Based on the mainstream B860 chipset, the ASRock B860 Challenger Wifi sits on the budget side of Intel's motherboard lineup, and costs a reasonable $149.99. You get a full-sized motherboard with full support for Intel’s Core Ultra and Core Ultra Series 2 (Arrow Lake and Arrow Lake refresh) processors. Still, some sacrifices in specs and features are inevitable at this price point.

The all-black B860 Challenger (there is a white version, too) includes all the basics. You get eight rear USB ports, three M.2 sockets (one PCIe 5.0), four SATA ports, 2.5 GbE, Wi-Fi 7, and a basic audio solution. It falls a bit short on USB speed (5 Gbps max.), power delivery isn’t strong (though it handled our 270K Plus without issue at stock), and ASRock’s BIOS is fully functional but dated compared to the competition. It has everything that most will need from a motherboard, but it’s not the fastest or the best at anything, which you should generally expect from a low-priced mainstream chipset.

Performance on this board was actually quite good in our testing. I have to admit, that surprised me a little given the VRM configuration. I expected it to throttle on some longer-running multi-threaded benchmarks. But the B860 Challenger proved me wrong and was average to above average across most of our tests. Whether gaming, doing office work, or juggling creative workflows, the Challenger handled our Intel Core Ultra 270K Plus without issue, though the VRMs ran hotter than on other tested boards. I would suggest using a chassis with good airflow with this board, especially if you plan to run a high-end processor and long-running, heavily multi-threaded applications.

Below, we’ll examine the B860 Challenger's tested performance and other features to see if it earns a spot on our list of the best motherboards. But before we share test results and discuss details, here are the specifications from the ASRock website:

Specifications of the ASRock B860 Challenger Wifi

Inside the Box

ASRock includes a few accessories to help get you up and running. You get two SATA cables, an M.2 screw and mount, Wi-Fi antennas, stickers, and a quick installation guide. The collection is sparse, but typical for a low-cost mainstream-class motherboard.

Design and Features of the B860 Challenger Wifi

The B860 Challenger sits on a matte-black PCB with black connectors and heatsinks. Only the Challenger branding on a couple of heatsinks and the capacitors dot the board, breaking up the stealthy appearance. It lacks a ‘full coverage’ heatsink on the bottom, partly due to the M. 2's physical orientation, but two of the three M.2 sockets do have heatsinks. You won’t find any integrated RGB, but the board has multiple headers to add your own.

Overall, this is a plain-looking board with a lot of exposed PCB, but that's typical for this chipset and price. Still, it will blend well into any dark build theme.

In the top-left area of the board, we see the standard dual 8-pin EPS connectors to power the processor. Below that is the large VRM heatsink that extends to the rear IO area and covers some unsightly motherboard components. On top, we can see the silver Challenger branding. A second VRM heatsink covers the top portion of the power delivery. Both appeared to make good contact with the MOSFETs and inductors/chokes below.

Moving right, past the socket, the next feature is the four DRAM slots, each with locking mechanisms on both sides. ASRock lists support for up to DDR5-8666, which is plenty fast for the platform, especially given today’s ridiculous memory prices.

Tucked between the heatsink and the DRAM slots on the left, along with two others on the right side of the slots, are the first (of seven) 4-pin fan headers. Per usual, each header supports PWM and DC-controlled devices. The CPU_FAN1 connector supports up to 1A/12W, while the remainder support up to 3A/36W. In other words, you won’t have any issues powering your system fans from the board. Just be sure not to overload them. You can control the headers via the BIOS or the A-Tuning app with FAN-Tastic tuning.

Rounding the corner and moving down the right edge, you'll find the first two 3-pin ARGB headers. Along the bottom edge are additional headers: a third ARGB header and a single 4-pin RGB header. The Polychrome Sync application in the BIOS or as a standalone app controls the attached devices. Next are the 24-pin ATX connector to power the board, a front-panel 19-pin USB 3.2 Gen1 (5 Gbps) header, and a front-panel USB 3.2 Gen1 (5 Gbps) Type-C header. Surprisingly, 5 Gbps is the fastest you’ll get out of any USB port on this board. For 2026, that’s disappointing, even in a budget-class mainstream board.

Power delivery on the B860 Challenger is paltry, but not by phase count; it’s 14 phases total, 10 dedicated to Vcore — but by the weak MOSFETs. Power heads from the EPS connectors to a Richtek RT3638AJ 3-rail, 8-phase PWM controller (meaning the Vcore runs ‘teamed,’ common in today’s systems). From there, power goes to 10 50A Vishay SiC632 Dr.MOS power stages. The 500A available isn’t a lot, but it handled our Core Ultra 270K Plus without throttling. That said, the VRMs ran hot during our 30-minute stress test, so make sure you have good airflow to keep temperatures down.

On the bottom half, starting on the left edge, is the audio solution: the basic Realtek ALC897 and a couple of dedicated audio capacitors. This isn’t the best audio section around, but par for this class of board. Still, most users will be satisfied with this implementation.

Two full-length PCIe slots sit in the middle of the board and couldn’t be spaced further apart. The top slot is reinforced, connects through the CPU, and is your primary slot for graphics running PCIe 5.0 x16 speeds (it does not bifurcate). The bottom slot connects through the chipset and runs up to PCIe 4.0 x4. The large gap between them lets you fit any video card, while still leaving that bottom slot open for expansion.

Mixed in and around the PCIe slots are three M.2 sockets. The first, above the primary PCIe slot, uses a larger heatsink with a quick-release mechanism that makes installing and removing the device easy. Under the heatsink is a CPU-connected M.2, M2_1, that runs at PCIe 5.0 x4 (128 Gbps) and supports devices up to 80mm. The other two M.2 sockets run at PCIe 4.0 x4 (64 Gbps), with one, M2_2, under a simple (not EZ DIY) heatsink and the other, M2_3, with no heatsink.

If you want to use RAID on the M.2 drives, you’ll have to look elsewhere, as the B860 Challenger doesn't list support for that here. Note that the primary M.2 socket made good contact with the M.2 drive. Moving right, past the chipset heatsink to the edge of the board, we reach the four SATA ports. These you can use RAID with (RAID0/1/5/10) for that extra speed or redundancy.

Finally, we snapped a few images of the board’s active ICs. This ASRock board uses a combination of Richtek (PWM controller), ASMedia (USB), Realtek (audio and networking), and Vishay (MOSFETs).

