.

All headings still appear across the top in advanced mode, but they are now larger ‘buttons’ and easy to select with a mouse. The highlight bar (where you are on the page) is a light blue here and easy to see. Every option you need and want is at your fingertips, and you don’t have to drill down several layers to reach the most commonly used functions – especially if you populate your selections in the Favorites section.

Software

Gigabyte Control Center (GCC) is a one-stop solution for controlling various functions, including RGB and Fan control, hardware monitoring, and overclocking. It also helps you find, download, and install driver updates for your system. It’s a simple application that does its job. It’s also a much cleaner tool than the previous App Center. It earns our approval for the breadth of functionality it offers users. There’s also the curiously named AI Snatch to help with overclocking.

Test System / Comparison Products

We’ve updated our test system to Windows 11 (25H2) 64-bit OS with all updates applied as of late April 2026. On the hardware front, we’ve updated the RAM kits to ones appropriate for the platform. Peripherals, including cooling, storage, power supply, and graphics cards, remain unchanged. We also use the latest publicly available BIOS unless otherwise noted. The hardware we used is as follows:

TEST SYSTEM COMPONENTS:

• CPU - Intel Core Ultra 7 270K Plus
• Cooling - Arctic Liquid Freezer II 420
• Storage - Crucial 2TB T705 M.2 PCIe 5.0 NVMe SSD
• RAM - Kingston Fury Renegade - 32GB DDR5-7600 CL38 (KF576C38RWAK2-32)
• RAM - G.Skill Trident Z5 CK - 32GB DDR5-8200 CL40 (F5-8200C4052G24GX2-TZZ5CK)
• RAM - V-Color 256GB (2x128GB) DDR5-8000 CL64 (TECQ5128G80Q864K)
• GPU - Asus TUF RTX 4080 16G
• PSU - EVGA Supernova 850W P6
• Windows 11 64-bit (25H2 - 26200.8037)
• NVIDIA Driver 595.97

Benchmark Settings

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Benchmark Results

Our standard benchmarks and power tests are performed using the CPU’s stock frequencies (including any default boost/turbo) with all power-saving features at default. We set optimized defaults in the BIOS, then enable the XMP profile to set the memory. If the BIOS enables boosts by default, it runs like that. We set the Windows power scheme to Balanced (default) for this baseline testing, so the PC idles appropriately.

Synthetic Benchmarks and Real World Applications

Synthetics offer a valuable way to evaluate a board's performance, since identical settings should yield similar results. Turbo boost wattage and advanced memory timings are areas where motherboard manufacturers can still optimize for stability or performance, though, and these settings can impact specific testing scenarios. We’ve also combined our previous ‘timed’ benchmark applications into this section..

Performance on the Aorus Elite was around the average among the tested boards. Some benchmarks were above average, while others were slightly below—nothing to worry about so far.

3D Games and 3DMark

Starting with the launch of the Arrow Lake refresh chips, we’ve updated our game tests. We’re keeping the F1 racing game but have upgraded to F1 25. We’ll also continue with the ever-popular, aesthetically pleasing Cyberpunk 2077. We run both games at 1920x1080 resolution using the Ultra preset (details listed in the table above). Both games are set to use DLSS.

The goal of these settings is to determine whether performance differs at the most commonly used (and CPU/system-bound) resolution, with settings most people use or strive for (Ultra). We expect the difference between boards in these tests to be minor, with most falling within the margin of error. We’ve also added a minimum FPS metric, which can affect your gameplay and immersion.

As we’ve seen for a while now, the 3DMark tests don’t show much separation from worst to first, and we see that again across our varied datasets. 3DMark scores were fine; in fact, they were the highest so far in these tight results, while gaming results were average overall. Not only does it do work, but as expected, the board also plays games just fine.

Overclocking

Over the past few CPU generations, overclocking headroom has been shrinking on both sides of the fence, while out-of-the-box performance has increased. For overclockers, that means less fun. For the average consumer, you’re getting the most out of the processor without manual tweaking. Today’s motherboards are more robust than ever, and most support power-hungry flagship-class processors, so we know the hardware can handle them.

You can extract even more performance from these processors by manually adjusting settings or using the fancy AI overclocking that board partners have been touting. Results will vary and depend on the CPU's cooling and quality. In other words, your mileage may vary. With that in mind, we’re not overclocking the CPU for these review articles. However, we'll test our different memory kits to ensure they meet the specifications.

Memory testing went OK, with the board surviving a 30-minute stress test using the DDR5-7600 and DDR5-8200 kits without issue. That said, it struggled with the DDR5-8800 kit and failed after about 5 minutes. If you really want to push memory speeds, stick to the QVL list for your best chance of reaching higher speeds.

Power Consumption / VRM Temperatures

We used AIDA64’s System Stability Test with Stress CPU, FPU, cache, and Memory enabled for power testing, using the processor's peak power consumption value. We measured wall wattage with a Kill-A-Watt meter, which captures the entire PC (excluding the monitor). The only variable that changes is the motherboard; all other parts remain the same. We now use only the stock power-use/VRM temperature charts, as this section aims to ensure the power delivery can handle flagship-class processors.

Stress testing with our flagship-class 270K Plus and the Team Group DDR5-7600 kit at stock yielded a peak of only 330W at the wall, tying our lowest result so far. The board also sipped power at idle, dropping to around 56W, the lowest result we’ve recorded for the platform. This board sips power compared to some others.

VRM temperatures ran warm, but are not a concern. Throughout the 30-minute test, the system (excluding the monitor) averaged 232W, and our sensors on the back of the board, directly under the MOSFETs, recorded temperatures peaking at just under 60 degrees Celsius, while HWInfo and the internal sensor showed similar peaks at about 60 degrees Celsius. That value is well within specification for the MOSFETs doing all the work below. We’re confident that the power delivery can handle whatever you're likely to throw at it. Chances are, the CPU temperature will limit you before the board does, but keep airflow good to keep temperatures down.

Bottom Line

Gigabyte’s Z890M Aorus Elite WiFi7 Ice is a solid all-around motherboard for the Micro ATX form factor and smaller builds. Its icy-white aesthetic and ‘full coverage’ of heatsinks are rare for this class of board and give it a premium vibe compared to its peers. Hardware-wise, it includes most of what you’d expect from the Z890 platform, though I’d like to see another USB4 port on the rear IO, and perhaps a better audio codec. Still, this is one of the better-looking and better-equipped of the Z890M Micro ATX options.

As for the competition, the Asus Prime Z890M-Plus ($216.99) has more expansion slots (4), additional “AI” features, and SATA ports (6), but fewer rear USB ports, and it just doesn’t give off the same premium vibes as the Gigabyte Z890M. ASRock’s Z890M Riptide Wifi ($252) costs quite a bit more than the others and offers more robust power delivery (like the Asus) and decent looks, but its specs are otherwise similar. Aesthetically, the ASRock is also less pleasing than the Gigabyte, and it has only one PCIe slot (so no room for expansion if needed). MSI has the Pro B860M-A WiFi ($158), which uses a lesser mainstream chipset, offers 5 GbE (and slower 6E Wi-Fi), and is otherwise comparable to the Asus with its extra PCIe slots. Oh, and it doesn't look great.

