• Those buying an RTX 5090 at Micro Center now have to fill out a declaration form
• This includes having a government-issued photo ID scanned by the retailer
• Some approve of the policy as it's an anti-scalping measure, but others view it as an annoyance or a pointless move

If you're buying an Nvidia RTX 5090, or a PC with the graphics card inside, over in the US, you may have to fill out an official form to declare that you don't intend to export and resell the GPU – or at least you will at Micro Center.

PC Gamer spotted the 'advanced computing product purchaser declaration' which a Redditor was forced to complete and sign – including a scan of their driving license for ID – when buying a PowerSpec AI90 workstation PC with an RTX 5090.

The Micro Center store was in Tustin, California, but someone else posting on the Reddit thread claims that the same form has been introduced at the Columbus, Ohio store.

Apparently this is a new policy that only started this week at Micro Center (but seemingly other retailers already follow this practice in the US, including Central Computers).

In case you hadn't guessed, this move is about trying to prevent scalpers from buying up the RTX 5090, or PCs containing it – which can be around the same price as the standalone GPU these days, and are sometimes the only way of getting this graphics card at all – in order to sell it on to China and turn a profit.

Analysis: a pain in the neck, or a valid anti-scalper tactic?

As some of the commenters on Reddit are quick to point out, this form isn't legally binding, and there are question marks over how any of this might be enforced. Somebody breaking the terms of the agreement is likely to just shrug their shoulders about the consequences, perhaps.

However, as PC Gamer notes, the use of the ID check is certainly a deterrent of sorts for GPU exporters. And what this is doing is preventing people who are making a short trip to the US buying an RTX 5090 and selling it on when they get back home for a hefty mark-up. Those people won't be able to provide a US address and government photo ID that can be verified as belonging to them, of course.

The fact remains that it's a bit of a pain for Micro Center's customers to have to go through this form filling and ID check, although that said, some of the folks on the above Reddit thread don't have a problem with the process given that it's an anti-scalping measure. Others are concerned about having to give a retail store personal information for an unnecessary reason as they see it, or they're just annoyed and think it's a waste of time. As one Redditor put it: "This is ridiculous."

Going by the Reddit thread, another measure Micro Center enforces is that there's only one purchase of an RTX 5090 GPU per customer full-stop, forever. Once you've bought one, you can never buy another, we're told.

• Borderless Gaming is a tool that's sold on Steam
• It just got an add-on to easily fudge DLSS 5 to work with various PC games
• Reviews of the tool have turned rather colorful, as those who still hate DLSS 5 and all it stands for are chipping in

You can't have missed all the chatter about experimenting with Nvidia's DLSS 5 in all sorts of different PC games, and if you've felt the urge to join in but have been too intimidated by the idea of fudging the tech to work, a solution is now at hand.

VideoCardz noticed that Borderless Gaming, a tool that's sold via Steam – it's used to facilitate gaming in a borderless window, as the name indicates – now has DLSS 5 support. Or, as the developer put it: "DLSS 5 Neural Rendering for Everyone."

The dev notes that: "DLSS 5 Neural Rendering is now available in Borderless Gaming – without replacing game DLLs, modifying game files, or needing a game-specific mod. Install the effect, select the preset, and apply it to your game."

Borderless Gaming applies DLSS 5 directly through its own BGFX pipeline, the developer explains, rather than forwarding requests to Nvidia's DLLs.

In short, this is DLSS 5 being fudged in about as no-fuss a manner as can be, save for the fact that you have to buy and install the app, of course. This implementation shouldn't be confused with native DLSS 5 support, because it's simply a workaround to bring the neural rendering technique into play (with variable results as you might expect).

Note that the Borderless Gaming app doesn't actually come with this built-in, but after installing the tool itself, you need to also download the appropriate effect (DLSS5-NR v0.2.1 currently) from GitHub here (installation instructions are provided at that link).

Analysis: catching some of the DLSS 5 hate

According to the developer, this implementation can work on a wide range of GPUs – not just the officially supported RTX 5000 models – and an RTX 3090 can hit around 30fps typically with DLSS 5 turned on. Obviously the frame rate will vary massively depending on the game and graphics settings, but the gist is that you can get something playable on the RTX 3090.

It's a neat enough solution by the looks of it, although as ever, if you're curious, I have to issue my usual warning about third-party apps here: download and use them at your own risk.

Borderless Gaming is an app that's been around for a long time, but the Steam reviews have turned distinctly colorful of late – with some of that color revolving around this latest move with DLSS 5. As one reviewer puts it: "Added DLSS 5 for no reason but to make games look worse... Slop." (Hence the above clarification that DLSS 5 isn't actually added to the app itself at all).

Nvidia's DLSS 5 was controversial when it was first announced, although the reception to its neural rendering trickery has warmed up considerably since it went live in a game (NBA 2K27). There are still haters out there, though, as the Steam reviews for Borderless Gaming illustrate.

It's also a fair question whether Nvidia might take action against projects like this, which are going further in terms of tweaking and playing about with DLSS 5 tech. It's likely that for now, with DLSS 5 getting a greater level of positivity from many of the gaming experimenters out there, Team Green might let it slide – at least for the time being.

• Discord is working on a new 'Game Mode' feature to reduce CPU and GPU usage while gaming
• The new feature seems to be an auto-toggle of the Reduced Motion feature on the desktop app when a game is running
• It's not yet clear if any improvements will be made to resource consumption while screen sharing

Discord is infamous for its high RAM, CPU, and GPU consumption while gaming, and some of those aspects are finally being addressed.

As reported by VideoCardz, Discord is working on 'Game Mode,' a new feature for the Discord client that frees up CPU and GPU resources while a game is running by disabling effects and animations for smoother gameplay.

Discord already offers options to reduce system resource use, notably Reduced Motion, which reduces the intensity of animations and hover effects when navigating the client. Users can also disable hardware acceleration, which stops the app from using the GPU for better performance within it, and disabling it should stop "visual glitches like frame drops in games or performance problems".

Game Mode sounds a lot like Reduced Motion, with DiscordPreviews (on X) describing how it reduces animations and effects automatically once a game is detected. With this in mind, Game Mode might not be the best answer to solving Discord's system resource issues, especially since there's no mention of RAM usage reduction.

It's also worth noting that Discord is an Electron-based application (a framework for desktop applications that uses web technology), which means Discord's web app is essentially running in an embedded browser engine known as Chromium — the same engine Google Chrome is built on, which is another app that is heavy on system resources.

What about screen sharing?

It's unclear if Game Mode will do anything new other than serve as an automatic toggle for Reduced Motion while gaming. In that case, Discord still has a long way to go in ensuring the desktop app doesn't continue to creep up as a system resource issue for gamers.

At the very least, having Discord devs address the issues is a great start, but it remains to be seen if Game Mode will also help with keeping CPU and GPU usage as low as possible while screen sharing.

Unsurprisingly, the latter uses high amounts of system resources, especially when streaming at higher resolutions, but it's more reasonable compared to simple voice chat or the app being open in the background and still hogging memory.

Still, in-game frame rates can suffer when using screen share, even if the resolution is below 1080p, and this is far more problematic on lower-end systems with less RAM. Solutions such as a capture card on a separate system (or specifically a laptop) can help solve game performance problems completely, but it's not exactly an affordable option.

If Discord can optimize the desktop app or move away from its Electron-based nature, it could go a long way toward removing all of the major pain points.

Normally we get to this time of year and the typical advice is to hold fire on any potential tech purchases. This is because Black Friday is just a couple of months away, and so it always seems prudent to think about being patient, and the bargain you might just secure in the biggest tech sale of the year.

Not this year, though, when it comes to GPUs – at least in my opinion.

During Black Friday 2025, we did see some decent deals on graphics cards. Not many, mind, but there was a scattering of them. I've noticed on Reddit that there are some gamers who have found a GPU with a decent price tag, but they're wondering whether to hold off and wait for something better on Black Friday. They are perhaps remembering some of the discounts that happened last year (thin on the ground as they were).

For example, this US-based Redditor asks: "Buy an open box [Nvidia RTX] 5070 now or wait until Black Friday?" They add: "I see a few open box deals for $745. What do people think about snagging this now at such an inflated price, or waiting until Black Friday to try and snag under $700?"

If you're in a similar quandary, my advice is this: absolutely do not wait for Black Friday. Just buy that graphics card now.

Let's break down the reasons why this isn't a 'waiters' market (by which I mean those biding their time, not the lovely people who serve us food and drinks).

Reasons to be fearful

For starters, as a legion of cynical Redditors are quick to point out, Black Friday isn't the best for graphics card deals anyway – it has never been the strongest suit for this sale in terms of PC components.