At the bottom are several headers, including front-panel audio and USB ports. A complete list of connectivity is listed below, from left to right:

• Front panel audio
• 4-pin RGB
• 3-pin ARGB
• (2) USB 2.0 headers
• (3) 4-pin fan headers
• 2-pin Clear CMOS jumper
• SPI TPM header
• Power LED and Speaker
• Front panel

Flipping the board around to the rear I/O, we can see enough ports for most users. Starting on the left, we see the HDMI (v2.1) output for integrated graphics, with the Wi-Fi 7 (the ‘slower’ 160 Hz) antenna screw-in connections above it. Moving right, we spy the only USB Type-C port on the rear IO, and it’s a slow 5 Gbps port. In fact, 5 Gbps is the fastest USB you’ll see on this board, which will disappoint anyone looking for speedy USB.

Next are two USB 2.0 ports (black), six more 5 Gbps ports (blue and yellow: the latter are the Lightning USB ports for reduced latency). Above the yellow Lightning Gaming ports is the Realtek-based 2.5 GbE. Next are the audio inputs/outputs, with three 3.5mm jacks (input/output/microphone). The B860 Challenger lacks SPDIF optical output, which could affect users who want to send the audio signal to an AV/R or other external output.

If you’re an esports gamer where every millisecond counts, the Lightning Gaming ports could come in handy. Otherwise, the feature adds little value for the average user.

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Firmware

Like other ASRock boards, the B860 Challenger starts in the informative Easy Mode, but it also lets you adjust several options (XMP, profiles, boot order, access to Fan-Tastic Tuning, etc.). The Challenger uses a black background and white text with light blue highlights. The high contrast also makes it easy to read. The standard BIOS displays headings across the top, with subheadings and details below.

You can tweak anything here, as ASRock includes every option you can think of. Overclocking is straightforward, with most options readily available. The layout is logical, and the mouse movement is smooth. We have no significant complaints about the ASRock firmware, but it could use a facelift to keep up with recent updates from Asus, Gigabyte, and MSI.

Software

ASRock offers several different software options. These include the App Shop, which lets users install drivers and software; the Nahimic 3 audio control panel; the A-Tuning application that lets you overclock and control fans; the Polychrome RGB software; and more. It also includes a Blazing OC Tuner, Motherboard Utility, and a convenient pop-up to install drivers on first boot. ASRock’s software gives users everything they need to manage and tweak their systems.

For those who want to run local AI models, ASRock’s Claw Quickset software automates installation, configuration, and environment setup so you can start using AI with minimal technical knowledge. On this 270K Plus system, it takes around 5-10 minutes to install the software and get running (most of the time is spent downloading data). Once installed, you’re presented with a browser-like window where you can chat, build your agent, and more.

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..

Starting with our synthetic benchmarks, the B860 Challenger was average to above average in our tightly packed tests, doing well across a wide variety of work. So far so good with this budget board!

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.

These settings aim 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.

The B860 Challenger did well in the synthetic 3DMark benchmarks (leading the pack, in fact), and was average in our games. In short, there’s nothing to worry about regarding performance on this board, whether for work or play.

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.

For memory testing, we skipped our fastest kit (DDR5-8800) because it exceeded the board's rating. The second G.Skill kit at DDR5-8200 worked flawlessly, as expected, since it's on the board's QVL list. The Challenger doesn’t have the highest rated memory speeds, but it’s easily capable of working in (and past) the sweet spot. Just don’t expect to break records with this budget board.

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 on this board with our flagship-class 270K Plus and the Kingston DDR5-7600 kit at stock yielded a peak of 339W at the wall, and lands on the higher side of average. Idle power use was high, settling around 71W. On average, it uses slightly more power than the boards tested so far, but isn’t out of line, and you wouldn’t notice it on your electric bill.

VRM temperatures were fine during our testing, peaking at nearly 57 degrees Celsius on our sensor (this board does not have an integrated VRM/MOS temperature sensor). While temperatures are warm under ~230W loads, the 50A MOSFETs and heatsink kept things within spec. I wouldn’t push this board's power delivery too hard, but it handled our 270K Plus without issue.

Bottom Line

ASRock’s B860 Challenger ($149.99) is an interesting board for the price. It can handle the basics and most of what more expensive boards can without issue, but it has shortcomings. Selling a mainstream-class motherboard, even at the cheap end of the spectrum, without at least one 10 Gbps USB port feels like an oversight in 2026. Sure, you can add an expansion card for faster speeds, but other boards around this price point include at least one 10Gbps port, freeing up the slot for other, more advanced, expansion needs. Still, you get three M.2 sockets, one PCIe 5.0 slot, average networking, and an all-black look that skips integrated RGB and blends into any dark-themed build.

As for the competition, there aren't many boards near the $150 price point that are readily available. Gigabyte’s B860 Gaming X Wifi 6E ($159.99) is a different option with similar features (though slower, yet still fast enough, Wi-Fi 6E) and at least one 10 Gbps USB port. That said, the contrasting heatsink color on the black PCB doesn’t sell me. Asus’ TUF Gaming B860-Plus Wifi ($199.99) is another strong contender, but costs 33% more. For that money, you get faster USB ports (including 20 Gbps Type-C), more robust power delivery, and several AI and DIY features. MSI’s B860 Gaming Plus Wifi ($209.99) is the most expensive of the bunch and offers the best connectivity, including Thunderbolt 4 (40 Gbps) Type-C, four PCIe slots, and faster 5 GbE and 320Hz Wi-Fi. Whether that’s worth a $60 premium depends on whether you can use the faster options.

Overall, we do like the ASRock B860 Challenger. At $150, it is one of the lowest-priced B860 ATX boards you can find. But that low price comes with drawbacks, which is why it doesn't make our best motherboards list like its big brother, the X870E Challenger, did. Still, it’s a capable board and a worthwhile base for building your Intel-based system. If you need faster USB ports or AI features that make life easier, other options exist, but you’ll have to pony up more cash.

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This Halloween weekend is the perfect time to think about buying a new 3D printer at a brilliant discount. Spooky season is nearly over, but as we hurtle towards the holiday season, the big names in the 3D printer world have slashed prices, making it even more affordable to pick up a new printer before the year is out. There are options that'll suit any skill set and experience, from total beginner to complete pro. We've put together some of the best deals you'll find on 3D printers right now, and you'll see discounts on some of the best 3D printer models out there.

● Check out Creality's 3D printer deals

● Check out Elegoo's 3D printer deals

● Check out Bambu Lab's 3D printer deals

● Check out Prusa's 3D printer deals

You'll see the biggest and best models on sale right now. There are models from Elegoo, Creality, Anycubic, Bambu Lab, and Prusa on sale, with resin and filament discounts to match, along with accessories.

You'll see the Bambu Lab H2D dropping to just $1,399, for instance. At the other end of the market, there's the Bambu Lab A1 Mini, now just $199, or the Creality Ender 3 V3 for $239. Or, you could pick up the Elegoo Centauri Carbon 2, down to only $319.