Overall, the Z890M Aorus Elite WiFi7 Ice is one of the better-looking Micro ATX offerings and nicely priced, earning a spot on our best motherboards list (for Intel Micro ATX). The icy-white aesthetic and minimal PCB visibility will turn heads in a white case. Hardware-wise, it has the specs you expect for this class of board. If you’re in the market for a Micro ATX Intel board, the Z890M Aorus Elite Wi-Fi 7 Ice should be your first stop, especially if you want to show off your paired white components.

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Following reports over the weekend that an Nvidia RTX 5090 shipment worth $470,000 was stolen from a Brazilian airport, a contraband graphics card linked to the shipment has shown up for sale online. Brazilian media also reports that the police and airport authorities have identified three employees thought to have been involved in the heist, according to GMC. (Machine translated)

According to the report, Guarulhos International Airport has issued a statement confirming that "The investigation of the facts is the responsibility of the competent authorities to clarify the circumstances of what happened." A Brazilian TV news network appears to have identified one of the cards, a Zotac Gaming RTX 5090 for sale on the online marketplace OLX for over $6,000. Quite unfortunately, the reseller uploaded clear pictures of the card's serial number, linking it to the missing haul of graphics cards. Per the report, there is no information to identify the seller, and the listing appears to have since been taken down.

However, police information reported by the outlet does reveal a chain of events and some possible suspects in the case. The shipment, imported from the United States and thought to be worth nearly $500,000, arrived in Brazil on September 20 and was registered with customs on September 24. The two pallets went missing after being authorized for release on September 25. Police believe "two outsourced forklift operators" removed the pallets from the warehouse on September 21, an act apparently recorded by CCTV.

Police state the equipment was loaded onto a truck and hasn't been seen since. A third "checker" employee is said to have released the merchandise from the system to pass through electronic controls.

The RTX 5090 is the world's best consumer gaming GPU, but high demand for AI compute has seen it all but disappear from conventional retail, with the card now fetching upwards of $10,000 in the few remaining marketplaces it can be found, nearly always offered by third-party sellers. As such, an idle, unguarded shipment of such cards would make ripe pickings for thieves, a tempt

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.

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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.

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DRAM featuring 4F² memory cells has long been considered one of the holy grails of the DRAM industry, as they promise to reduce cell area by 33% compared with conventional 6F² designs and therefore enable building DRAMs with more memory cells in the same area. However, after working on 4F² memory cells for a couple of decades, Micron has concluded that the architecture offers no meaningful density advantages, increases manufacturing complexity and costs, and has fundamental scaling limitations. This has a dramatic impact on Micron's future plans.

"Micron invented 4F² DRAM," said Scott DeBoer, president and chief technology and products officer at Micron, during the company's event on Wednesday. "The path with 4F² DRAM is always been an option through time, and we have evaluated it and not pursued it due to increased complexity and cost through this past two-decade period of time."

Interestingly, both Samsung and SK hynix still have 4F² memory cells in their roadmaps (according to TechInsights), so Micron's rejection of the technology puts the company on a unique trajectory. Several years ago, the company delayed integration of EUV lithography into its manufacturing flow, contrary to what its rivals did, and still managed to retain competitive positions both in terms of costs and in terms of performance. Therefore, skipping 4F² memory cells is not completely surprising.

4F² is not the future of Micron's DRAM

The main attraction of 4F² DRAM is its theoretically smaller memory cell. The 4F² naming refers to a cell area equivalent to four times the square of the minimum lithographic feature size (F), compared with six times F² for conventional DRAM.

At identical feature dimensions, a 4F² cell occupies approximately 33% less area than a 6F² cell, which could theoretically increase the number of memory cells per wafer by 50%. Such an improvement would reduce manufacturing costs per bit and increase per-device memory capacity even without an equivalent reduction in feature dimensions. However, to make these advantages possible, DRAM makers must develop a suitable transistor architecture and a sufficiently compact capacitor arrangement. This is not easy at all.

The CTO of Micron says that the theoretical advantages of 4F² DRAM do not necessarily translate into higher memory density in practice. DeBoer explained that dimensions and pitch of DRAM capacitors, rather than the nominal area of DRAM transistors, ultimately determine how many memory cells can fit on a wafer. Both 4F² and 6F² transistor structures must fit beneath the capacitors, which means that reducing transistor area alone does not guarantee a corresponding reduction in overall cell size because transistors need a capacitor. Furthermore, Micron believes that 4F² introduces additional manufacturing steps and complexity that increase costs without delivering sufficient benefits.

"It is important to understand the capacitor pitch, the capacitor size, and dimensions, is what sets the DRAM bit density, not whether it is 6F², 4F², 8F²," DeBoer said. "From our investigation of this technology over the past couple of decades, it is a bit of a myth that 4F² actually provides anything versus 6F². It is capacitor pitch that defines the DRAM. You can build the cells, the transistors underlying them in different ways, but they still have to fit under the capacitor pitch, which sets the DRAM [cell size]. So, some of that is just smoke and mirrors in terms of talking about 6F² versus 4F²."

4F² memory cells may curb new process technologies

Instead of adopting the 4F² DRAM cell architecture, Micron plans to continue scaling conventional 6F² DRAM. The company believes it can increase bit density by reducing capacitor pitch and shrinking process technologies even without introducing a fundamentally different transistor architecture.

Advanced lithography, new materials, and wafer bonding should allow Micron to extend planar DRAM scaling for several more generations, according to the company. For example, its upcoming 1δ process technology, scheduled to enter volume production in the second half of 2027, promises a mid-20% improvement in bit density compared with its predecessor. Micron also plans to adopt High-NA EUV lithography for future DRAM generations.

Interestingly, DeBoer fully acknowledges that 4F² DRAM is technically feasible and that Micron itself has manufactured experimental devices based on the architecture. However, its manufacturing complexity and costs become increasingly problematic as feature dimensions shrink, so essentially Micron claims that it can either adopt 4F² or use more sophisticated process technologies, a claim that perhaps implies why China-based CXMT recently praised 4F². Although DeBoer did not identify any specific physical limitations involved, he stated that 4F² has no sustainable scaling path beyond a certain point. This suggests that Micron sees little value in introducing an intermediate architecture that would eventually require another major transition.

"When you look at a scaling path, you can go back a few nodes and absolutely, 4F² can be built back a few nodes, no question about it," DeBoer noted. "It is more complicated, it is more complex, it is more costly, but you can do that. When we look at scaling 4F² beyond where we are sitting today, there it is; it is physics. There are fundamental problems with 4F² scaling that ultimately will lead to 3D DRAM coming in instead of 4F²."

3D DRAM is the future

Indeed, Micron's preferred long-term solution is 3D DRAM, which would increase memory density by stacking memory cells vertically rather than relying exclusively on reductions in their lateral dimensions. Alongside development of multiple next-generation planar DRAM process technologies, the company is already developing multiple generations of 3D DRAM production nodes (which is not surprising, as 3D NAND nodes will rely on fundamental innovations developed for planar processes), although it has not disclosed when the new architecture will enter commercial production. DeBoer indicated that Micron will make the transition when 3D DRAM offers the right combination of density, manufacturing complexity, and cost.