As noted, there have been bargains in the past though. Despite those Redditors who insist that GPUs just have their prices quietly upped in October so they can be artificially 'discounted' for Black Friday, there are actually some genuinely decent deals – or there have been.

However, things have just gone crazy this year, and as the second half of 2026 has rolled around, the RAM crisis has reached another tiring peak of frenzied hiking.

There were more rumors of imminent GPU hikes just a couple of weeks ago (following last month's negative chatter), and at retailers in the US we've already seen graphics card prices rising considerably over the past month. Compounding this are even more negative predictions about the memory shortage in general – which inevitably affects video RAM as well as system memory – and DDR5 prices which are spiking in a ridiculous manner right now. So you've got a recipe for a tumultuous rest of the year.

In short, I can't see 2026 panning out any other way than seeing more GPU price increases – so why wouldn't you buy now? At least from the perspective of whether Black Friday might somehow bring some bargains around – it surely won't.

I'm pretty convinced of that, and there are nuances here in terms of what kind of graphics card you're looking to buy. I'm talking about mainstream GPUs, the mid-range or lower tiers of the market, and not the higher-end graphics cards.

The beefiest GPUs like Nvidia's RTX 5080 (don't even mention the RTX 5090) are already exceptionally pricey, and while I don't think they'll get any cheaper – and indeed I reckon they'll probably still creep up in price – the cost of those products is already a very bitter pill to swallow.

I don't blame you if you don't want to pay out that much cash for a graphics card, because over $1,500 for an RTX 5080 (in the US) is a pricing nightmare. But you'll have to accept that you'll likely be in for a long wait for better prices, maybe not until 2028. A compromise might be to buy a card like an RTX 5070 to tide you over, or maybe an AMD RX 9070 XT (it's a touch less expensive in the US at the time of writing), then sell that second-hand later on when the RTX 5080 comes down.

The trouble is, there are no good options here... not for the pricier GPUs anyway.

Red Friday

I think that this year, Black Friday should be renamed Red Friday for its Herring-like nature, at least when it comes to graphics cards. Don't be swayed by the temptation of waiting for a deal, and if you see a reasonable price on the GPU you're considering, grab it now.

A $750 (open box) deal on an RTX 5070, the dilemma of the aforementioned Redditor, seems a sound enough proposition, even though that's a depressing reality considering this GPU was still going for around $650 just two months ago – because you're now looking at $850 or so (going by Newegg US pricing).

You can pick up an RTX 5060 Ti 8GB for only 10% more than this GPU was priced at in June (again, going by Newegg US), and I think there's an even stronger case to snag something like this if you're looking at the more affordable end of the market.

Obviously, do your own research based on the regional pricing for the GPU you're thinking about, but whatever the case, I'd still urge you not to be fooled into waiting for Black Friday, as I really think that'd be a mistake.

• Alibaba's T-Head unveiled the Zhenwu V900 with 216GB of memory, 1.2TB/s links, and a claimed 3x gain over the already-shipping M890
• Very few details associated with its raw performance: Alibaba gave no FLOPS, node, foundry, or power figures, and both specs it did share project it will trail Huawei's Ascend 960DT, which releases in the same quarter
• CEO Eddie Wu targeted more than 20GW of Alibaba Cloud-operated capacity by 2032 while admitting supply-chain shortages are limiting growth for the company

Alibaba opened its annual Apsara Conference in Hangzhou with three big numbers: a chip that it says triples the performance of its predecessor, AI clusters that could stretch to 500,000 of those chips, and a pledge, quoted by the South China Morning Post, that the data centers Alibaba Cloud operates worldwide will pass 20 gigawatts of capacity by 2032.

CEO Eddie Wu called the new Zhenwu V900, designed by the group's T-Head chip unit, the "most powerful AI chip in China today."

This was part of an address that distinguished Alibaba's offering as a GPU rather than an ASIC, landing it squarely in Nvidia's territory even as the latter's H200 GPU is highly sought after by AI labs.

A powerful offering on paper, but one that doesn't publish actual performance

The Zhenwu V900's spec sheet might be intentionally short, even as its performance figures versus comparable current-generation Nvidia GPUs, a banned option, could limit interest ahead of launch.

Alibaba has, however, added an impressive amount of memory and interconnect, allowing it to cluster a configuration it claims can run as many as 500,000 GPUs in parallel.

The V900, as per Zhidx, reporting on the launch, lists 216GB of memory and 1,200GB/s of chip-to-chip bandwidth and was originally expected to be available to clients in Q3 2027 before the recent revision pushed it two quarters earlier.

T-Head vice president Gao Hui now says the company will, going forward, keep a one-generation-per-year cadence, with a J900 due in the third quarter of 2028.

Despite the closer timeline, it is interesting that Alibaba has published no FLOPS figure, process node, foundry, power rating, or even the V900's internal memory bandwidth, making it hard to gauge its most powerful single-chip offering in terms of raw AI and compute performance.

This is particularly ironic at a time when the competition from Huawei, the Ascend 960DT, which was launched the same quarter after being pulled earlier by three quarters, is offering far more detail.

It lists 2 petaFLOPS of FP8 compute, 288GB of memory, 9.6TB/s of memory bandwidth, and a 2.2TB/s interconnect, making it a higher-VRAM and higher-interconnect offering based on the information Alibaba has already published.

The 500,000-card figure interestingly may just be a scaling limitation, not a system anyone has built. For scale, T-Head said in May 2026 that it had shipped just over 560,000 Zhenwu chips in total. One maxed-out V900 cluster, in other words, would need nearly as many chips as the company had shipped in its entire history.

It does, however, bring a secondary calculation into the equation: if each V900 drew what Nvidia rates its H200 at, up to 700W, the accelerators alone in such a cluster would pull a significant amount of power. A newer, larger chip could run hotter and be more power-hungry than Nvidia's Hopper offerings, even as China remains limited to older process nodes because of US sanctions on chips and chipmaking equipment.

A large cluster of 500,000 or similar GPUs would undoubtedly rack up power requirements considerably fast for the regional AI juggernaut, and 20GW by 2032 is not an unforeseeable event when one considers that per-GPU power draw is only heading up for the foreseeable future as the chips get faster, denser, and more monolithic at the same time.

Wu said medium- to long-term demand far exceeds what Alibaba can supply, and that shortages across the AI data center supply chain "are currently limiting the speed at which we can scale our compute infrastructure." The target covers capacity Alibaba Cloud operates, and the company did not say whether it means IT load or total facility power.

A Nomura note relayed by Sina puts Alibaba's current footprint at roughly 4GW and expects future buildouts to blend owned, leased, and third-party-financed sites, implying about fivefold growth in six years.

Whether the upcoming V900 displaces Nvidia's global market dominance, even slightly, is unclear, with Team Green already far ahead in a market where AI customers buy GPUs years in advance. The situation, however, is vastly different in Beijing.

In China, much of the disruption has already happened, with Chinese AI labs being 'persuaded' to stay away from Nvidia solutions by the state. Nvidia's latest 10-Q says shipments of data center Hopper products to China were under 1% of its $89 billion in data center revenue for the quarter to July 26, and the company said in its earnings report that objections in Beijing kept it from selling the full volume of H200s that Washington had licensed when relations briefly thawed.

Chinese labs have turned to a mix of homegrown solutions, including specific ASICs, GPUs, and CPUs, allowing local players such as Alibaba, Huawei, and others to thrive in a market devoid of foreign competition.

With the US government restricting Nvidia's power limits and the Chinese state taking a dim view of local labs depending on foreign chips, Alibaba's V900 GPU doesn't need to beat Nvidia's Rubin GPUs or even its Blackwell offerings. It simply needs to take on and provide a viable alternative to a GPU that is two generations older: the H200 (based on Nvidia's Hopper architecture).

Its bigger challenges will be Huawei's locally produced Ascend 960DT and similarly configured chips from upcoming local chip design firms, as well as supply chain limitations that could restrict overall production and, by proxy, deployment for a company looking to spend billions on AI infrastructure in the coming days even if its "most powerful" status, which is currently consigned to a claim holds at the time of its release.

• Nvidia Smooth Motion has been modded onto RTX 3000 series GPUs
• The experimental mod allows driver-level frame generation in unsupported games
• Nvidia hasn't officially implemented this and other features on older RTX hardware yet

Modders continue to find new ways to implement Nvidia's latest technologies on older hardware, and now it's been done with Team Green's driver-level frame generation.

As reported by Wccftech, Nvidia Smooth Motion has been unofficially made to work on RTX 3000 series GPUs, with a new NVSmooth30 mod available on GitHub, confirmed to work on an RTX 3050 laptop and an RTX 3080 desktop GPU.