These big names are running sales throughout the next few weeks as we head towards the Black Friday sales period, but just because the sales are live doesn't mean the stock will be there. If you want a bargain on a new 3D printer right now, here are the deals you'll want to look for.

Best 3D Printer Deals for Halloween

Best 3D Printer Filament and Resin Deals for Halloween

More Tech Deals

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

Darkbloom, a decentralized AI inference network that aggregates and sells spare compute capacity from Macs, told its members to expect revenues to fall as token prices continue to drop. According to The Register, the price per million tokens for Anthropic dropped by 77% in under five months, falling to $0.62 in October 2026 from $2.65 in May.

“Data centers have become cheaper. Output per NVIDIA cluster is up ~20x this year, and their margins are wide enough to cut prices 90 percent and still profit at 50 percent,” said Kydo, a researcher from Eigen Labs, the developer of the compute platform. “The market caught up to our price. We could go lower, but then most of you would earn even less [than] nothing.”

It’s estimated that someone running an M5 Pro Mac Mini with 64GB of Unified Memory could earn as much as $192 per month. This is the best-case scenario, though; the median earnings of the top 50 operators on Darkbloom’s leaderboard are about $159.86 per month. This translates to about $5.26 daily or $1,918.50 annually. However, if we account for Anthropic’s 77% token price drop, earnings will fall to a measly $36.77 per month, or about $1.23 per day.

AI token prices are falling so fast that they've even outpaced Moore’s Law, with some reports saying AI is becoming 50% cheaper every quarter and up to 13 times more affordable every year. News of companies blowing through their annual AI budgets in months has less to do with per-token price and more with the number of tokens, as agentic AI use outpaces token price drops. Aside from that, OpenRouter, Darkbloom’s primary client, has started prioritizing decode speed, quantization, and prefill speed, putting users without a top-of-the-line Max or Ultra Apple chip at a disadvantage.

Despite that, Darkbloom says it will not sit idly by and let some users lose out because of these changes. The network is analyzing model demand to advise members on which models are in higher demand right now. It’s also looking at other kinds of workload beyond inference, including distributed CI/CD jobs, improving network performance to better compete against other computer providers/aggregators, and finding other clients outside of OpenRouter.

In case you're not yet subscribed to our Tom's Hardware Premium subscription service, here's what you've been missing out on this week. We detail our thoughts on Anthropic's filings pre-IPO, Cadence's new suite of LLMs to power its EDA tools, how Nvidia is securing its entire supply chain to serve AI data center demand, how Vera CPUs are landing in the cloud, an update to the ongoing TP-Link saga, and more. Remember, to access any of the articles listed here, you'll need to arm yourself with a subscription.

We've been hard at work behind the scenes to determine exactly how locally-run AI models and workloads stress consumer-level components. While throughput and tokens per second are indeed important factors, our resident CPU expert Jake Roach has begun laying out his vision for how Agentic workloads tax CPUs, and how we're building benchmarks in this newfangled AI world that the PC hardware space finds itself increasingly entrenched in. It's not often that readers get the chance to look at our behind-the-scenes work, and this piece offers a look at some of the foundational exploration we're doing around how to define what an agentic AI CPU benchmark might look like in the future.

• Our first step at defining a CPU benchmark for agentic AI — how we can measure throughput of agentic AI workloads without any GPU involved

As the rise of Artificial Intelligence increasingly becomes attached to powerful, locally-run hardware, you might encounter terminology and nomenclature that you may otherwise not be familiar with. So, we've published a primer on all of the basic terminology that you need to know moving forward. Currently, you get breakdowns of how inference works, details on quantization, context, KV cache, and more. We're striving to update this page as our exploration with local AI grows, to serve as a handy bookmark. It's not a mere dictionary either, as we contextualize how each of these things relates to the larger overall model, how it might be served, or where you might encounter it when trying to run an AI model of your own.

• A primer on key AI LLM concepts — KV cache, weights, quantization, and how inference actually works

Nvidia's Vera CPUs were a salient part of a swath of Oracle announcements this week. The chip, usually found alongside Nvidia's NVL72 rack, is now generally available, but curiously, standalone Vera instances are also available on OCI superclusters. The CPU is specifically designed with Agentic AI workloads in mind, and it just so happens that we've benchmarked an Nvidia Vera server just this week to highlight the efficacy of how well Vera might perform under certain workloads.

• Standalone Nvidia Vera CPUs land in Oracle Cloud's multi-gigawatt deployment — our independent benchmarking of a local server reveals Vera's massive memory bandwidth lead over dual Xeon 6 server

Last week, we covered TP-Link's proposal to allow the router manufacturer to sell its Wi-Fi 8 products in the U.S. Now, according to a new report, it's alleged by the FCC that TP-Link's own reports contain "false or incorrect information in its applications" related to equipment authorizations for four different models of Wi-Fi 8 routers that the company hopes to sell stateside. As the saga continues to develop, we attained a statement from TP-Link on the subject, as the situation continues to develop.

• FCC rebuffs TP-Link again as it attempts to sell Wi-Fi 8 gear in the US — FCC alleges inaccurate documentation and out-of-spec power levels for routers

Anthropic's large and sprawling S1 filing made headlines this week as the company prepares for an IPO. Within the document, it details many (but not all) of the numbers driving one of the world's foremost AI labs. Once you get past the mind-bogglingly high $800 billion in GPU and TPU contracts, the company has shown that most of its compute capacity isn't actually served to customers, and is instead dedicated to R&D for new models, features, and testing. There's a huge amount of information to sink your teeth into here, and despite what many might believe, the company's revenue per compute dollar spent is actually in Anthropic's favor, shattering the myth that tokens cost more in compute than they do for a user.

• Anthropic’s IPO filing shows most of its compute goes to R&D, not serving customers — company details massive $800 billion in TPU and GPU contracts

As neoclouds and hyperscalers (who rent compute out to companies like Anthropic) scale up and scale out, domains become exceedingly important. With copper materials coming up to their natural limits, eyes have turned to the photonic domain to alleviate bandwidth bottlenecks. Now, PsiQuantum has entered the domain, showcasing a prototype photonic switch that loses less light than other devices on the market, and the company expects to develop and mature its solution and is likely to enter the photonic switch market.