Although both Samsung and SK hynix have 4F² DRAM products in their roadmaps, Micron believes that the assumption that reducing the nominal footprint of DRAM cells improves manufacturing economics is wrong and that extending 6F² scaling and eventually adopting 3D DRAM offers a better long-term strategy.

In a world where SSDs with up to 256TB capacity are about to enter the scene to compete against hard disk drives that store over 40TB, magnetic tape storage may seem archaic. However, the 25-year-old Linear Tape-Open (LTO) format continues to evolve at a rather impressive pace.

The current LTO-10 generation stores up to 40TB of uncompressed data per cartridge, while HPE, IBM, and Quantum — the companies behind the LTO Program — now envision LTO-14 cartridges with up to 365TB of native capacity. But capacity is not the only advantage of LTO. In fact, the consortium has deliberately slowed its capacity roadmap in a bid to prioritize reliability, cost per terabyte, and manageable backup and recovery times over the previous goal of doubling capacity with every generation.

LTO began in 2000 with the LTO-1 format, which stored just 100GB of data natively and transferred it at 20 MB/s. Since then, capacity increased to 200GB with LTO-2, 400GB with LTO-3, 800GB with LTO-4, 1.5TB with LTO-5, 2.5TB with LTO-6, 6TB with LTO-7, 12TB with LTO-8, and 18TB with LTO-9.

The original LTO-10 media introduced in 2025 increased native capacity to 30TB, whereas an extended-length LTO-10 cartridge announced later increased it further to 40TB.

LTO cartridge capacity has increased by a factor of 400 in about 25 years without changing the form-factor itself. For comparison, the capacity of 3.5-inch hard drives increased by roughly 585 times over the same period, from around 75GB in 2000 to as much as 44 TB today, so tape has evolved at a slower pace. However, LTO has evolved without dramatic changes in internal complexity.

Two scaling vectors

The 40TB LTO-10 cartridge is noteworthy because its additional capacity is enabled by higher recording density and literally longer tape. The LTO-10 format uses 15,104 data tracks (enabled by the new barium ferrite recording layer), up 68.5% from 8,960 tracks with LTO-9, and combines them with higher linear density. To make this possible, LTO-10 uses a redesigned high-bandwidth servo system with a low-mass mechanism that enables the head to follow increasingly narrow tracks accurately, including in environments subject to shock and vibration.

Both 30TB and 40TB LTO-10 media use a strontium-doped barium ferrite (BaFe) recording layer, but the 40TB version uses a new Aramid base film that is thinner and smoother and therefore enables manufacturers to put more tape into the same cartridge. According to MagStor, the thinner substrate increases tape length from approximately 1,035 meters with the 30TB cartridge to around 1,335 meters with the 40TB version. Meanwhile, the 40TB cartridge works with the same LTO-10 drives as the existing 30TB media.

Therefore, modern LTO has at least two major scaling vectors: manufacturers can record more bits on a given area of tape, and can put more tape into a cartridge. Meanwhile, with LTO-10, the consortium had to drop backwards compatibility, which we will detail further within this article.

There appears to be plenty of room left on the tape front. Back in 2020, IBM and Fujifilm demonstrated a strontium ferrite tape technology with an areal density of 317 Gb/in², which they said could theoretically enable a cartridge capable of storing 580TB. The prototype used tracks only 56.2nm wide and a 29nm TMR read sensor, which proved that magnetic tape could reach capacities vastly beyond commercially available LTO products.

Capacity is not everything

Ironically, despite considerable technological headroom, the LTO Program has recently made its roadmap considerably less aggressive.

When HPE, IBM, and Quantum extended the roadmap through LTO-14 in 2022, they expected capacity to roughly double every generation. The plan envisioned 72TB for LTO-11, 144TB for LTO-12, 288TB for LTO-13, and a whopping 576TB native — or 1.44PB compressed — for LTO-14. But that changed in November 2025, when the three companies introduced the new roadmap for LTO that significantly slows down capacity scaling. The current roadmap targets 70TB native for LTO-11, 120TB for LTO-12, 210TB for LTO-13, and 365TB for LTO-14.

While the new roadmap is somewhat less impressive, it does not necessarily indicate that tape technology has encountered a physical scaling wall. The developers claim the revised targets are intended to prioritize reliability, affordability, efficiency, and cost per terabyte. The consortium also specifically says that lowering maximum cartridge capacities should help reduce the amount of time required to store and recover data, which is a legitimate argument even though it looks like an attempt to make a 'feature' out of a limitation.

"AI has turned archives into strategic assets," said Stephen Bacon, Vice President, Data Protection Solutions Product Management, HPE. "The new 40 TB LTO-10 cartridge will help enterprise-class organizations — across healthcare, financial services, media, research, manufacturing, the public sector and beyond — consolidate petabytes efficiently, strengthen cyber resiliency with true offline air-gapping, and keep long-term retention affordable and sustainable."

Bandwidth is becoming one of tape's more obvious limitations. LTO-8 offered 360 MB/s of native bandwidth, LTO-9 increased this to 400 MB/s, and LTO-10 remains at 400 MB/s, although hardware compression can boost effective throughput to as much as 1,200 MB/s when data can achieve the assumed 2.5:1 compression ratio.

As a result, while maximum native cartridge capacity increased from 12TB with LTO-8 to 40TB with LTO-10 — a 3.33X increase — native transfer performance improved by only around 11%. At 400 MB/s, writing 40TB sequentially would theoretically take around 28 hours (without the overheads). Future LTO generations will likely increase performance, but the consortium has not yet published transfer rate targets for LTO-11 and its successors.

No backwards compatibility

One thing to note about LTO-10 is that it has broken a long-standing LTO tradition, which is backward compatibility. Up until LTO-7, new drives could generally read cartridges from two generations earlier and write media from one generation earlier. LTO-8 and LTO-9 reduced compatibility to one previous generation. However, because LTO-10 redesigns its head, its backwards compatibility disappears completely: an LTO-10 drive reads and writes only LTO-10 media, although the 30TB and 40TB cartridges are of course interchangeable.

This creates a natural problem for operators that need to maintain archives for decades. Once they adopt LTO-10, they either must migrate all their archives to the new format from LTO-8 or LTO-9 cartridges, or keep the old drives in their fleet, which may be increasingly difficult.

Demand remains strong

Perhaps counterintuitively, the AI boom could strengthen demand for tape. AI infrastructure produces enormous datasets, but not every training dataset, checkpoint, model, log, or generated asset needs to remain indefinitely on expensive SSDs or HDDs.

LTO capacity shipments reached 160.3 exabytes in 2025, down 9% year-over-year. However, shipments in the first quarter of 2026 jumped 57% YoY, according to figures reported by the LTO consortium. The organization attributed the increase to AI-related data growth, traditional archival demand, cyber-resilient backups, continued LTO-9 adoption, and the beginning of the LTO-10 transition.