Nvidia's Smooth Motion functionality is essentially identical to AMD's Fluid Motion Frames, meaning that it enables frame generation in games that don't have official support for it — a tool that is most useful for older games or games running in emulators.

The mod works by modifying Nvidia's driver-level frame generation DLL (Dynamic Link Library) file, labeled NvPresent64, bypassing the usual compatibility checks that would stop it from working on Ampere GPU hardware, aka RTX 3000 series GPUs. It also works by "conservative metadata retargeting" from Ada Lovelace (RTX 4000 series) and targets Ampere instead.

The creator says that all users need to do is place the DLL file into the relevant game's folder and use the Nvidia Profile Inspector app to enable Smooth Motion. The process is very simple, but this is an experimental project, so it runs the risk of game bugs and crashes, or potentially other issues — and must not be used in online games using anti-cheat (doing so could result in a ban).

Gamers want new features, but new GPUs are unaffordable

Nvidia has been quite impressive with its latest technologies, notably with DLSS 5 Neural Rendering (which I saw at Gamescom 2026), and Smooth Motion has been one of many over the last few years.

The GPU market is in complete disarray due to the RAM crisis, which means prices for GPUs for both AMD Radeon and Nvidia GeForce GPUs are way too high for most people to consider an upgrade. Features like Multi-Frame Generation, Dynamic Frame Generation, and Smooth Motion are those that PC users would love, but can't use on older hardware.

Modders have consistently proved that these features can be backported in some way, with some even going as far as porting DLSS 5 onto the RTX 4080 (despite the performance hit).

DLSS 5 Neural Rendering coming to older hardware in the immediate future is unrealistic — but Nvidia has previously told me that it does plan on adding backwards compatibility at some point, though it's likely to come to 4000-series models first, and then we'll have to hope for 3000-series later in the future, if it's even possible.

But it feels as though features such as Frame Generation, and specifically Smooth Motion, deserve backporting attention now more than ever, as users are stuck with older GPUs.

Doing so would put Team Green in the good books of many PC gamers, and keep players from relying on unofficial mods to achieve better performance and enjoy GeForce hardware to the fullest extent.

I can't stress enough that Control Resonant is an absolute marvel in terms of visual enjoyment. Remedy Entertainment has crafted one of the most immersive visual experiences in gaming, doubling down on its predecessor's trippy, psychedelic, and mind-bending nature, and taking it to a new level using Nvidia's path tracing.

Putting my Nvidia GeForce RTX 4080 Super to the test, I ran Control Resonant on LG's 39-inch 5K2K OLED monitor, and I was pleasantly surprised by the significant enhancement to every detail on screen (albeit it did leave my GPU rather toasty).

At a 5120 x 2160 display resolution which is a 21:9 aspect ratio, you're getting 33% more pixels than a regular 4K gaming monitor at a 16:9 ratio, so the demand on the GPU is harder than most can handle — and even though Control Resonant was cooking my GPU, the frame rate was quite surprising.

With DLSS 4.5 Quality and Frame Generation enabled, and the high graphics and high ray tracing presets, performance remained fairly consistent within the high 50fps to low 60fps range. At 5K2K resolution, that's very reasonable, even if Control Resonant relies on Frame Generation to keep the gameplay smooth.

Dropping DLSS down to Performance mode pushed the frame rate to the high 80fps mark, and it's worth noting that it remained consistent even in moments of intense combat with tons of foliage and objects involved.

It's worth noting that the graphics with standard ray tracing are still fantastic, and the high (or even the medium) preset is likely the best route for any PC gamer who is using a low- to mid-range GPU (with Frame Generation). Lighting in all areas, specifically those where the Hiss is present (the really bright red zones), is phenomenal, and frankly, that applies to the experience without any ray tracing at all.

Path to victory

However, the star of the show is path tracing, which can be enabled by switching to the ultra ray tracing preset. I instantly knew my GPU was in for a rough ride once its temperature shot up to nearly 80C — but that's to be expected when running path tracing on a 5K2K display.

With DLSS Performance and Frame Generation enabled, I was able to achieve a solid 60fps in most scenarios, with occasional dips into the high 50s during traversal and combat. This aligns well with Remedy's system requirements for Control Resonant, which require an RTX 5080 for 60fps at 2160p using DLSS Performance, as the RTX 4080 Super is relatively close to this current-gen GPU for performance.

Realistically, this setup is out of the question for most gamers, as it will cost around $3,000 / £3,000 (or potentially more). LG's display is very expensive, sitting at $1,799.99 / £1,499 (on sale I should note), but an Alienware AW3926QW 5K2K alternative might help lower the cost.

The RTX 4000 series is discontinued, but pricing for anything equivalent to the RTX 4080 Super in the current-gen line-up (an RTX 5070 Ti or RTX 5080) would cost at least $800 (much more for the latter GPU), and then you need to add the cost of the other PC parts.

Handheld gaming PCs are still expensive, but more reasonable than an entire new PC build — and I tested Control Resonant on my Lenovo Legion Go S Z1 Extreme. That portable managed a solid 40fps on its handheld preset, and 70fps when dropping the resolution to 900p and enabling FSR Balanced with frame gen.

Overall, running Control Resonant at 5K2K is very demanding for any gaming PC, as expected, but I walk away shocked that it's even remotely possible given how much it elevates the gaming experience.

• XMG has announced price rises for its laptops due to the increased cost of components
• The laptop maker points out that DDR5 RAM for laptops is now close to 6x the price it was before the memory crisis
• We're also hearing that Micron has pulled the plug on its 2GB modules of GDDR7, and Nvidia's supply of VRAM could feel an impact from this

The RAM crisis sadly keeps rolling on and finding fresh pricing misery to heap on us, and that includes new laptop hikes and a hint that Nvidia GPUs could be in yet another spot of bother.

VideoCardz spotted the development with laptops, as manufacturer XMG announced on Reddit that its notebooks are subject to price hikes of either €100 or €150 for most models, or €300 in one case (that's for a Schenker portable, which is XMG's parent company, so it's all under the same umbrella).

Some laptop upgrades have got pricier, too, with a €120 premium on an RTX 5090 configuration, and as XMG observed: "The reason [for the price rises] is another increase in purchasing costs. This is no longer just about RAM and SSDs: PCBs, electronic components, CPUs, graphics cards and video memory are also contributing to the higher cost level."

In other words, everything is subject to price inflation, including the motherboard and associated chips, as well as the mentioned key components.

XMG highlighted data drawn from Geizhals (which tracks German retail prices) showing that DDR5 RAM for laptops is close to 6x the price it was before the memory shortage began (in mid-2025).

The laptop maker also made it clear that discrete GPUs and GDDR7 video memory have become more expensive, as have the prices of AMD and Intel laptop processors.

Also on the subject of GPUs, Wccftech reports that another slight worry is that Micron is no longer making 2GB modules of GDDR7 video RAM which are used in some Nvidia RTX 5000 GPUs.

Uniko's Hardware flagged up this news in a post on X, noting that these chips have "reached end of life" and that this is the case for all Micron 2GB modules, with only 3GB GDDR7 chips now listed on the memory maker's website.

With Micron apparently no longer supplying Nvidia with those 2GB modules, that means more of a squeeze on the availability of video memory for RTX 5000 graphics cards, at least in theory. This could hit stock levels and put a bit more pressure on pricing (which is already climbing fast).

Analysis: yet more pressure

We need to season the claims around Micron here, as this isn't a definitive statement from the company itself, and more to the point, it's only a minor supplier for Nvidia's gaming GPUs. Team Green gets the majority of its GDDR7 from Samsung and SK Hynix, and so the impact here should be relatively slight.

However, I'd argue that any impact is bad news given the current climate which is rapidly worsening for GPUs, particularly those from Nvidia which are heading upwards at a rate of knots for some models. The RTX 5090 has got completely ridiculous, the RTX 5080 is similarly out of hand, and even the RTX 5070 is now feeling the pricing heat, with a 30% price rise compared to two months ago in the US (and a similar picture elsewhere).

So, even small extra pressures are really not going to help Nvidia's GeForce GPUs here.

As for the laptop price hikes, this is a sign of the RAM supply times, and XMG is following other makers who have had to jack up prices (like Dell for example, which just bumped up the XPS 13 in a roundabout way).

It's a commendable level of transparency from XMG here, with the company making it clear that it isn't turning any extra profit from these laptop price increases. XMG also observed that other factors are in play with increased costs for notebook makers, and that includes rising air freight costs (due to conflicts in the Middle East) and difficulties with shipping by sea, too.