• PsiQuantum turns its photonics know-how into an optical switch for supercharging AI data center GPU networks — 8x8 lab prototype loses less light than rivals, with plans to develop larger devices

Cadence has revealed Maestro, a suite of tuned LLM's, designed specifically to work in EDA flows using the company's in-house suite of agentic tools. We've covered the rise of agentic EDA tools closely, and Cadence's Maestro suite appears to be the company's own shot across the bow in helping its customers automate elements of their own chip designs. In initial results compared with general-purpose AI models, Cadence claims up to a 30% improvement in the quality of results and that Maestro effectively uses fewer tokens for the same task, with up to 5x the token efficiency compared to off-the-shelf AI models.

• Cadence reveals Maestro, fine-tuned AI models built to run specialized chip design agents, with early access coming for 'select customers' in Q4 2026 — claims up to 30% higher quality results and up to 5x token efficiency over a general-purpose AI model

But all of those new AI chips have to come from somewhere. With the ongoing, ceaseless AI buildout, firms are looking to secure their supply chains, with Nvidia one of the chief companies among them. As demand continues to soar, the very real limitation of fabs is particularly highlighted in the realm of the substrates used to create PCBs. Ajinomoto Build-up Film, or ABF, is one of the hottest commodities in the chipmaking industry as a result, and Nvidia has announced plans to secure the material from Ibiden, in addition to other critical materials used in chip packaging, testing, and more. Of course, Nvidia isn't doing this out of the goodness of its own heart; it's doing it in exchange for reserved production capacity.

• Nvidia is bankrolling AI accelerator supply chain buildout to reserve production capacity — announces billion-dollar deals with six major suppliers across substrates, advanced packaging, semiconductor testing, and optical engines

The ramifications of AI are still being felt across the globe, but if you've been on social media over the past several weeks, you may have found that there's one particular trend: Decompilation and recompilation of video games, recompiled to work natively on PCs. We detail how additional software tools like Reverse Engineer Anything and Ghidra are powering the boom.

• Why native PC conversions of console games are suddenly everywhere — Reverse Engineer Anything gives AI agents a unified toolkit, and byte-for-byte checks keep hallucinations in line

To read any of the articles we mention above, as well as unlock Bench, you'll need to purchase a Tom's Hardware Premium subscription. Your support goes a long way in helping us to publish deeper, more insightful articles that might not otherwise be covered.

Although the consumer PC market is shrinking and will continue to shrink in the coming quarters, Intel is confident that the overwhelming demand from the AI industry for everything that can compute or store data will offset declines in the client space. To that end, the company is reallocating some of its capacity from client to data center CPUs, expanding its Fab 24 in Ireland to make more Xeons, has begun equipment installation into Fab 62 in Arizona ahead of schedule and vows to make 18A chips there, and is expanding its advanced packaging capacity in New Mexico and Malaysia.

"The industry continues to navigate one of the most significant supply shortages in history, driven by the unprecedented demand for Super Intelligence," said Lip-Bu Tan, chief executive of Intel, during the company's earnings call. "Against this backdrop, I am pleased by the progress we made growing our server supply in Q3. I am mindful about the ongoing challenges we face in the future quarters to keep pace with server demand."

More Intel 3-based Xeons

Intel's manufacturing expansion comes as demand for server processors continues to exceed supply despite substantial production increases over the next several quarters. The company's Data Center and AI (DCAI) business generated $7.3 billion in revenue in the third quarter of 2026, up 17% sequentially and nearly 80% year-over-year. Intel expects demand for data center CPUs to remain strong in 2027 – 2028 as AI infrastructure operators deploy more CPU-intensive agentic and inference workloads.

To meet demand for Xeon CPUs in the coming years, one of Intel's immediate priorities is to increase output of Xeon 6 'Granite Rapids' processors, which are made using its Intel 3 process technology. The company recently began expanding production capacity at its Fab 24 manufacturing complex near Leixlip, Ireland, but this capacity will only come online by the end of 2027, unless the move can be accelerated.

To further increase its Intel 3 capacity, Intel plans to convert some manufacturing resources at its Oregon facilities from Intel 18A to Intel 3. These resources were originally intended to manufacture Panther Lake client processors, but weaker PC demand has allowed Intel to prioritize higher-demand data center products. The company expects the additional Intel 3 capacity in Oregon to enter production in the second half of 2027.

"What we are taking offline to put Intel 3 into Oregon is 18A wafers, which we are generally going to build Panther Lake products," said Dave Zinsner, chief financial officer of Intel. "We see the opportunity with some of that capacity freed up to go produce more data center wafers."

Granite Rapids has already become Intel's fastest ramping server processor family, but demand continues to exceed available supply, according to the company's management. Intel is also improving manufacturing yields and reducing production cycle times to extract more usable processors from its existing capacity. According to the company, Intel 3 manufacturing costs have declined by approximately 15% since the first quarter of 2026.

Prepping for Diamond Rapids, Nova Lake

Intel is also accelerating the expansion of its leading-edge manufacturing operations in Arizona. The company is ramping Intel 18A production at Fab 52 and is accelerating equipment installation into the adjacent Fab 62, which is set to become the company's second high-volume manufacturing facility for 18A, 18A-P, and derivative process technologies.

These investments will support future Intel 18A/18A-P-based products, including server CPUs, although the company has not disclosed the precise allocation of manufacturing capacity between client and data center products at the facility. While the latter is natural, Intel said during the conference call that it expects to win some market share in the client space with its Core Ultra 400-series 'Nova Lake' CPUs, which will require the company to produce these parts in high volumes.

To support its capacity expansion, Intel aggressively procured new tools in the third quarter.

Not only wafers

While expanding production of Intel 3 and Intel 18A/18A-P wafers is a must to increase output of data center CPUs, producing more wafers will not necessarily solve Intel's supply problems. The company also faces shortages of advanced organic substrates required to package its multi-chiplet processors (or rather system-in-packages, or SiPs?) that rely on EMIB and/or Foveros 3D packaging technologies. Intel has been working with substrate suppliers to expand their production capacity and expects approximately 40% additional substrate capacity to become available in the second half of 2027.

"We are not only constrained on the wafer side, we are also constrained on the substrate side," Zinsner said. "So, it is important we get the substrate piece of this ramped up to be able to meet the demand."

In addition, Intel is expanding its advanced packaging operations in New Mexico and Malaysia to support growing demand from internal product groups and external customers. The company already uses its EMIB technology to connect multiple compute dies in Granite Rapids processors, while its newer Clearwater Forest Xeons combine EMIB with Foveros Direct 3D and hybrid bonding to stack Intel 18A compute dies on Intel 3 base dies. Additional packaging capacity will be essential as Intel increases production of these processors and introduces more complex multi-die products as well as assembles advanced system-in-packages using EMIB, EMIB-T, Foveros 3D, and other technologies for external clients.