"We are seeing unprecedented data growth combined with increasing cost, energy, and cyber resilience pressures across the industry," said Hugues Meyrath, CEO, Quantum. "As organizations adapt to this new reality, tape is increasingly viewed as a strategic component of modern data infrastructure, delivering predictable economics and resilient long-term data retention at scale."

Indeed, tape has a number of fundamental advantages that are not going to disappear any time soon. Tape provides vast capacities at a low cost per terabyte, cartridges consume virtually no power while sitting offline, hardware encryption protects data, and physically removing a cartridge from a drive provides a genuine air gap against network-based attacks. LTO also supports the LTFS file system, which maintains indexing information on tape and makes archived files considerably easier to manage.

Meanwhile, tape's disadvantages are equally fundamental and are not going away: tape is sequential and therefore cannot provide anything resembling the random-access performance of HDDs or SSDs. Although nobody expects something similar from it.

LTO isn't going anywhere

25 years after LTO-1 offered 100GB per cartridge, LTO-10 can store as much as 40TB, and the roadmap calls for 365TB with LTO-14 several years down the road. Perhaps more importantly, laboratory demonstrations indicate that magnetic tape itself has considerable scaling potential beyond today's commercial products. Meanwhile, instead of pushing capacity as quickly as technologically possible, the LTO consortium is now deliberately balancing density with reliability, performance, and cost.

For a storage technology which demise has been predicted repeatedly for decades, LTO not only continues to evolve at a predictable pace, but its adoption is growing, while its relevance remains on a high level. Only time will tell whether it remains relevant for another quarter of a century, but its steady progress certainly increases this possibility.

SSD controller designer FADU’s new File-Semantic SSD (FS-SSD) was announced at the 2026 OCP Global Summit. The new device promises to move the file system into the SSD itself. As detailed in a white paper, this enables GPUs, DPUs, and NICs to open and read files with “no host filesystem, no block layer, and no storage-server CPU in the path.” FADU told Tom’s Hardware Premium it expects partner samples by Q3 2027.

FADU is a Seoul, South Korea-based fabless SSD controller designer. Its FS-SSD technology is designed to handle and improve the control path, as the data path side moved to accelerators years ago. FADU’s measurements show that the file system, plus block layers, can consume about 30% of CPU cycles in a GPUDirect Storage (GDS) random-read workload. It notes that bypass options give up the files, and the company claims its solution promises the best of both worlds.

In FADU’s own preliminary Network File System (NFS) over NVMe test, on a drive built on its FC6161 Gen6 controller in a PCIe 5.0 host, remote file throughput held steady as the server downshifted from what FADU labels 16 cores to just one, maintaining about 460,000 ops/s.

The NFSv3 operations are carried inside standard NVMe commands, and the drive handles path lookup, access control, and file-to-flash mapping. FS-SSD’s performance is remarkable when compared to Linux NFS-over-RDMA, which achieved a third of the ops/s with 16 cores and only 40K ops/s with one core. The technology remains “under active development,” and FADU told Tom’s Hardware Premium it expects Gen6-host results by Q1 2027, with partner samples in Q3 2027.

FADU chooses to use NFSv3 because it’s “small (21 operations), OS- and filesystem-agnostic, and stateless” with low firmware overhead. FS-SSD supports PCIe today, with NVMe-oF over RDMA and TCP working without any new transport needed. Reusing an existing protocol is a smart move, in our view. Under the hood, the file system and flash translation layer are merged with a file layer derived from F2FS. Node and data blocks are aligned with the natural flash pages, sections at corresponding erase units, so that the F2FS node table becomes a “File Map” pointing the node IDs at physical flash addresses.

One big advantage is that the DRAM mapping metadata overhead is considerably smaller: it uses the same amount of DRAM as a standard SSD, ~0.1% of NAND capacity (about 1 GB per TB), which a standard SSD fills almost entirely with its mapping table. Here, most of that DRAM, ~95%, can act as a hot-path node cache.

One garbage collector also replaces two, avoiding what FADU calls the “double GC” of host F2FS, where file-system cleanup and the drive’s own garbage collection amplify each other. Write amplification is also 63% lower versus a host F2FS solution on a mixed sequential and random workload with FADU’s research prototype, the company said. FADU told Tom's Hardware Premium that the prototype runs synthetic fio workloads on NVMeVirt, an open-source software SSD emulator from Seoul National University, so it is not a hardware result.

Most importantly for this method, it ensures host-free access. The GPU builds NFS-over-NVMe commands in queues in its own memory, which could include HBM. Alternatively, a remote SmartNIC or DPU with NVMe-oF target offload can drop commands in the drive’s submission queue. The data goes from SSD to NIC via PCIe peer-to-peer DMA, coming out as RDMA writes. FADU’s explicitly named use cases for this include GPU file reads and checkpoints, DPU-served HTTP content delivery, and a JBoF (just a bunch of flash) file server.

FADU’s numbers for its internal test come from a client and server Intel Core i5-13600K, a CPU with 20 threads that clocks up to 5.1 GHz with 128GB of DDR5, and a Mellanox ConnectX-6 100 Gbps NIC. Synthetic testing is compared using fio with the baseline F2FS and Ext4 on block firmware versus the FS-SSD via a kernel client and an SPDK user-space client. The sequential test is 1 thread, queue depth (QD) 128, with 128KB blocks, while random is at 4 threads, the same QD128, but with 4KB blocks.

These block sizes are typical for client workloads in our experience, so they are a fair measure, with detailed preliminary results in the table below. Against SPDK on the raw drive, figures FADU provided to us, FS-SSD’s SPDK client keeps about 93% on 4K random read and 53% on 4K random write, via fio, with around a 7% and 47% cost for the in-drive file layer. Though the raw drive’s 13,240 MB/s random write is above the ~12 GB/s FADU gives as the NAND’s program bandwidth, those runs likely weren’t at steady state. The Filebench result is particularly interesting, as the SPDK random gains apply to a plain block device too.

This should be the workload most favorable for the technology, as the Filebench file server is metadata-heavy with relatively high host overhead: FADU says it uses 10,000 files in a multi-level tree, mean directory width 20, and a mean file size of 128KB with 50 client threads.

One important thing to recall is that although this test is on a Gen6 drive, the test results are on a PCIe 5.0 host. Therefore, every sequential read config tops out at around 14.1 GB/s, which is roughly the link limit. The testbed also uses a consumer-class desktop CPU, while the one-core NFS server is a showcase example. The kernel client ends up 11.5% behind Ext4 on random read and 5.3% behind on random write, again by our math.

One example of a tough question more generally is: how do concurrent GPU, DPU, and host writers coordinate? How does a kernel mount’s page cache stay coherent with GPU access? NFSv3 storage devices, by the pNFS Flexible File Layout spec (RFC 8435), are “always treated as loosely coupled,” which means “Mandatory byte-range locking cannot be supported.”