Financial crime has never stood still. In my nearly three decades in financial services, I have watched fraud move in lockstep with the technology built to stop it, and at times, even stay a step ahead of it​,​ given the speed fraudsters adopt new technology.

I have witnessed decades of AI innovation ​that raised​ the bar on fraud detection, yet criminals continue to test those boundaries. Fraud remains a top consumer concern, with over ​87.5 million American adults experiencing a scam or financial fraud each year. That’s roughly one in every three American adults.

The question for financial institutions isn't whether AI has a place in fraud prevention​,​ but whether the AI they've deployed is built for the threat landscape they're facing today – and the one that's coming.

Compute has finally caught up with mathematical vision

For decades, data scientists working on fraud prevention had theories they couldn't implement. The ideas were sound, but the computers at the time weren't powerful enough to get the math done. That constraint no longer exists.

Historically, most fraud detection has been carried out by building a profile summarizing a customer's typical behavior using sophisticated features, a neural network, and the customer’s current transaction to flag transactions that are suspicious. It's an approach constrained by the computational limitations of time.

Today, access to GPU and other high-performance compute is changing the art of the possible. Rather than analyzing a transaction in the context of a profile, GPUs allow us to implement entirely new algorithms that can evaluate a customer's extensive transaction history in real-time as the transaction happens.

The result is a significantly sharper, more accurate prediction and far fewer false alarms that can delay or stop legitimate purchases​,​ eroding customer trust.

Built for one job, not every job

Thanks to greater GPU availability and computational power, we're now seeing new opportunities to support fraud prevention with a sequence-modeling transformer – not a generic transformer, but one purpose-built for transaction analytics and financial crime.

With a purpose-built transformer architecture that’s trained exclusively on financial transaction data and engineered for a single focused task, financial services institutions can detect financial crime in real time using deep personalization and the context of the customer transaction history.

These are not overarching ‘do everything’ models. They are focused foundation models purpose-built to deliver auditable, high-performing, low-latency generative AI for the fight against financial crime. Each of these models specializes in distinct areas, such as account takeover, scams, mule detection, and first-party misuse.

Independent models focused on their specialty allow for a more complete, accurate, and transparent picture than any single model working alone. And this is just the start​,​ as the same methodology applies to risk decisions, hardship, collections, and any application where understanding our customers leads to better engagement, protection, and service.

The future is now

The fraud prevention capabilities that will define the next five years are being built right now. Enterprises investing in protecting customers from fraud – both now and in the future – understand that purpose-built models, use of specialized compute, and AI agents are the path to protecting their customers.

The math protecting consumers today was invented decades ago by AI scientists who saw the potential in algorithms even before the compute and infrastructure existed. I've spent much of my career continually chasing that goal to ensure that the industry is ready to bring the best algorithms when compute shows up.

Some of my proudest work came from refusing to settle and trust that technology will catch up with AI invention and math. Every patent, every model, every AI experiment has served the same purpose: making sure the industry is ready to lead with the best AI tools once compute catches up with scientific invention.

That work is happening right now. The only question is whether ​​​​​​financial institutions are​​ part of it or racing to catch up.

We've featured the best antivirus software.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

• Apparently Nvidia's not launching RTX 6000 GPUs until 2028
• A leaker claims that these graphics cards have been delayed from the 2027 debut Nvidia originally planned
• Pushing back these GPUs makes sense given the RAM crisis, and some gamers are happy to wait anyway

Nvidia has pushed back its timeframe for launching next-generation graphics cards for gamers, and we're now hearing they won't arrive until 2028.

As ever, all this is theoretical – Nvidia hasn't uttered a peep about its RTX 6000 GPUs officially – but according to Kopite7kimi, a well-known leaker on X (via TweakTown), these products are now destined for a 2028 release which "means they have postponed again."

In other words, Nvidia was supposedly looking at a launch for next year, but the leaker now believes that isn't the case.

Another leaker, Moore's Law is Dead on YouTube, recently said that Nvidia is planning a 2027 launch for the RTX 6000 series, so this directly contradicts that idea. However, it's possible that this was the case, but Team Green has only just changed its mind.

Analysis: a sensible move

Of course, both of these assertions are just rumors, and we need to regard them with an equal amount of caution – but I think it makes more sense for Nvidia to delay the release of its next-gen GeForce GPUs until 2028.

Why? I have three predictable words for you: the RAM crisis. With the memory shortage – which also impacts video RAM – rapidly worsening as 2026 progresses, and predicted to descend further into nightmarish pricing territory in 2027, next year seems like a bad move for launching a family of next-gen GPUs.

Especially when you consider that the first graphics cards to emerge will doubtless be the flagship RTX 6090 and the 6080. How expensive will they be in such a climate, given that the RTX 5080 is already exorbitantly priced? The latter has reached around $1,500 in the US at this point, and is at similar levels in other regions, such as £1,350 in the UK (that's the cheapest GPU in both cases at the time of writing, I should make clear). And let's not even talk about the RTX 5090 which has got completely ridiculous.

Remember that these next-gen GPUs are going to require more memory to be an upgrade over their predecessors, and are also likely to use more expensive VRAM modules.

3GB modules will likely be used by Nvidia, or maybe even 4GB or 6GB chips, which as Wccftech reports, are rumored to debut in the next year or two (which would align with a 2028 release for RTX 6000, in theory). That's according to another prominent leaker over in Asia, Golden Pig Upgrade, as posted on Weibo.

All expectations are for the RTX 6000 series to be pricey, which is why launching them at what might be the height of the RAM crisis – 2027, going by current predictions – doesn't make a whole lot of sense. The following year seems a lot more likely, when hopefully the crisis has started to settle down and pricing is at least stabilizing to some extent (although some believe we're looking longer term for that to happen, more towards 2030).

Whatever the case, some gamers are getting jaded with the market. One of the replies to Kopite7kimi's post on X simply says of the next generation of Nvidia GeForce GPUs: "Nobody cares, nobody can afford it anyway." Others – like this Redditor, who says "I'd rather they delayed the launch to consumers" – indicate that they're happy enough to wait due to pricing or stock issues (launch quantities of GPUs would likely be thin on the ground).

The other question is whether we'll see those RTX 5000 Super refreshes that have been long rumored. I'm doubtful at this point, and I think Nvidia may be inclined to rely more on the AI and software side of the equation, principally DLSS 5, to impress gamers, rather than new (stupidly pricey) hardware.

• AWS deal with Nvidia adds 2 million Blackwell Ultra, Rubin, and Rubin Ultra GPUs, on top of more than 1 million committed in March 2026
• Totals more than 3 million Nvidia GPUs due before 2029, a ~1.9x multiple for each of Amazon's roughly 1.58 million employees
• Nvidia's CFO has said deliveries start this quarter, not in 2027, but neither company says what it counts as a GPU or what the deal costs

Amazon ended 2025 with about 1.58 million full- and part-time employees, most in fulfillment centers and delivery operations, with a much smaller share working in its AWS data center division (estimated at around 246,000).

By mid-2028, Amazon Web Services expects to have taken delivery of roughly twice that many new Nvidia GPUs, based on a recent deal it made with Nvidia.

The latest deal was announced on August 26, the same afternoon Nvidia reported quarterly earnings, and will see AWS plan to deploy two million additional Blackwell Ultra, Rubin, and Rubin Ultra GPUs across its global infrastructure in 2027 and 2028. This is on top of over a million Nvidia GPUs that AWS committed to at Nvidia GTC 2026 in March, and which Nvidia's Ian Buck told Reuters would ship from 2026 through 2027.

A mammoth deal that dwarf's Amazon's entire payroll

Together, this all amounts to over three million GPUs in play between the data center giant and the chip designer, which is also the world's most valuable company at the time of writing. At 3 million GPUs against a workforce of 1.58 million, that's nearly 1.9 Nvidia GPUs per employee.

This is only Amazon's commitment to Nvidia; it also has its own custom Tranium3 GPUs, which the company says are "nearly fully subscribed" or "almost fully booked" as of mid-2026.

At the same time, Amazon is not increasing job roles on its end; it cut around 30,000 corporate roles between October 2025 and January 2026, a restructuring its top HR executive, Beth Galetti, described as "reducing layers, increasing ownership, and removing bureaucracy."

Building on an already solid base

While AWS's current GPU base from Nvidia, consisting mainly of H100 and H200 GPUs, is smaller than Microsoft's 485,000 count, it is hardly a rounding error, with Omdia estimating that Amazon bought 196,000 Hopper GPUs in 2024 alone.

The interesting part is determining what counts as a GPU: Nvidia and Amazon's joint statement about 2 million GPUs across calendar years 2027 and 2028 might mean two very different things depending on how you count GPUs.