"On Advanced Packaging, we are pleased by the progress we are making with EMIB and EMIB-T for our internal products," Tan said. "Both continue to see significant external customer traction as well. We continue to improve on execution, working with our supply chain to secure the capacity to meet the needs of our Advanced Packaging customers. We are also seeing robust progress in the readiness of Hybrid Bonding Interconnect (HBI), which is an enabler of 3D chip stacking for our upcoming server products."

Capital needed

Intel's expansions will require substantial capital. Intel expects its capital expenditure (CapEx) budget to reach approximately $20 billion in 2026 and increase significantly in 2027 (though it did not reveal any firm numbers). The company said firm purchase orders to semiconductor equipment suppliers increased by nearly 40% sequentially as it secured tools for its manufacturing expansion. Intel is also evaluating opportunities to accelerate construction of its semiconductor manufacturing complex in Ohio, where the first major structural truss was recently installed.

"We have made good progress securing the equipment required to support our growth plans with firm purchase orders to equipment suppliers increasing nearly 40% sequentially," Zinsner said. "We are also accelerating clean room build-outs, including Fab 62 in Arizona and exploring opportunities to accelerate in Ohio.

Yet Intel's capacity expansion will take time to produce results. New equipment must be installed and qualified, additional wafers must pass through lengthy manufacturing cycles, and substrate suppliers must increase their output (which will likely require them to procure new tools and install them) before Intel can ship more finished processors. Consequently, the company expects supply constraints to remain particularly severe during the first half of 2027, even as the client PC market is set to continue contracting.

Nevertheless, Intel expects its data center business to continue growing and believes that additional manufacturing capacity, higher yields, and improved substrate availability will enable it to capitalize on demand for AI infrastructure in the second half of 2027 and beyond.

Developer Jan de Jager has created a full Intel 486 PC system in a browser. On the e486-web GitHub page, de Jager boasts that the emulator is coded in 100% pure JavaScript. The project’s fuller title is the Retro486 Modular Browser PC. Claude gets a development credit, so we guess you could say e486-web was (partially) vibe-coded.

The live demo you can boot with a single click is impressive, with tabs to interact with and configure your browser-based, dependency-free Intel 80486DX2-66 PC in a browser. The first tab is dubbed the CRT monitor, and this is where you will spend the most time using the command line, apps, and games. However, it is also very appealing to be able to adjust your PC configuration in the tabs for Motherboard & Slots, Storage Bay, Custom Card Studio, and System & Diagnostics.

I couldn’t resist taking the e486-web for a spin using the live demo. The CRT monitor screen is totally charming, with various display options including color and scanlines, and tributes to classic CRTs with green phosphor, amber, or paperwhite displays. This is the screen where you will also type DOS commands and interact with whatever you get to run.

The next tab in this comprehensive 486 PC system emulator lets you pick a motherboard design and, probably more importantly, add and remove expansion cards. The default system comes with a VLB graphics card, Sound Blaster 16 ISA card, a multi-I/O controller, network card, and more. All the cards seem to be configurable. A Custom Card Studio tab lets you create and test more cards, and it looks quite advanced.

I spent quite a lot of time in the Storage Bay tab, switching through the OS and software disks inside the “1-Click bundled & Cached Disks” collection. FreeDOS started fine, but I got some errors when I wanted to test some of the games in the library, which includes Doom, Wolfenstein 3D, and more. Though tempted to find and install Syndicate on the hard disk that the emulator can create and configure, I didn't get around to it yet. However, the Bullfrog classic is one of the first games I played on an actual 486DX2 system in the 1990s, and I also played it on Amiga. This browser-based emulator features browser persistence, so e486-web settings can be maintained between sessions, and it automatically caches ROMs, floppy images, and custom uploaded .img/.iso files for your convenience.

Another tab in this extensive system emulator is called System & Diagnostics. Here you can switch the CPU to a different model, view the CPU registers, and nose around in RAM, VRAM, storage, BIOS, boot sectors, and so on.

Currently e486-web is in version 0.1, and the GitHub shows that most files were uploaded/updated about a week ago. Some files are just two days old, though, so hopefully wrinkles are busily being ironed out by de Jager and Claude. The presentation of this no-downloads live emulator, and the conveniently tabbed interface and configuration options, show lots of promise.

Reverse-engineering games for converting them between systems is currently a hot topic, and it's getting messier by the day. According to multiple user claims, Anthropic's Claude Code and/or Opus 5.5 model are blocking attempts at innocuous reverse-engineering, including but not limited to those using the popular Reverse Engineer Anything (REA) tool. That issue may be linked to a text rule that's now in force, which allegedly instructs the model to avoid "[recreating] a specific existing game."

According to Twitter user Chasm, the game-related textual rule is "Do build original games, games in a genre, and games from the user’s own designs and assets. Don’t build a recreation of a specific existing game, even if it is renamed or called original." There is no official or additional confirmation if this is the actual rule text, but it's plausible enough given the very clear refusals that devs have been encountering over the past week.

This situation is tricky to analyze due to the varying types of reports. First, the existence of a game-related rule is real, as Claude Code's GitHub is seeing an influx of issues complaining about refusals to do standard game work halfway through development, when replicating a game mechanic, and patching a tabletop-like game. It's possible that some of those reports have been made by users with nefarious purposes, but at least one is a bona fide developer with a real track record.

As for reverse engineering, there had already been a smattering of user reports across Reddit and other platforms, wherein Claude refused to perform tasks like (allegedly) analyzing a simple Windows crash dump, clearing up junkware on a Samsung TV, or just using REA altogether.

The simultaneous timing of both game- and cyber-security restrictions may be a coincidence, and yet there are complaints from purported game developers saying that Claude blocked their own games' anti-cheat development and security reviews, under the justification that its safeguards were triggered.

Anthropic introduced its Cyber Verification Program on October 6, essentially saying that access to its frontier models' advanced cybersecurity capabilities would be limited to entities covered by Project Glasswing, taking effect immediately.

It's possible that whichever ruleset was applied is the same one that's causing the cybersecurity-related refusals. Still, it's odd to see that 24 days have passed since then, and yet reports of bot refusal are only coming in since the last week or so.

As for possible motivations behind these restrictions, they are twofold. The first and most obvious one is that Anthropic — and, by extension, other AI players — are preemptively protecting themselves from potential lawsuits from software companies, including game studios, for offering the means to reverse-engineer their software.

There is no official statement on these matters from Anthropic or other AI companies so far. Anthropic isn't the only one playing this game, too, as recently OpenAI deactivated the account of another person trying to clean up their TV's software.

The recent rash of AI-powered clones of application suites like Adobe's suite and Microsoft Office 365, as well as the countless recomps and decomps of console games, likely has most every software company on earth rethinking their life choices. And probably also in frequent contact with their legal teams.