Credentials riding in the NVMe command may also face security issues, as loosely coupled devices get only “a level of security equivalent to AUTH_SYS,” NFS’s basic scheme, in which the server trusts whatever user and group IDs the client sends. FADU’s published material also does not describe features such as snapshots, encryption handling, quotas, ACLs, crash handling, and so forth, related to this. Statelessness is what makes it work, but it doesn’t solve all problems, so the trust factor moves elsewhere.

In reply to our questioning, FADU said that there is no cross-host locking, as NFS’s lock manager isn’t implemented. The drive applies each write whole, in order. If two writes hit the same spot, the second one wins; this is “last-writer-wins.” Coordination depends on the clients: kernel-mounted ones get the usual advisory locks among themselves, GPU and SPDK clients coordinate in the application, and at scale a pNFS metadata server handles the coordination. Caching is also handled like ordinary NFS, with kernel clients, or is not done at all, for GPU and SPDK clients. This is stock NFSv3 behavior.

The drive has to check user/group IDs against the file permissions itself. Because those IDs ride inside the command, a client could fake them, but FADU says it closes that issue with capability-based authentication. Each command carries a capability issued by an outside authentication server, plus a code computed with a key shared only between that server and the drive. This is not detailed in its published material. FADU adds that support for the Kerberos authentication protocol is planned. For networked drives, the standard NVMe-oF protections are used, with only pre-approved hosts admitted. A drive trusts a single host’s kernel like any NVMe drive.

However, as FADU described to us, ACLs and other features are missing in the current release, aside from encryption, which in this case is handled by the FC6161’s standard TCG Opal self-encrypting drive support. Power loss is also typically handled with capacitors flushing metadata, the write buffer, and a log of in-flight operations. On restart, the drive replays the unfinished operations, and every write is durable if the drive acknowledges it.

FADU’s longer sights are on producing a JBoF storage solution with no server in front: FS-SSDs, a PCIe switch, and a DPU or NIC for handling NVMe-oF in hardware. FADU’s model puts this at about 42% lower power, about 57% lower cost per 16-drive server, and higher rack density with significantly lower five-year total cost of ownership. The drives would slot in behind existing pNFS metadata servers and could scale. FADU’s controllers already ship with drives such as the SN861, which Western Digital launched and SanDisk now sells, but this would expand the options and solutions it can provide.

Next year should bring real numbers and samples, with the JBoF reference design also expected. There may be an NVM Express or OCP Storage proposal down the line for a file-semantic command set to further cement and mature the approach. FADU has a good idea, is building it on an existing framework, and has a testbed with results and a hardware path forward on its Gen6 controller, with a trust model in mind. A Gen6-host run is now needed to support the company’s claims.

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.

The two biggest NAND flash memory manufacturers on the planet, Samsung Electronics and SK Hynix, are reportedly working to upgrade their Chinese factories to produce more advanced chips for use in AI data centers, Reuters reports. The move comes as the two companies continue to fight off competition from the fast-growing Chinese memory makers like CXMT. Fierce competition in the lucrative AI RAM market has already seen manufacturers slash consumer-focused production to allow them to increase production capacity for the more advanced — and money-spinning — components.

Citing four people familiar with the companies' plans, the report claims that Samsung Electronics aims to switch its Xian plant to the production of 286-layer flash chips by the end of the year. SK Hynix has its sights set a little lower, targeting chips with 240 or more layers at its Dalian facility. That factory was taken over back in 2021, but a timescale for the new upgrades isn't clear.

However, while Samsung Electronics and SK Hynix are well placed to deal with the growing threat from Chinese chipmakers, both are faced with additional complications in the form of U.S. regulations. Export controls on chipmaking equipment were applied in 2022, with the aim of slowing China's technological progress. Both companies, based in South Korea, must now get licenses in order to install U.S.-built hardware in Chinese factories. The report points to this as a reason for the recent growth of Chinese firms like Yangtze Memory Technologies Co. (YMTC). The company told investors at a recent IPO preparation meeting that it aims to become the world's largest NAND flash producer by the end of 2027.

While both Samsung Electronics and SK Hynix say that they are working in consultation with the U.S. authorities, there's little doubt that this extra step has hampered the companies' ability to upgrade their factories to better meet the new AI memory demand.

It's impossible to overstate just how key Samsung and SK Hynix are to NAND supply. Samsung's Xian factory produces around 40% of the company's global output. It currently produces chips that have around 200 layers, but Samsung's plans aim to boost that to 286 layers for V9 NAND chips. For its part, SK Hynix's Dalian plant currently produces chips with 192 layers, with the company's aim for 240-layer chips reportedly confirmed by three people familiar with the plans.

Meanwhile, CXMT, China's premier chipmaker, is looking to move beyond DRAM production. A report from September 2026 noted that it was eyeing production of 3D NAND memory for use in solid-state storage (SSD) products. The country's largest DRAM producer, CXMT, posted $22.41 billion in revenue and $11.57 billion in net profit in the first half of 2026 after years of losing money. But despite this purple patch, the company is still much smaller than the likes of Samsung, SK Hynix, and Micron.

Micron faces a one-day labor stoppage at its Taoyuan operations in Taiwan on October 22, Reuters reports. Micron's employees are striking for concrete terms for this year's bonus and a clearer mechanism for sharing the company's future profits. The strike's teeth come from the resultant financial impact on Micron's operations, as semiconductor fabs are supposed to operate around the clock. The scheduled protest comes amid strong demand for memory chips and will have a minor impact on Micron's memory output.

The Taoyuan union wants Micron to present a specific proposal for this year's additional employee bonus and establish a transparent formula for distributing a portion of future profits. Previous negotiations between the company and the union ended unsuccessfully in September, which prompted employees to approve industrial action in early October. Nonetheless, the union stresses that the October 22 strike is intended to pressure Micron into reaching an agreement rather than terminate negotiations. The union is prepared to conclude a deal if the company presents terms acceptable to employees across its Taiwanese operations.

The situation could become more serious if employees at Micron's Taichung operations, its largest manufacturing site in Taiwan, decide to join the action. A separate labor organization that represents workers at that facility is scheduled to meet with Micron for mediation on October 22, the same day as the Taoyuan protest. However, the Taichung union has not yet authorized a strike.

Micron's fabs in Taiwan produce commodity DDR5 and LPDDR as well as expensive high-bandwidth memory (HBM) for AI accelerators. Amid record demand for memory of all types, even a one-day suspension of operations would have a material impact on Micron's output and earnings.

Modern semiconductor fabs are supposed to work 24/7/365, as many processes cannot be halted. However, if management has sufficient time and personnel to prepare, a one-day warning strike does not necessarily mean a complete shutdown of Micron's Taoyuan manufacturing operations, not to mention permanent damage to wafers or equipment. The actual consequences of the strike will depend on employee participation, which manufacturing operations are affected, and Micron's contingency plans. While it is likely that the output will drop, the decline will likely be negligible.

Micron employs approximately 15,000 people in Taiwan. The workers point to compensation arrangements at Samsung Electronics and SK hynix as examples of how semiconductor manufacturers can distribute profits among employees as AI-driven demand generates unprecedented cash flows for memory firms.