At GTC 2025, Nvidia said it would count Rubin-generation GPUs by compute die rather than by package, which is why the Vera Rubin rack was first unveiled as NVL144. It reversed course before CES 2026, and the flagship now ships as Vera Rubin NVL72, counting 72 two-die packages. To make matters a bit more complicated, Rubin Ultra, due in 2027, puts four compute dies in each package.

Whether the companies count each die as a separate GPU or the whole package as a GPU could make the numbers skew heavily in either direction. The deal also includes a national security element: approximately 100,000 GPUs are earmarked for US government AI workloads at Impact Level 6.

Amazon's limitation here is supply, not demand; AWS revenue rose 37% year over year to $42.2 billion in the second quarter, and its contracted backlog reached $496 billion, up from $364 billion three months earlier, as CloudTech News reported.

On Amazon's July earnings call, CEO Andy Jassy said capacity would fall short of demand this year and likely next, adding: "In fact, the demand we already have for 2028 is striking."

In addition to its own custom ASICs, including Tranium3, Amazon is gearing up for a few fiscal years of eye-watering AI infrastructure spend and AI demand combined, and it better be right: Amazon's free cash flow has already turned negative as it looks to fund its bid to be one of, if not the largest hyperscaler in play for the foreseeable future.

Via StorageNewsletter

It's been over four years since Intel Arc graphics made their debut. Team Blue, primarily known for making some of the best processors of all time, had made its second big swing against the best graphics cards. Alchemist had promise from a price-to-performance perspective; the A-series impressed with budget-friendly performance in 1080p and 1440p with the Arc A750 and Arc A770, respectively, despite some driver issues and (initially) a lack of developer support.

Everything changed with Battlemage. Intel's second-generation Arc graphics cards received higher praise, with far superior generational performance, rivalling the best cheap graphics cards. In particular, the Arc B570 was a powerhouse for 1080p gaming with its $219 / £219 MSRP, and the Arc B580 confidently earned a perfect review from us with its all-star 1440p performance for just $249.99 /£249.99. However, that was some time ago.

Now, nearing the end of 2026, the concept of a cheap video card, or a true graphics card deal, is (sadly) extinct. You can expect to pay double (or more) for a B580 that made waves due to its value proposition just two short years ago, lessening the impact of an otherwise excellent GPU. Team Blue has reportedly canceled its Celestial range of discrete graphics cards, and the future of Druid (the codename for Intel's fourth-generation GPU) and beyond is uncertain.

Has Intel abandoned the dedicated GPU market to go all-in on the likes of its G3 Extreme chip found in the best gaming handhelds? Moreover, is there still hope for a third major competitor during the worst time to build (or buy) a gaming computer in recent memory?

What were Intel's original plans for Celestial?

When Intel Arc was originally announced more than five years ago, Team Blue confidently laid out its "Multi-Year Roadmap", with Alchemist (A-Series) slated for Q1 2022, a goal the company only just achieved as the initial GPU lineup dropped on March 30. With that said, no dates or timeframes were confirmed for the second, third, and fourth generations of its Xe platform.

Intel Arc Battlemage (B-series) graphics cards were officially launched on December 3, 2024, meaning almost three years (or two years and eight months) had passed between the two Xe generations. This release schedule is fairly standard for GPU launches; Nvidia launched the Blackwell-based RTX 50 series on January 30, 2025, with the RTX 5090 and RTX 5080, succeeding the RTX 40 series that debuted on October 12, 2022, with the then-flagship RTX 4090 (two years and three months).

It's nearing the time when we should start hearing about Intel Celestial, especially given just how well-received Battlemage was, and yet there's radio silence from Team Blue. More specifically, speculation around The C-series' cancellation were sparked from rumors dating back to April. Specifically, it was hardware leaker Jaykihn on X who alleged that "Celestial was canned long ago" and that "Druid is up in the air".

If we look at the updated Intel Arc Graphics roadmap, the company alleged that the Xe3P Cestial graphics cards should have been arriving in 2026.

What happened to Intel Celestial?

Intel had clearly stated in 2025 that next-generation Xe3 Battlemage graphics would arrive that year, and then year-on-year we would receive Xe3P with Celestial in 2026, Xe4 with Druid in 2027, and Xe Next, the "Next-Gen," in 2028. So what actually came of these claims? So far, so good, as the B-series is integrated into the latest G3 family.

As well as the Intel 18A-based Compute Tile (14-core with NPU 5 and up to 8,533 MT/s LPDDR5x memory), it also uses the Xe3 architecture for its 10-12 Xe-cores, 10-12 RT units, and 80-96 XMX AI Engines, whether it's the standard or the G3 Extreme variant. In other words, Intel has decided to renew Battlemage for a third year running, with no apparent space (or need) for Celestial at this time, at least for the purpose of dedicated gaming.

It's alleged that Xe3P architecture (Celestial) is being baked into the upcoming Intel Nova Lake processors. More specifically, the C-series could be entirely relegated to integrated graphics onboard certain incoming chips rather than powering discrete graphics cards.

This is claimed to be the case with the Nova Lake-S lineup, which is said to be a 16-core CPU with a 12-core Xe3P iGPU forged on the silicon, unlike other Nova Lake processors that could feature just two Xe3 cores.

While Xe3 is already being used in gaming handhelds powered by the G3 and G3 Extreme, the combination of both Xe3 and Xe3P in Nova Lake could be where Celestial lives. It's been rumored that the extra performance of the newer-generation cores could be primarily for driving the Visual Engine rather than being used for anything more intensive. Revealed at Hot Chips 2026, Intel announced that Xe3P would be powering its Crescent Island AI GPUs. At the moment, then, it seems that Team Blue has no interest in bringing over Celestial tech for gaming.

Battlemage isn't worth the price anymore, and Intel needs to learn from this

There's no easy way to say this: Intel Arc isn't worth the inflated asking prices. While the two main Battlemage graphics cards initially won favor with us and the general gaming public, the value proposition simply isn't justifiable this late in 2026. As touched upon above, both entry-level GPUs have doubled in price, and it's really hard to see the justification against a considerably stronger graphics card like the RTX 5060 and RX 9060 XT.

The average Arc B580 GPU nowadays costs around $330 / £340 for the 12GB variant from Intel's board partners such as ASRock and Sparkle. That gets you the current top-end Battlemage card with a 192-bit memory bus, 12GB of GDDR6 memory, and a total of 2,560 GPU cores.

However, for around the same price, you can also opt for an RTX 5060 8GB, or bump your budget up to around $400 / £400 for the far more capable RTX 5060 Ti instead. The former has a smaller 128-bit memory bus, although it benefits from 8GB of GDDR7 memory and 3,840 CUDA cores, whereas the latter comes with the same bus width but with up to 16GB of GDDR7 VRAM and 4,608 CUDA cores. Which one would you pick when weighing up a cheap gaming PC build?

Let's forget the tech specs and instead look at the performance numbers laofcct. According to testing conducted by Mark PC, both the similarly priced RTX 5060 and RX 9060 XT. We see this in countless examples with the demanding PC games tested, such as The Last of Us Part 1, Cyberpunk 2077, Assassin's Creed Valhalla, and Starfield; all of these games had superior average framerates from the AMD and Nvidia GPUs when benched in 1080p at max settings.

This is consistent with the testing conducted by Hardware Unboxed as well, as the three entry-level graphics cards were benched in 1080p with Medium to High settings, depending on the game. It's the same story with the likes of Ratchet & Clank: Rift Apart, Marvel's Spider-Man 2, Assassin's Creed Shadows, The Last of Us Part 2; you get the idea. If buying a graphics card from a processor company wasn't already a hard sell, then the price-to-performance of Arc circa 2026 certainly is.

Druid is Intel's last chance at remaining in the gaming GPU market

If Celestial is truly canceled (or relegated to an obscure APU), as has been claimed, then all hopes hinge on Druid and its Xe4 architecture, which is slated to be released in 2027. "Up in the air" really is an understatement with Team Blue's plans for its proposed fourth Arc generation; there's nothing circulating about this tech at all, which is rare considering the usual slate of rumors and speculation that usually whir up a year or so out from release.

The only real sliver of information that points to Team Blue still being in the GPU race at all comes from Alex Katouzian, Intel EVP and GM of Client Computing, who spoke to Dutch tech site Tweakers during Computex 2026. Katouzian is quoted as saying: "GPUs are a super important part of our PC product range" and "the traction of our GPU cores is really very good". It's a non-answer to a tough question that doesn't really give any indication as to what the company is planning; typical corporate speak to cover up the fact that it may have no idea where (or if) Druid has a future at all.