The online reaction was swift, suggesting that users looking to perform reverse-engineering work simply use Chinese, open-weight, or local LLMs instead of Claude or GPT. This, at the same time, highlights the irony of frontier AI companies that copied the world's information and art for their training sets and are now concerned with copyright infringement.

And yet there are situations that merit some discussion, like the recent controversy about the Steam Next Fest being chock-full of AI slop copied from existing titles. That particular situation is getting particularly nasty, as game developers are reportedly being extorted under threat that their game demos will be cloned into complete games before they have a chance to finish and release the original.

Adding insult to injury, this is seemingly being done to small studios whose main priority is usually "having food," rather than big publishers looking to microtransaction everything into a new yacht for shareholders.

Exin Therapeutics, a biotech startup focusing on next-generation neurotherapeutics, claims it has successfully conducted brain surgery on a mouse using an AI agent. Its co-founder and CEO, Gabriel Ocana-Santero, shared the entire procedure on X, showing how the AI agent chose the gene therapy vector and dosage and the brain region where it would be applied. The AI agent also drove the robotic arms that injected the medication into the mouse’s brain. Thankfully, the operation seems to have been a success, with the mouse recovering well and recorded moving around in its enclosure.

“Autonomous surgical robots exist and they are better at the mechanics than our bench rig, [to be honest]. But in every one of them, a human decided what operation to perform, and the robot executed it,” Ocana-Santero said. “Nobody told this agent what to give or where to put it. It got a phenotype and a shelf of candidates and had to work out the therapy and the coordinates itself. I am not aware of an agent previously choosing a treatment and a brain target and then delivering it into a living mammal.”

The team used Anthropic Sonnet, which received a mouse model of epilepsy, control of a motorized surgery rig, and 19 gene therapy vectors in a spreadsheet. Aside from that, it also had access to three research papers, allowing it to choose the brain region where it should apply the treatment. Nevertheless, a licensed veterinarian was purportedly overseeing the entire operation, with every irreversible step requiring approval before the AI agent could proceed. Aside from that, the entire system also had an emergency stop button that would cut the power to every motor in the surgery rig.

The only thing that the vet surgeon on duty did was to do the craniotomy procedure to expose the brain, as the AI agent wasn’t allowed to do that yet for safety reasons. There were also several safeguards that the AI agents were banned from overriding, which even the human operators couldn’t bypass, necessitating a manual fix to the agent’s code during the operation.

What’s interesting, though, is that the startup only used Anthropic’s mid-range Sonnet model for the operation. It initially tried using Opus 5.5, but it immediately refused to do any work after it detected that it was working on a biological experiment. The older Opus 5 model was able to run the entire procedure on paper but refused to do live surgery. “The block isn't the rig and isn't the inputs. It's me. My own output was stopped when I started writing the plan for this surgery... if I try, it gets cut off the same way, and the worst version of that is me cut off partway through a live procedure with a needle somewhere in the brain,” the LLM reportedly told the Exin Therapeutics team. “Starting something I can't finish on an anesthetized animal is worse than not starting.”

Despite the seeming success of the operation, some people are concerned about the ethics of such a procedure. While AI LLMs have been useful in medical research, adding them to sinus surgery has seen malfunctions skyrocket by more than 12 times. Aside from that, relying on an AI to make every decision in such a risky procedure puts accountability in question, especially if something goes wrong. We also haven’t even touched the long-standing ethical question of animal experimentation in the medical setting. Still, some users applauded the experiment, with one comment saying that they’re excited about the possibilities of these integrated technologies, as their son has been suffering from drug-resistant epilepsy for 19 years.

Dave Plummer, former Microsoft engineer and wizard of Task Manager, Windows Pinball, and now TMOG, has an interesting project in his hands once again. After seeing exactly how many zeros were in the price tag for a megabyte of memory for his vintage PDP-11, he decided to take matters into his own hands and conjure up a new RAM board.

The PDP-11 is from 1970, and later models could fit in as much as four megabytes of memory. Plummer enlisted the help of ChatGPT and the EasyEDA online circuit simulator, though he notes that he hadn't done complicated projects like this before. As several PDP-11 models used Q-Bus boards for main system components, he designed this RAM as a standalone card, then tested it on a backplane alongside another board containing the system's M8190 CPU.

Atop it, he placed a Lattice MachXO2 FPGA serving as a memory controller (model 2000HC, if you're wondering), connected to four ISSI 1 MB memory chips. After adding a U2S I/O chip, a bank of DIP switches, comm ports, and sprinkling a handful of capacitors, he had a complete circuit. The M8190 board design has a 22-bit bus and reserves the top 256 KB for I/O and ROM.

However, it wasn't a first-time-lucky project. Plummer encountered a few abortive starts, as he'd never flash-programmed an FPGA chip before. He fixed that after a few attempts, but then he fell into what appears to be a classic PDP-11 trap.

The machine's memory bus design means it can only access entire words (two bytes) at once, and treats the lowest bit in a memory address as a "lane" selector that picks between the low or high byte in the word.

When reading, the CPU will pick out the right byte itself, but Plummer's "memory controller" still needs to return two. Similarly, on writes, the bit selector must be read and then the proper byte selected so that only that will be updated, as the bus lines will still carry an entire word that could otherwise write invalid data.

Plummer seemingly wasn't aware of this before, and one commenter joked that he'd "built 4MB of memory that turned out to be 2MB", to which he replied that the memory "only returns every second word," matching the aforementioned design pattern. Although there are no further updates, since more commenters pointed this out, we assume that he implemented an easy fix in his FPGA code.

One person suggested that he sidestep the entire problem and implement his memory in software via a Raspberry Pi instead, wired directly to the PDP bus. Plummer replied that he'd basically done that already last week with a modern QBone DEC interface board, which in turn contains a Beaglebone Black atop it (similar to a Raspberry Pi).

Just like we suspected, our fellow Australian hardware examiner TrashBench is up to shenanigans again. Not too long ago, after putting a graphics card in the "wrong" place for much better cooling results, he's ... thinking bigger, let's put it that way. He took an old 4-kW outdoor radiator-fan unit from a split air-conditioning setup (sans gas) and hooked it up to a water-cooling loop to assess its performance.

He kicked off the video with his best impression of Crocodile Dundee, and set out to rearrange the unit for the task at hand, as he only needed the actual radiator, fan, and pump. Most of the fiddly guts were taken out, and casters were added for convenience. TrashBench then added a bog-standard reservoir to the main enclosure.

Moving on to the PC side, he converted a T-joint into a Y-joint with judicious application of heat and force, and, being the ever-clever craftsman, designed 3D-printed mounting brackets for the various cold plates. It was around this time that it was made certain he'd be successful, as at 02:49 you can see that his knuckles paid the requisite blood toll to the machine god.