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.

Popular graphics post-processing injector software ReShade, commonly used to mod DLSS 5 into unsupported games, now has a foveated imaging add-on, including another standalone project that doesn't need precursor software, allowing DLSS 5 to affect only what's in view, reducing GPU load and increasing FPS.

Foveated imaging is nothing new; it's a technique that's been used in VR to increase performance. It works by only rendering what's in view, often increasing the resolution in the center and reducing it at the edges. Our eyes work in a similar way, with the clearest image in a small area in the center of your vision, blurring on the edges. With foveated rendering, you barely notice the lower-resolution edges as the peripheral vision is less concerned with fine details.

Instead of varying the resolution of the image, however, it varies the level of detail in DLSS 5 Neural Rendering. DLSS NR loads a whole AI model into your GPU and renders images in real time, making it a resource-intensive task; but the task is minimized greatly when most of the detail is only asked for in the middle of the image. That's what projects like maximedgoulet’s Foveated DLSS5 and ClarkCheekyKent’s CheekyFoveatedDLSS aim to do; with Foveated DLSS being a ReShade add-on and CheekyFoveatedDLSS capable of being a standalone integration.

Both implementations allow you to adjust the size of the center area with the highest rendering quality, with independent width and height adjustments to suit your personal situation, as some people have a larger focus area than others or have a different monitor distance. You can also adjust the render fall-off rate, so the image quality lessens more quickly or slowly past the focus area.

As Maximedgoulet's implementation is an add-on for an injector, the pipeline is quite long compared to the standalone integration of CheekyFoveatedDLSS, which Reddit comments claim is more convenient and more polished. Though both show a big improvement in performance, Maximed's Reddit post on Foveated DLSS5 claims an improvement from 48 to 80FPS in The Witcher 3 with 2x Multipass at ultrawide 7680x2160p on an RTX 4090. Considering Maximedgoulet’s 4090 could not handle DLSS-NR on an ultrawide, this implementation might genuinely be feasible to make Neural Rendering more playable.

Nvidia has earned billions selling AI accelerators, but with the emergence of agentic AI, CPUs are going to play a considerably more significant role than before, which creates new opportunities for the company. Reuters reports that Nvidia has secured a major design win with its Vera CPUs with AI cloud provider Modal. According to Modal, preliminary evaluations showed that Vera could deliver twice the throughput of its existing AMD and Intel processors, although the company does not intend to cease using CPUs from its current suppliers.

Modal provides cloud infrastructure that enables AI developers to deploy AI agents that can perform complex operations autonomously over extended periods. Such workloads require substantial CPU resources for software execution, data processing, and other tasks that cannot be efficiently handled by GPUs. Modal currently relies exclusively on AMD and Intel processors for these operations, but its tests indicate that Nvidia's new Vera CPUs could significantly improve performance in its specific workloads. Of course, since Vera is based on an Arm instruction set architecture, Modal's decision to adopt Vera will require substantial modifications to its software. Nevertheless, Modal believes that the potential performance improvements justify the additional engineering effort.

The reported 2x throughput advantage is particularly interesting because agentic AI workloads can involve numerous independent tasks that compete for CPU cores, cache capacity, and memory bandwidth. However, Modal has not disclosed detailed benchmark configurations it used, specific AMD and Intel processor models, or performance-per-watt figures. Consequently, it remains unclear whether Vera's advantage is enabled by advantages of its Arm v9.2-based Olympus CPU cores that can decode and execute up to 10 instructions per cycle, its memory subsystem with 1.2 TB/s of bandwidth, or other architectural characteristics. Also note that tests compared Vera against currently available AMD and Intel processors rather than their upcoming generations that will compete against Vera in the coming years.

Since Modal cannot port all of its software to Arm ISA overnight, the company will continue using x86 CPUs from AMD and Intel, according to Modal chief executive Erik Bernhardsson. Rather than sticking to one ISA for everything, Modal intends to operate a heterogeneous server fleet and select the most suitable processors for each workload. Naturally, the company intends to evaluate upcoming AMD and Intel processors once they become available to make its choices in the future.

For Nvidia, the agreement represents a major step toward making Vera a standalone server processor that commands a major share of the server market. The company expects Vera sales to generate at least $20 billion during its current fiscal year and estimates the potential total available market for these CPUs is approximately $200 billion. The company is on track to sell at least four million Vera CPUs in fiscal 2026.

The announcement comes shortly after Modal secured $750 million in financing led by Accel, which valued the company at $15.75 billion. Modal expects its annual revenue to reach $1 billion within the next year. The company's service consumption has increased 3X in the last 12 months, while revenue has surged more than 15 times compared with the previous year, Reuters reports.

What if you could buy a cheap used DDR5 SODIMM (laptop memory) kit and transform it into a super-fast DDR5 desktop kit? That’s what electronics hobbyist Blighted Agent recently did when they succeeded in converting a SK hynix 2x 16GB DDR5-5600 SODIMM kit they got from Facebook Marketplace for $120 into a 2x 16GB DDR5-7800 desktop kit, claimed to be worth around $1,000. They also had to buy some blank DDR5 desktop memory PCBs from AliExpress for around $16 each, and a set of heatsinks for around $18.

In the above video, our hero says they bought the donor laptop 2x 16GB DDR5-5600 sticks for just $120, which is a bargain. With extra bits and pieces from AliExpress (desktop DDR5 PCBs, etc.), the total bill of materials came to $175. Blighted Agent comments that the SODIMMs used what he believed to be SK hynix A-die modules, which are the same as the ICs used in expensive desktop DDR5 modules like the G.Skill Trident Royal line.

The process began with taking the memory ICs from the donor modules using a hot air station. Then they were cleaned and had 0.45mm leaded solder balls added, using a DDR5 stencil, reballing jig, and hot air. Next, the blank desktop DDR5 PCBs were prepared. A little solder was added to the plethora of BGA connectors to be ready for the memory chips to connect to.

The old DDR5 ICs and the new desktop modules could now be mated, using flux, the preheater, hot air, and watching and prodding carefully with a dental pick. Blighted Agent’s experience lets him know when the BGA chips have successfully mated with the PCB. You can eyeball when they pop precisely into place due to surface tension, and offer up a modicum of resistance to pick prodding.

Finally, the enthusiast added the SPD chip and BIOS chip from the SODIMMs to the new desktop DIMMs. These new desktop DIMMs were quickly tested in a PC before they were finished off with carefully applied thermal pads and the fancy-looking heatsinks.

Blighted Agent felt lucky that there were no issues with the newly created desktop modules. There’s a lot of intricate things that can go wrong during such a process. The initial boot verification showed them recognized in his Asus ROG Maximus Z790 Apex Encore motherboard as two “SK hynix 16,384MB 5600MHz” modules, which was correct. Some tuning resulted in rock-steady performance at DDR5-7800 CL38 and 1.40V. This was verified by stress testing for 90 minutes, which the enthusiast reckons was ample for a gaming PC. It is very likely a better result than using those mechanical SODIMM-to-DIMM converters you can buy, which can be problematic.