Worst-case scenario, then. Let's say Celestial is properly canned, but that Intel gives Druid a shot as a last-ditch effort to save the fledgling Arc graphics division in its dedicated form. Following the same blueprint as its last two GPU generations, a prospective launch of the D570 and D580 would need to be 12 to 16GB GDDR6X at a minimum, be built with XeSS 3's MFG in mind for 1080p to 1440p gaming, and still retail new for $250 to $350, respectively. Is this really something that can happen in 2027 with the price of graphics cards continuing to rise? I remain unconvinced.

There's a pathway for Intel to win back favor and consumer trust with a line of affordable graphics cards that deliver playable results for today's games. However, given the dire state of the industry and some truly puzzling top-level decision-making over the last two years, it just doesn't seem like things can be salvaged here. I would love to be wrong; more competition and consumer choice are always good for business, particularly if it means showing Nvidia the true meaning of budget and mid-range, but is Intel really the company to do that in 2027 and beyond? It's unlikely.

• AMD is rumored to be hiking prices for its chips
• Industry insiders in the supply chain indicate that a rise of around 10% will be applied across AMD's "entire chip line"
• This means GPUs and processors, as well as motherboards, and the hike is expected in Q4, so it could happen next month

AMD's processors and graphics cards could soon get more expensive in the latest blow from the RAM crisis rumor mill.

Wccftech spotted that leaker Harukaze5719 highlighted a post from ChannelGate (the Board Channels over in Asia) that cites sources in the supply chain who claim that TSMC has informed its customers of a 10% price rise.

The post observes that most of AMD's chips are manufactured by TSMC, and that Team Red has in turn notified its customers of a 10% "price adjustment" across its "entire chip product line".

That means everything, so on the consumer front, we can expect AMD's GPUs and Ryzen processors to be hit with price increases — and motherboard chipsets are also affected, so the price of those AMD boards will climb, too.

It's worth noting that processors aren't referred to explicitly in the post on the Board Channels, but given the mention of the entirety of AMD's chips, I think we can take that as real (as the leaker Harukaze5719 indicates).

The sources believe that AMD will enforce this new policy in Q4, so it could happen next month, in theory (although all of this remains a rumor).

In other RAM crisis bleakness, the Steam Frame arrived earlier this week with a much-inflated price tag compared to what Valve first envisioned for the VR headset. It starts at $1,059 / £889 / AU$1,609, which is a few hundred more dollars than what Valve was thinking originally.

As PC Gamer reports, a hardware engineer at Valve, Joy Lyons, said, "We set out to design [the Steam Frame] with one particular price in mind, but we've made choices to make sure that we're making a product that is choiceful, that people can purchase. They can upgrade with different features later. But we wanted to make sure we had a base product with really great performance. Then that price target shifted due to the ongoing RAM crisis around the world."

Analysis: a believable enough prediction

Sadly, the AMD rumor is another worrying doom nugget from what seems to be a never-ending supply of bad news in the past couple of months. Just this week, we've had a report that shows DDR5 RAM is somehow getting even more expensive, blowing past the levels I'd expected — not to mention the laptop price hikes.

The RAM crisis was forecast to worsen as 2026 rolled on, and that appears to be unfolding just as predicted — and there's very possibly worse to come in 2027, going by rumors elsewhere. If the pundits, analysts and insiders were right about this year, there's a fair chance they'll be right about next year, too.

Okay, so that's not a foregone conclusion, and some kind of more positive developments could yet happen — we can hope. This particular rumor must also be treated with some caution, as a Board Channels post may not have everything right (by any means), but the problem is that given the current climate, it's believable enough that AMD has price hikes in the works. Team Red already warned us earlier this year about pricing pain for the second half of 2026, after all.

• The cheapest available US RTX 5090 now costs over $6000 against a $1,999 launch price, with third-party listings often running past $9,000
• The GPU that already pushed past $3,500 in Feb 2026 owing to memory constraints driving prices higher has now hit fresh highs at multiple retailers
• The move is linked to AI demand, as data center operators have entered the fray to secure compute despite Nvidia's GeForce driver license having banned 'data center deployment' on paper since 2017

Six weeks ago, the story was ultra-rare books being fed spine-first into high-speed scanners so that AI labs could train on text written before chatbots polluted the corpus.

Focus, however, has shifted considerably to AI labs bringing the same voracious appetite to Nvidia's flagship consumer-grade Blackwell GPU, the RTX 5090, which has essentially disappeared from shelves unless you want to pay a 200 percent or higher premium to grab one.

Photographs circulated by Hong Kong outlet HKEPC, and picked up by multiple publications including Guru3D, VideoCardz, and TechPowerUp, appear to show wooden pallets stacked with boxed, retail GeForce RTX 5090 cards at AI server assembly sites, waiting to be unpacked and slotted into multi-GPU rigs.

The sky is the limit for Nvidia's flagship consumer card?

This isn't the first time Nvidia's RTX 5090 GPUs have been deployed en masse on multi-GPU, AI-centric rigs, but this time feels different, even compared with previous shortages.

For context, Nvidia launched the RTX 5090 at $1,999 in January 2025. Tom's Hardware's price tracker, updated on September 14 2026, lists the cheapest available US card at $6,389, nearly 3.2x the former.

PCGamesN reported the same week that first-party stock at Amazon, Newegg, and Best Buy had essentially vanished, leaving third-party marketplace listings above $6,000 and, in some places, over $9,000.

The pictures in circulation don't show RTX PRO workstation GPUs, but rather GPUs from MSI, Gigabyte, and ASUS that the average gaming enthusiast or consumer would pick off a shelf.

An AI-generated image to create more FOMO?

The images have, however, been disputed by some quarters: Kevin Hofer at Swiss retailer Digitec, one of the few writers to examine the images rather than republish them, pointed at the box lettering in one frame and asked what a "50B0" or a "50R0" is supposed to be, concluding that AI was probably involved in producing the picture. Twitter has also added a "made with AI" moniker to the image in question.

TechPowerUp and TweakTown both carried the same warning in softer form. Guru3D, to its credit, noted that the report explains neither why these firms chose the RTX 5090 nor the scale of the purchases.

Coverage like this, even with disclaimers to the contrary, can create a "fear of missing out" (FOMO) where price increases become a self-fulfilling prophecy as businesses and consumers alike move purchases forward to avoid paying a further premium.

Examining the value that an RTX 5090 brings to the AI table

The Nvidia RTX 5090 is its most powerful consumer-grade card to date, packing a Blackwell-based GB202 chip and 32GB of GDDR7 memory, which checks multiple boxes for local AI use cases and gamers looking to max out games at 4K or higher.

Nvidia's GeForce driver EULA has, since late 2017, included a clause titled "No Datacenter Deployment" that should, at least on paper, prevent data centers from stockpiling or using these.

The chip designer, currently the world's most valuable company, has previously implemented technological restrictions such as LHR (Lite Hash Rate) on its RTX 3000 series GPUs to prevent GPU miners during the Ethereum gold-mine rush from hoarding supply.

It has also released a China-specific RTX 5090 D, which reduces AI performance while matching the RTX 5090 in gaming throughput. The RTX 5090 D, created to meet AI export restrictions, shows that Nvidia can limit the RTX 5090's AI performance, but it remains relatively indifferent to a market that was its core revenue source only a few years ago.

The RTX 5090's price hike, at least in part, may be due to the RTX PRO 6000's staggering, out-of-control pricing, which Nvidia nearly doubled to $16000. The underlying cost driving the price hike is the GPU's 96GB of VRAM, which also makes up a sizeable, if not dominant, chunk of its total bill of materials.

An RTX 5090 comes with 1/3rd the VRAM on offer, but nearly the same compute performance, and with AI-centric algorithms often assisting in breaking up tasks between GPUs and memory pools, even as the total memory pool remains similar, a triple stack of RTX 5090 GPUs should comfortably outperform the RTX PRO 6000 in certain tasks.

At the same time, Chinese OEMs have reportedly managed to slap on as much as 96GB of VRAM on an RTX 5090, which could make it an even hotter commodity in a country where both the RTX PRO 6000 and the RTX 5090 are export-restricted but do manage to make it on the regular.

The RTX 5090 is a manufacturing problem with a memory bottleneck attached for AI consumers, but with the alternatives having doubled in cost recently, AI consumers are looking to save money wherever possible, and both the stock RTX 5090 and a potentially modified one are some of the best candidates in a market that has already exhausted most of its last-generation supply of the same.

• AMD is rumored to be working on its own version of DLSS 5
• A leaker says that the neural rendering tech will be launched with next-gen RDNA 5 GPUs
• That means we could be waiting until late 2027 or 2028 to see this debut, which might leave AMD lagging behind Nvidia considerably

AMD could be working on its own take on Nvidia's DLSS 5, and apparently this alternative attempt at neural rendering will be for its next-gen RDNA 5 graphics cards.