After firing up the entire system, he set to benchmarking, enlisting both a modern RTX 5060 and a hotter, earlier RTX 3080 for the process. The 5060 is a very power-efficient GPU, and its temperature with the standard cooler was a tame 52ºC. However, the mighty power of four kilowatts' worth of cooling brought that down to just 33ºC, around the temperature of lukewarm water, and a 16ºC drop altogether.

With such a wide thermal range to work with, he set out to overclock the living daylights out of the GPU, moving the boost clock needle from 2902 MHz up to 3300 MHz. Despite the 14% clock-speed improvement, average FPS saw a mere 3% uplift, clearly highlighting how perfectly Nvidia has the power/performance curve dialed in since the RTX 2000 series.

He then moved on to the RTX 3080, a beastly, much more power-hungry card that could provide a worthy challenger for the Fujitsu radiator. It was promptly defeated, and its temperature went from 65ºC down to just 28ºC, or in other words, not much above ambient. Overclocking this card, however, also yielded a mere 3% fps, barely worth the man's time.

The final challenge was seeing how well the teeny weeny Fujitsu could handle a combined GPU and CPU load. The processor on hand was probably the worst possible consumer chip to try and keep cool, the lightning-fast and flame-hot Intel Core i9 14900K.

TrashBench hooked it up and saw CPU temperatures drop 18ºC down to 76ºC, a strong achievement for this silicon outside of rooms with liquid nitrogen buckets. As for the graphics card, its heat sensor simply didn't move at all, suggesting that the radiator had far greater headroom than TrashBench had hardware.

A study published on October 22 in the journal Forensic Science International reports that researchers from Curtin University in Perth, Australia, have developed a forensic method to analyze 3D-printed PLA parts and match them to their respective filament, correctly matching 26 out of 28 samples of PLA. This potentially provides a way to link seized 3D-printed “ghost-guns” with other seized filament, allowing police to form a clearer network for the manufacturing and distribution of the 3D-printed firearms.

3D-printed firearms have become a big problem worldwide, as they are untraceable and even compostable in the case of PLA, with tools like this AI 3D-printed gun generator making it scarily accessible. Serial numbers, registration, and a network of licensed distributors are usually the first line of investigation when it comes to crime involving firearms, but easily manufacturable, untraceable, disposable plastic firearms are a new threat with no clear way to crack down on them yet.

However, this research, by Dr. Georgina Sauzier et al. from Curtin University's School of Molecular and Life Sciences, along with forensics experts from ChemCentre, has devised a way to trace a printed object to a specific filament product, down to the brand and type.

The process of 3D printing changes the filament’s physical properties, and this change can be measured. In this research, differential scanning calorimetry (DSC) is used, a thermoanalytical technique that lets the sample go through a range of temperatures, and the instrument measures how heat flows through the sample. It measures how much energy or power is used to keep the sample at a certain temperature or to change its temperature, giving us a graph of its thermal properties.

The sample’s thermal properties can then be cross-referenced with its unprinted filament, creating an association between them. As of now, the tested PLA products are the only successfully identified material, with PETG and ABS not providing enough information to link them to their filament product. Sauzier blames the amorphous nature of those filaments, giving very similar results with no clear identifiers linking them to their respective filament products. PLA has a semi-crystalline molecular structure, which provides clearer temperature transition points under the temperature tests as the crystalline structures break down and rearrange.

However, ABS and PETG did show some promise when tested using ATR-FTIR (Attenuated Total Reflectance-Fourier Transform Infrared), which uses infrared to identify chemical bonds and material composition. The team did find differences in additives using this method, but still did not give enough information to link them back to their respective filament products.

The research is still very early, with more rigorous testing to be done, as the team printed using only one machine, printed small sample tiles cut with scissors, and left them for a year in monitored office conditions before testing. Properties could further change as cooling rates vary greatly depending on what the printer is printing: Faster cooling and slower print speeds on overhangs, or slower cooling and faster print speeds on infill sections. Different printers may also affect the physical properties, adding one more factor in the chain.

So far, correctly identifying 26 out of 28 samples is a great start to cracking down on dangerous, untraceable illegal firearms. When the research matures and can reliably identify a broad range of materials, it could potentially trace 3D-printed firearms to the printer and filament, potentially creating a list of where they were purchased and who purchased them.

A technology enthusiast claims that the oldest GUI application that still runs on Windows 11 is CDPLAYER.EXE from November 1992. The app had to run on Microsoft’s newest consumer OS without modifications or emulation involved to be chosen as the ‘winner’ of their experiment. Blogger Enlyth expected something from the early NT era, as Windows 11 doesn’t support 16-bit apps, despite its strong backward compatibility. Finding an app that is almost 34 years old that still works with a simple double-click is a remarkable result.

At the beginning of their journey to find the oldest Windows UI app that just works on Microsoft’s newest OS, Enlyth confirmed FREECELL.EXE from February 1993 would still run without issues. This game was distributed alongside the Win32s environment, designed to allow some 32-bit applications to run on the 16-bit operating systems like Windows 3.1 and 3.11. Win32s was made available in beta in October 1992, but went mainstream in July 1993.

A tip Enlyth received via a tech forum suggested that FREECELL.EXE was a candidate for the oldest GUI app remaining compatible with Windows 11. However, the blogger wasn’t satisfied with this easy win and dug through “some early NT 3.1 pre-release versions that seemed promising.” Build 347 caught the detective’s eye, specifically CDPLAYER.EXE, linked on Nov 16, 1992. That indeed seems to be the earliest GUI app that works without modification or emulation on Windows 11. But this knowledge almost defied Enlyth’s eye as their system is, like many modern systems, optical-drive-less. Luckily, adding a small DLL (cdemu.dll) allowed Enlyth to emulate a CD drive and demonstrate that the 1992-era application still functions as intended.

I wanted to verify that CDPLAYER.EXE was still usable on the latest Windows 11 release. Unfortunately, the multi-part.ARJ archive of Windows NT 3.1 that I found on Archive.org threw up errors when I tried to pick through its contents. I have a USB-attached optical drive that plays CD audio in Windows 11, so I thought I could get CDPLAYER.EXE to run without any extra DLL.

Lastly, Enlyth wanted to push the envelope a little and see what even more ancient Windows apps might work if they got some help from the Winevdm project on 64-bit Windows. “Using otvdm does feel like cheating,” admitted the digital sleuth, and we’d agree. However, being able to run 16-bit apps in Windows 11 ratcheted back the wheels of time. The result was that Enlyth managed to enjoy “a fully playable version of REVERSI.EXE dated 15-Nov-1985.” That’s a GUI-driven game distributed as part of Windows 1.01 and is roughly 41 years old.