Blighted Agent seems to specialize in BGA soldering work, and has also successfully upgraded several graphics cards with double the VRAM. Though videos like this are edited to be brief, and they make the process look easy, the TechTuber admits there is a lot that can go wrong during this kind of rework. Moreover, with RAM modules, they lack the testing equipment to locate an issue with any particular IC on the PCB. So, if this module didn’t work, they might have ended up in a world of pain, not knowing which memory chip had an issue due to either an internal fault or a BGA soldering glitch.

Looking around at used DDR5 SODIMMs, it looks like Blighted Agent was very lucky to get a used working 32GB kit for $120. I just checked eBay U.S., and the best deal there was $320. Meanwhile, the best price for a new 32GB DDR5-6000 kit seems to be $449 at the time of writing.

We reported on Russian enthusiast VIK-on succeeding in a similar project earlier this year, but all their costing was in Rubles, and they went the extra mile in flashing custom firmware so the remade modules would be auto-detected with 6400 MT/s XMP support on most motherboards. In late 2026, DDR5 RAM continues to be too expensive.

Panchovix on GitHub recently released a VBIOS configurator for RTX 30-to 50-series cards that doesn’t require flashing. The loader provides a UI for easy configuration and lowers the risk of bricking your GPU by avoiding a risky flash process, and it's available for Linux, too.

Software like MSI Afterburner or ASUS GPU Tweak is often the go-to tool for quickly changing your graphics card’s settings; however, those tools have hard limits to how much you can push the graphics card. If you want to tweak your GPU beyond the firmware’s set limits, you can change it by tweaking the parameters in the VBIOS. Configuring VBIOS is similar to changing BIOS settings in the BOOT menu. With the VBIOS loader, you can change settings beyond the firmware’s hard limits.

The way it works is by storing the modified VBIOS image in the GPU’s register key; as the Nvidia driver looks for a VBIOS override on startup, it finds the VBIOS image and restarts, applying the override settings. The flash chip on the graphics card is not overwritten, reducing the risk of bricking your GPU. However, this does not protect the card from any extreme settings that could destroy electrical components; it merely provides a safer and more convenient way to adjust and apply VBIOS settings, including a way to roll back to the default VBIOS settings should you face any instability.

Bricking a flash chip isn’t as catastrophic as it seems, however. As long as you have a backed-up version of the VBIOS, you can easily buy an SPI flash chip programmer or even build your own using a cheap Raspberry Pi Pico and its many clones; sometimes programming the flash chip may not even require desoldering. Programming a flash chip is very tedious and inconvenient, though, which is why avoiding the risk of a botched flash process altogether is so appealing.

Unless you’re familiar with power delivery, voltage tables, and the patience required to test for hours, we wouldn’t recommend jumping into this unless you’re prepared to risk your GPU. However, you can still safely take advantage of this software by tweaking the fan curves and other settings you’ve applied and tested in software like MSI Afterburner if, for some reason, the startup settings don’t stick. This software will give your GPU new default settings that override at every startup, so long as Nvidia doesn’t remove the registry key that allows the VBIOS override.

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.

You don’t need the latest and greatest PC hardware to have fun or even break overclocking world records. OC expert Luumi has demonstrated this very capably by achieving a new HWBot world record using an ancient Intel Core i5 4670K, a modest amount of DDR3, and (inevitably) a flask or two of LN2. Overclocker Luumi recently knocked the four-cores Intel Core i5 4670K Cinebench R11.5 record holder off their perch after 12 years, achieving a multicore score of 10.8 cb.

The HWBot-crowned system is built around Haswell-era Intel silicon, the Core i5 4670K to be precise. This is an unlocked 4C/4T CPU with a stock base/boost of 3.4 / 3.8 GHz, 84W TDP, with a 6MB cache and HD 4600 graphics, built on Intel’s 22nm process. You had to buy an i7 chip back in this era to get 4C/8T.

Luumi’s system hosted the CPU on an ASRock Z97 OC Formula motherboard, which was fitted with 4GB of DDR3 RAM from XPG, and fed ample power via a Corsair AXi 1600. To achieve the Cinebench R11.5 benchmark record liquid nitrogen was used to cool the 4670K, and the validation files show the CPU ran at a blistering 6,301.00 MHz.

Again, we’ll comment that this isn’t a world record Cinebench R11.5 score for any / all quad-core processors. It's just in the Core i5 4670K category. Nevertheless, it is great to see retro hardware achievements like this, 12 years later. As one other HWBot community member commented, it is brilliant to see an OC result on the HWBot homepage that involves neither an X3D CPU or RTX 5090 GPU. You don’t need the latest, greatest, most expensive, nor unobtainuim components to get featured on the online home of competitive overclocking.

Out of curiosity I decided to give ye olde Cinebench R11.5 a spin on the laptop I’m currently working on. With its 12C/24T CPU, it trounced the old-but-record-breaking Haswell desktop, of course. Even though the laptop is running in cool/quiet mode I achieved 4x the 4670K score.

Mostly I was happy that this older version of Cinebench still works on modern hardware and Windows 11 without any fuss. Some apps which were popular benchmarking staples, like 3DMark tests from DX10 and earlier eras, have issues on modern computers making the results you can wheedle out of them invalid for HWBot rankings. Luumi used Windows 7 64-bit Pro for their Haswell CPU Cinebench R11.5 testing.

A Brazilian electronics and IT distributor, Oderço, has gone on Instagram after failing to find answers about a missing shipment of RTX 5090 GPUs worth around $470,000 or R$2,500,000. According to its Instagram post [machine translated], the company has never faced an experience like this in its 38-year history. It was expecting two pallets of Zotac RTX 5090 GPUs at Guarulhos International Airport in São Paulo, which supposedly arrived there but then disappeared. The company has not provided any details, like the shipment’s arrival date or any tracking numbers, but claims that there hasn’t been any official response regarding its shipment inquiries. Because of this, the company went on the social media platform pleading for answers.

RTX 5090s are currently in short supply across the world, with the top-tier card disappearing from online retailers in the middle of September. There have been rumors that Nvidia has ceased production of the GPU to focus on more expensive professional AI cards, although it insists otherwise. Still, it doesn’t help that the flagship GPU is marked “not carried” in Micro Center’s online retail store, making it insanely difficult to find one of the best gaming GPUs you can buy today.

We don’t have any idea how many GPUs are missing, as the distributor only mentioned two pallets’ worth of RTX 5090s. A Zotac Gaming GeForce RTX 5090, which goes for around $8,000 on Amazon presently, is listed at R$33,999.99 on a Brazilian online retailer Promotech. This means that the company is missing 63 GPUs at the minimum, although this is likely going to be so much more considering that the $R2,500,000 amount the company said is its acquisition cost, not the retail price that it’s expected to go for.

We’ve seen various scams where retail customers lose their GPU shipments on the way to their home or delivery address, as well as unscrupulous buyers stripping off the GPU core and memory modules from an RTX 5090 and then shipping it back to the seller. This also isn’t the first instance that a shipment of high-value graphics cards has been stolen — one brazen crew has even rammed security escorts to hijack an AI hardware shipment, while another group stole two trailers marked with the Nvidia logo, only to find that it contained sand.