VideoCardz spotted that a known leaker in the GPU field, Kepler L2, posted on the Anandtech forum in a discussion around RDNA 5 speculation to say that: "AMD will have their own version of 'Neural Lighting' like DLSS5 next-gen."

Kepler then clarified that he didn't mean a version of Ray Reconstruction, but a take on DLSS 5 (neural rendering), and that next-gen RDNA 5 GPUs would be required because "this stuff is pretty heavy" (as in resource-intensive).

In a further post, Kepler elaborated: "There's a lot of issues with Nvidia's approach [with DLSS 5], but it's possible to have a version of this with minimal hallucinations and 'AI slop' look."

He then suggests a way that AMD could work its version to improve on DLSS 5, including giving the AI "direct access to 3D game data such as geometry, ray data, depth buffers, materials, etc so it doesn't have to guess and can accurately know how each object in a scene should interact with light."

Kepler's outline of a proposed alternative for AMD would have a separate model (AI) for lighting improvements, and another different model solely for the shading of complex surfaces. DLSS 5 bundles these together with its neural rendering system, and adds color-grading on top — to adopt what the AI judges as more natural colors — which Kepler advises that AMD should dispense with entirely.

Analysis: a race against time – or a chance to get it right?

I won't pretend to be able to critique what Kepler is suggesting as an alternative for AMD and the technical nuances therein, except to say that the idea is clearly to achieve a result that looks less like it's been 'messed' about with by AI and minimizes any 'slopification' therein — preserving more of the original artistic intent.

And that seems a laudable goal, of course, and it also brings up how AMD is in an interesting position here in lagging behind Nvidia with its graphics tech (which has, of course, been the case from the start, with FSR following DLSS — version 2.0 of Nvidia's upscaling tech was already in play, in fact, when FSR 1.0 arrived). Team Red can sit back for now and see how DLSS 5 plays out, as more games emerge that use it, and gauge the reaction of gamers, and forge its own neural rendering tech to tackle any perceived weaknesses.

The performance hit will be an obvious area to target, and if AMD can bring that down — it's substantial with DLSS 5 as it is now — that will obviously be a big win. That said, I'd expect Nvidia will be working with some haste to make DLSS 5 more performant, and as with DLSS 1, the tech will be improved considerably by the time Team Red has its own version out.

This is the other side of the equation here, where Nvidia could win out. With RDNA 5 GPUs not expected to arrive for at least a year, and quite possibly longer (the RAM crisis isn't helping), there's quite a lengthy timeframe on any AMD rival to DLSS 5. By the time it arrives, DLSS 5.5 may be in town with considerable improvements in tow. There's already been a notable turnaround in the perception of DLSS 5 with its official launch (compared to Nvidia's sneak preview earlier this year).

This is, of course, assuming AMD is indeed working on its own neural rendering technology, but I'd be surprised if this wasn't the case. For now, though, the word of a single leaker needs to be thoroughly seasoned, as ever, even though it's believable enough that Team Red would be aiming to use this on RDNA 5 graphics cards.

• Nvidia's RTX 5090 is now over $9,000 in the US
• A new rumor suggests that RTX 6000 gaming GPUs are coming in 2027, maybe in the first half of the year
• If true, the price tag that's attached to the RTX 6090 will likely be colossal, and lower-tier GPUs could be pricey too

Nvidia's RTX 5090 flagship has hit new heights in terms of ridiculous asking prices, just as a new rumor suggests that RTX 6000 (Rubin) GPUs are coming in 2027 — earlier than anticipated, and to say the price of those next-gen offerings is a worry given the current climate is a huge understatement.

A Redditor pointed out the current state of RTX 5090 prices, which are close to commanding $10,000 in the US for some models. Notably, the Asus ROG Astral RTX 5090 will set you back a princely $9,659 on Newegg US, although that's not sold directly by the retailer.

Indeed, none of the big retailers have any stock of the RTX 5090 anymore, and the only graphics cards you can buy are from third-party marketplace sellers, often shipping from Asia (that ROG Astral GPU comes from Hong Kong).

You can find more expensive RTX 5090s than that if you want to get the gold-plated version (Dhahab Edition) of the ROG Astral, which is now $11,999. The very cheapest RTX 5090 that I could find at the time of writing is an MSI Ventus model that's priced at $6,549 on Newegg.

What about outside of the US? Price inflation is rampant in other countries too. If we take the UK as an example, you can pick up an RTX 5090 for around £4,500 on Overclockers UK, which is still an eye-watering asking price. (And those are the cheapest GPUs — they go up in price from there to £6,600 for the aforementioned Asus ROG Astral RTX 5090).

It's an alarming situation, and one that heaps worries on top of a new rumor about the RTX 6000 launch as aired by Moore's Law is Dead (MLID) on YouTube (via TweakTown).

Previous rumors have contended that Nvidia's looking at 2028 for the arrival of its next-gen GeForce graphics cards, but a source at the firm told MLID that this is incorrect, and Team Green is aiming for a 2027 launch. Moreover, the current plan is still to get the RTX 6000 ball rolling for PC gamers in the first half of next year, meaning within the next nine months.

There's an obvious sticking point here, though: if the RTX 6000 generation is this close, how come we haven't had much in the way of leaks yet, and nothing of any real substance? The source claims that this is due to Nvidia's management successfully clamping down on leaks with the next-gen products.

The first offering will presumably be the RTX 6090 (or maybe an RTX 6080 as well), and it's going to have some kind of interesting spin on the design — though we aren't told what. It could have beefed up hardware to better cope with running DLSS 5, perhaps, as that would make sense — something to help deal with the performance hit of neural rendering would clearly be very welcome.

Analysis: house deposit or GPU?

There are obvious problems with a possible RTX 6000 launch next year, if we take this rumor at face value. As noted, the RTX 5090 is now being sold for beyond ridiculous prices — and so how much is an RTX 6090 going to run? The fiscal equivalent of an ultramarathon, presumably, and with AI demand likely coming into play with this GPU, the next-gen flagship could be 'unobtainium,' as the disgruntled gamers out there are already predicting.

When you consider that the RAM crisis is going to get worse next year, going by the more recent forecasts from analysts and industry insiders, video RAM is going to be more problematic — and how much of the stuff will be on an RTX 6090? — it all adds up to a frightening prospect for an MSRP. And the likely reality is that the price to actually buy the next-gen Rubin gaming flagship will blow well past that towering recommended cost. (The RTX 6080 won't likely be much different, either.)

For all these reasons, I find it difficult to believe that Nvidia will go ahead and launch the RTX 6000 series next year. Surely it makes sense to wait longer, although what Team Green may know is that 2028 isn't going to be any better for RAM price inflation, and so perhaps that's why next year is greenlit for next-gen GeForce graphics cards to arrive. It's a sobering thought. As one Redditor observed: "Can't wait to decide if I want a down payment on a house or an Nvidia GPU."

• Japanese retailer warns of further GPU price hikes
• The retailer doesn't specify which GPUs will see increases
• Consumers are urged to buy now, but GPUs are already overpriced and unaffordable in many cases

The PC hardware market is still in disarray, with RAM shortages impacting almost every component, and unfortunately, matters could get even worse for GPU hunters.

As reported by VideoCardz, Japanese retailer Applied has warned consumers about potential price hikes for GPUs (yet again). It's unclear which GPU models this might apply to, but the retailer urges PC owners looking to upgrade their GPUs to buy as soon as possible.

VideoCardz also highlights that Japanese retailers only recently adjusted GPU prices upwards. In August, stores in Akihabara warned that pricing would be around 20% to 30% higher than usual.

Considering the recent rumblings of price hikes from Nvidia's board partners, it's fair to suggest that these increases will likely apply to other regions outside of Japan (assuming there's anything in these rumors).

If it wasn't exactly clear already, these price hikes are caused by the RAM crisis which is affecting all manner of PC components. Graphics cards are hit due to the rising cost of the video RAM on board.

Panic buying still isn't the best solution

PC owners are now hard-pressed to find affordable hardware upgrades, and it's been that way since the start of 2026. The RAM crisis is showing zero signs of slowing down, too, especially with reports from Samsung and industry analysts suggesting that the memory shortage will last past 2027 or beyond that, even.

Despite that, I still don't think it's the best idea to panic buy now when it comes to a GPU. Many Nvidia GeForce or AMD Radeon third-party GPUs are either unaffordable or overpriced at various major retailers. Prime examples of the former are the RTX 5080 at $1,699 at Best Buy in the US currently, while the RTX 5060 remains overpriced between $450 and $500, despite its $299 MSRP.