First, it was the GeForce RTX 5090, and now the GeForce RTX 5080 – two of the best graphics cards have gone dark. After the Blackwell flagship left Nvidia's marketplace, the GeForce RTX 5080 followed suit. Prices for the sub-flagship have exploded to more than 2.2X its original $999 MSRP, and the Blackwell-powered graphics card is slowly going out of stock at various U.S. retailers.

As with the recent disappearance of the GeForce RTX 5090 on Nvidia’s marketplace, the listings and filters for the GeForce RTX 5080 have also disappeared. While its absence does not necessarily mean Nvidia has discontinued the graphics card, it does raise questions about its status and future availability. This move is especially fishy because other Blackwell SKUs, such as the GeForce RTX 5070 Ti and GeForce RTX 5070, remain listed on the marketplace, albeit marked as “Out of Stock.”

The continued presence of the GeForce RTX 5070 Ti and GeForce RTX 5070 suggests that Nvidia wants to keep the products visible even when they are not immediately available so that consumers can anticipate restocks. The complete removal of the GeForce RTX 5090 and GeForce RTX 5080 breaks that pattern. It fuels rumors that Nvidia has allegedly stopped production of the GeForce RTX 5090 and possibly the GeForce RTX 5080 too, in favor of a rumored GeForce RTX 5080 24GB.

Rumors claim Nvidia allegedly stopped producing the GeForce RTX 5090 to repurpose the valuable GB202 silicon into the chipmaker’s RTX Pro Blackwell lineup, which fetches higher margins. This has a lot of credence, since many agree that Nvidia stopped being a gaming hardware vendor long ago and has transformed into an AI provider.

Rather than simply discontinuing the GeForce RTX 5090, Nvidia purportedly intends to introduce the GeForce RTX 5080 24GB as the new flagship gaming graphics card. The thing is, a 24GB variant of the GeForce RTX 5080 would solve one of the biggest consumer gripes with the graphics card: the lack of memory. While a GeForce RTX 5080 24GB would offer the same memory as the GeForce RTX 5090, it simply isn't a direct drop-in replacement. The former has 2X fewer CUDA cores, a substantial performance gap that even a 50% memory increase can't make up for.

How much money are you willing to spend during the Black Friday sales?

The GeForce RTX 5080 launched in January of last year with an MSRP of $999. Demand quickly outpaced supply, and with the rapid price hikes due to the memory shortage, the market price has more than doubled its original MSRP. As of this moment, the most affordable GeForce RTX 5080 in stock, the PNY GeForce RTX 5080 ARGB Epic-X RGB OC, retails for $2,199.99, which is 2.2X over the original launch price.

While some stock remains, it’s selling out fast, and the remaining units will only get more expensive as availability dwindles. At this rate, the GeForce RTX 5080 is unlikely to be available by Black Friday. If you are set on a GeForce RTX 5080, you may have little choice but to act quickly and buy at today's elevated prices.

If the GeForce RTX 5080 24GB is indeed legitimate, the graphics card will almost certainly debut at a substantial premium over the original GeForce RTX 5080. Although Nvidia maintains that the RTX 5090 is still alive, the reality suggests otherwise. We have contacted the company for comment regarding the GeForce RTX 5080’s status.

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

Fire sale

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

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

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

Gloomy outlook

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

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

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

What about Apple?

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

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

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

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

This weekend we celebrate all things Warhammer, and although it might be sharing the date with Halloween, fans of the grimdark franchise will be looking towards a different kind of spooky chaos, and things that materialize from the warp. Warhammer Day 2026 takes place this October 31st, and this is a good time to grab a deal or pick up a gift for yourself to adorn your desktop setup. Maybe even pick up the latest Warhammer 40K-inspired PC games to really jump into the fray.

We've compiled a list of some of the best Warhammer 40K furniture, collectables, and PC games, ahead of the celebrations.

Warhammer 40K Furniture

Secretlab has a range of officially licensed Warhammer 40K furniture that includes both desks and chairs. The chairs are fully decorated with the chapter livery and standards, with skins available to convert existing chairs to the same designs. The desks are just the standard Magnus Pro desks but include a 40K-themed MAGPAD that can also be bought separately if you already own the desk.

Warhammer 40K Peripherals and Collectables

If you're looking for some collectables or ornaments to decorate your gaming setup and add a Warhammer 40K theme this Warhammer Day, then we also have some ideas that include mouse pads, keycaps, Nurgle plushies, a Death Korps rucksack, and some Space Marine figures for decoration.

Warhammer 40K Games

When you're not painting your miniatures or indulging in some tabletop action, relax with some of the best Warhammer 40K games. Bring the grimdark future straight to your gaming PC and satiate the Omnissiah with these great titles. Combat the hive mind as a Space Marine, or jump on board the upcoming Dawn of War IV RTS and command the Space Marines, Orks, Necrons, and the Adeptus Mechanicus.

OpenAI CEO Sam Altman has data centers full of memory, but seemingly it's the 32GB of RAM in your desktop that's the problem. In an interview over beers with the YouTube channel Cheeky Pint, Altman said that local inference, and, by extension, people having DRAM in computers at home, is "quite terrible."

When discussing local inference on home computers with open-source models, Altman discussed the assumption that people will be able to run local AI on their own computers, the ones they may already own or want to build. Then he explained why that's a bad idea (at the 29-minute mark):

"From a global allocation perspective, actually, it's quite terrible to have everybody have a bunch of the world's limited supply of DRAM sitting in their own computer and being used 5% of the time," Altman said. "You want maximum utilization in the cloud if you're trying to deal with this very supply-constrained environment. And somehow many people's intuition is the opposite of that."

While OpenAI does have some open-source models, its primary business is in closed-source models that run in data centers, so he's really defending the company's business model.

OpenAI isn't exactly threatened by some laptops and gaming rigs just yet, but local AI could mean people one day paying less for subscriptions to models like GPT-6 Luna if they have the power to run them at home. Altman's talk suggests that the company would prefer that more RAM go to OpenAI's data centers rather than home computers, which also sparks enthusiast fears of not being able to own your own hardware or software, but rather rent an agent and a computer in the cloud.

Some of what Altman is saying is based on an idea that data center buildouts won't slow down. It also assumes that RAM being used in AI data centers 24/7 is more worthwhile than RAM that is used for spreadsheets, web browsing, gaming, and maybe even local AI occasionally.

The rest of the wide-ranging interview includes talk of this week's PHP vulnerabilities, sandboxing models in training, and OpenAI's research in mathematics.