A new version of DLSS 5 on NBA 2K27 was just released, and modders have already extracted it and are running it on unsupported games. Modders are comparing performance between the older and newer Neural Rendering (NR) model and found it up to 40% faster than the previous one.

While many are still experimenting with leaked and first-release builds, Renan Maniero has already extracted the new 310.9.16.0 DLSS NR build, letting other modders use it in unsupported games and compare performance. Gaming Optimized on X compared the new NR model to the old one and found massive improvements of up to 90% in The Witcher 3 running DLSS 5 natively.

Running a full NR model to modify your game's image is resource-intensive, just as LLMs require a lot of RAM; DLSS NR does, too. To improve performance, Nvidia made the AI model 24% smaller, using 20% less VRAM at 4K, and, according to Nvidia, processes its neural rendering workload up to 2x faster.

Typically, improving an AI model means increasing its parameters and size—in other words, giving it a bigger brain. However, because consumer GPUs have limited, non-upgradable VRAM, Nvidia can't improve by adding a bigger model; instead, the AI needs to become more efficient while reducing resource usage.

These comparisons were much easier than switching back and forth between updates, since the latest version still includes the older model as a preset. The new DLL has two Neural Rendering presets: Preset A is the old model, and Preset B is the newer model.

As with many other DLSS 5 experiments like those Valery Kryzhanovsky does, DLSS is injected into the graphics pipeline using RenoDX or OptiScaler, both of which let you tweak the DLL settings to get different results. To run DLSS NR on older RTX GPUs, the modding community also modified the runtime to support RTX 20-series GPUs, as the OptiScaler GitHub README notes.

Nvidia plans to release DLSS 5 to RTX 40-series GPUs, but there are no reports of it officially coming to RTX 30- or RTX 20-series cards; the modding community seems to have done it anyway.

Nvidia’s GeForce RTX 5090, undeniably one of the best graphics cards of our time, vanished overnight without a trace and is now selling for $8,500 on Amazon. In a recent development, Reddit user DallasGrave showcased a custom quad 8-pin power conversion kit designed for the notorious melting 16-pin (12VHPWR) power connector and the later 12V-2x6 revision. This invention, an upgrade over a previous mod, could reduce the risk of power-related meltdowns.

Unlike the endless stream of aftermarket adapters designed solely to prevent 16-pin power meltdowns, DallasGrave's iteration is more like a power-conversion kit. The direct-mount kit sits above the graphics card and uses a custom harness soldered to the graphics card’s PCB power rails. The quad 8-pin power conversion kit bypasses the 16-pin connection and redistributes the massive power draw more evenly across four conventional 8-pin PCIe power connectors.

Each 8-pin PCIe power connector can deliver up to 150W, so all four combined in this custom configuration match the 16-pin connector’s maximum capacity of 600W. However, this configuration addresses concerns with the 16-pin power connector, which channels 50A through a small, tightly packed set of pins. The power-conversion kit instead spreads the load across four 8-pin PCIe power connectors, which are physically larger and allow a wider pin pitch.

While 8-pin PCIe power connectors are not entirely immune to melting or other power-related failures, such incidents are far less common than issues with 16-pin power connectors. The 16-pin power connector is significantly more compact than a single 8-pin power connector and carries 4X the wattage, so it is more prone to higher current density and heat buildup.

According to PCI-SIG specifications, each of the six power pins inside the 16-pin power connector is rated for a maximum current of 9.5A. This means that, in theory, the power connector's total capacity reaches up to 684W or 57A. For example, 600W (50A) requires each power pin to carry about 8.33A, which is already close to the recommended safety limits.

By contrast, a standard 8-pin PCIe power connector contains three power pins. Combining four of these connectors in tandem provides 12 power pins. When distributing a 50A load across 12 pins, each pin carries just 4.17 amps, about half the current per pin of the 16-pin power connector design. This lower current per pin dramatically reduces wire and terminal temperatures and lowers the risk of heat-related damage.

The quad 8-pin power conversion kit tricks the sense pins on the 16-pin power connection into recognizing the full 600W. However, the Redditor claims they have tested the kit for up to 800W with a shunt mod. The beauty of the kit is that users can use it as a standalone power source or alongside the native 16-pin power connector, essentially acting as a parallel load spreader.

DallasGrave is developing a custom backplate that will enhance the power conversion kit's visual appeal. Notably, it is not limited to the GeForce RTX 5090 or any specific brand. According to the Redditor, they are preparing a range of models for production that cover nearly every variant on the market, including Nvidia’s Founders Edition. However, the creator has not yet revealed key details such as the official release date, pricing, or installation logistics.

Last week, gamers still holding any hope that the GPU market would somehow stabilize had their hopes dashed. A while after Nvidia reportedly put the RTX 50 Super series on hold, rumors started flying that production of the already-rare RTX 5090 was stopping, likely to use precious silicon manufacturing capacity for more AI accelerators. Now, the company's senior VP Jeff Fisher reportedly said that card was not discontinued and would continue to be shipped. The statement comes after a myriad of websites, including Tom's Hardware, have asked the company for official comment, but to no avail.

The information comes from Taiwanese websites including 4Gamers and SJTV, which both are quoting a purported post-event interview where Fisher offered a brief explanation of the situation. According to the VP, supplies of the GPU are limited, but Nvidia is seemingly going all out to get the product to market (paraphrased from the Taiwanese reports).

"The supply chain (capacity) is indeed somewhat constrained, but NVIDIA is doing everything it can to get the product on the market. Although there are other variants of the RTX 5090 (chip), production has not been discontinued, and NVIDIA will continue to ship, which is very important," Fisher reportedly said to 4Gamers.

He also reportedly reiterated a common quote from Nvidia execs, stating that without GeForce, Nvidia wouldn't be where it is today, and likewise, the AI market wouldn't exist as it does today.

The claim that the card isn't gone after all merits some spot-checking, so we did a cursory browse of the common retailers. At Amazon, RTX 5090s are selling for about $8,500, but from third-party sellers. Best Buy has a grand amount of naught cards on offer, while Newegg lists 5090s for about $7,300, but from what are likely Chinese sellers, judging by the shipping time. The ever-famous U.S. tariffs would likely add quite a chunk of change to that price tag, too. Finally and perhaps most poignantly, the card remains absent from Nvidia's own marketplace and Micro Center as of this writing.

Some would say that these statements are nothing but a means to keep the company in gamers' minds, even though gaming-related revenue is now a vanishingly small piece of Nvidia's ever-larger money pie.

Jensen's firm isn't the only one seemingly keeping up appearances, as Intel has repeatedly stated that its long-awaited refresh of consumer GPUs isn't dead, and last year AMD said it still intends to deliver "the best mainstream gaming GPUs on the market." Yet there are no new GPU launches from any of the three, and their quarterly launch figures keep doubling down on AI.

We reached out to Nvidia for comment on the situation and received no reply.