The same goes for AMD's Radeon RX 9070 XT, which has a $599 MSRP but can now cost up to $929 (specifically the Gigabyte overclocked model). The Radeon RX 9060 XT (16GB) also sits at least $200 to $300 above its MSRP, and the list goes on (in the US and elsewhere).

Simply put, buying a new GPU doesn't seem worth it unless you're a gamer looking to dive into the PC ecosystem for the first time. That's a harsh reality to accept, but panic buying might do more harm than good by increasing demand (which could lead to further short-term price hikes).

• More mods are out for DLSS 5
• They allow for the tech to be easily used with many more PC games
• One of these mods also alters the way in which DLSS 5 is applied to improve performance considerably — at a cost

As you've no doubt seen, modders have been having a field day messing about with Nvidia's DLSS 5, and the latest experiments include a trick to boost performance in a big way, and a method of easily running the tech in a lot more games.

Let's start with the latter, which as TweakTown reports is the DLSS 5 Swapper app which appeared on GitHub courtesy of developer Rakan Alkhaldi.

This takes the pain out of having to manually fudge DLSS 5 to work in unsupported games by automating the process, adding all the required files in the blink of an eye. You just drag and drop the game folder into the app, and it takes care of everything from there.

Swapper can even detect games on the PC it's installed on which can have DLSS 5 modded in. Not every game is supported, of course, but plenty are — and any given title doesn't necessarily have to have DLSS support at all, in any form (this is achieved via another community mod called DLSS 5 Feeder which is included with Swapper).

A similar tool, DLSS 5 Autopilot, published by 'Kizzuwatnaa' and also on Github, offers one-click DLSS 5 setup (via Feeder) along with an additional trick in the form of the 'neural upstream' add-on (from 'matiasLombo'). This runs the neural rendering (AI) process before the DLSS upscaling happens.

Normally, the AI polishing that DLSS 5 applies is performed as the last step of the rendering process to the upscaled final frame, but if you choose this option with Autopilot, it's happening earlier in the chain of events.

Based on experiments detailed on Reddit (posted by ToxicFatee), this makes a major difference to performance. The Redditor has an RTX 4080, and ran Assassin's Creed Shadows at 4K which went from 63 frames per second (fps) to 31fps with DLSS 5, but it was around 50fps with the neural upstream take on DLSS 5. That's a 20% loss, and a far more palatable hit on the frame rate rather than it being cut in half.

Others have aired similar results on Reddit, and there's plenty of excitement about what's being achieved with this mod (and the automated implementation of DLSS 5 across all manner of games). As one Redditor put it: "Absolutely amazing time to be a PC gamer."

Analysis: tread carefully with unofficial mods

All these latest developments with modding are great to see, but for me, it ends at just seeing this progress. By which I mean I wouldn't advise jumping in and installing these kinds of mods – as wonderful as they seem – and I'm content to merely observe, and see the frame rates and visual results, that others are getting. And we aren't short of these observations of late.

Why do I take that view? Well, for starters, I'm not keen on installing third-party software from unknown sources as a rule, because of the concerns around security that this involves. Granted, these are open-source tools (so can be checked over), and I'm sure they're on the proverbial level; but nevertheless, I'd still rather be careful around the risks of viruses and the like.

The second note of caution here pertains to the idea of messing with the rendering pipeline in terms of having DLSS 5 applied earlier in the process (with the Autopilot mod). This will likely involve image degradation or artifacts to some extent — or generally messing with the graphics more than Team Green intended — and I'm sure if this really was a genuinely better way of doing things, Nvidia would've used this route itself. As per observations on Reddit, there does appear to be a quality trade-off for the improved performance here.

All that said, perhaps there will be some kind of official option along these 'performance or quality' lines in the future, as some gamers are already hoping. However, DLSS 5 is, for now, officially designed to work with just one supported title, NBA 2K27, and it does an excellent job with that basketball game.

Following the leak of the tech and a raft of unofficial mods, this week saw Nvidia's official launch of DLSS 5, with the company showing it off in NBA 2K27 at Gamescom 2026 and providing some further illuminating details.

Before, after Nvidia's initial DLSS 5 reveal in March, I was skeptical on some points, but I wasn't tearing holes in the idea like some gamers were. However, this week, we've seen a rapid shift in opinions and the general online sentiment around DLSS 5 — and I'm a good deal more excited about this AI trickery myself.

Indeed, I think there are a number of reasons to be hopeful that DLSS 5 could prove to be a compelling step forward for PC gaming, from Nvidia's clarification on support for GPUs, through to what modders have shown that the tech can achieve since it was leaked — some of which is truly eye-opening.

Here are my five reasons why Nvidia's incoming neural rendering model could turn out to be a very literal game-changer.

1. Nvidia has clarified that DLSS 5 won't just be for RTX 5000 GPUs

While DLSS 5 is currently only supported by RTX 5000 graphics cards — the tech went live this week in NBA 2K27 — Nvidia has confirmed that it will come to older GeForce GPUs. Indeed, we won't have to wait that long before wider support is ushered in, which is good news.

VideoCardz spotted an update from an Nvidia rep on Reddit which stated: "Our current focus is on optimizing performance for the GeForce RTX 50 Series with model updates expected later this fall. Once RTX 50 Series performance is more fully tuned, we plan to work on expanding official support to the GeForce RTX 40 Series."

So, we could be looking at early 2027 for work to begin on bringing DLSS 5 to RTX 4000 models — and possibly previous generations of GPUs will be in line for the same treatment. Modders have already got the tech working on RTX 3000 and 2000 models, after all — although the performance levels could well be the sticking point here.

At any rate, this puts paid to fears that DLSS 5 could remain locked to just the latest Nvidia RTX 5000 graphics cards.

2. Continual optimization should improve performance a good deal

I just touched on performance, and this is the area which has proved to be the biggest downer with the mentioned unofficial experiments that have been conducted with DLSS 5.

As Tom's Hardware observes, the performance hit with DLSS 5 is a nasty one, and it's generally causing a 40% to 50% drop in frame rates. In some reports, it's less than this (more like 30%), and what we have to remember is that all these unofficial figures are based on a pre-release version of DLSS 5 being fudged into play by modders.

The final version of DLSS 5 will likely provide better performance, and in any case, optimization is going to be high on Nvidia's list of priorities. I'd be surprised if there weren't major strides taken in this department as 2027 rolls around and more games are supported.

3. Experimental results with DLSS 5 are pretty incredible

Those modders playing with the leaked version of DLSS 5 have clearly shown us that this tech can be used to produce seriously impressive results. Of course, on the official front, the demo of NBA 2K27 at Gamescom 2026 proved the case that this AI-powered graphics uplift can work wonders, too.

That said, the benefits of DLSS 5 are situational to an extent, and it's not a silver bullet for making all graphics better. It really shines in certain use cases, though. For example, even if you don't want the main character models in a game to have the tech applied because you hate that idea, it can still make a huge difference to background details, and the likes of the faces of NPCs in the lurking atmospheric crowds which are the backdrop for open world games.

As one Redditor points out: "NPC crowd faces are one of the best use cases for it [DLSS 5]. It sometimes takes you out of the game when you're talking to a character model that's clearly been hand crafted with a lot of effort, and as you said then there's some janky smooth skinned ghoul walking by you lol. Watching an LTT [Linus Tech Tips] vid where they showed the difference in random NPCs was actually super impressive."

DLSS 5 can also transform lighting and shadows to make graphics look far more realistic, including character models — some of the results shared by modders in a megathread on Reddit make that crystal clear. I was blown away by some of these examples, frankly. When it works, DLSS 5 works really well — although it doesn't always come off.

That said, some of the wonkier examples that have been aired are down to modders being daft with the sliders and options on offer, which brings me onto my next point.

4. Tuning options are key for DLSS 5

As noted, some of the more stomach-churning moments from the various modders messing around with DLSS 5 have come from those folks ramping up the intensity of the sliders — sometimes intentionally just to provoke an anti-AI reaction.

There's a decent level of granular control over various aspects of what DLSS 5 does (including intensity, tone, and structure), and when a game developer properly tunes the tech for their particular release, the effect is going to be more subtle, appropriate, and in line with the overall art direction. (Well, hopefully — you'd assume this will be the case, anyway).

Used judiciously, it's clear enough that DLSS 5 can really enhance the visuals of a game — modders have proved that in some cases, and NBA 2K27 is a great official example of how this works, too.

Yes, it is very possible to get 'uncanny valley' kind of effects with character models if you're extravagantly flinging sliders up towards their maximum limits — and not every game's art or graphics style suits DLSS 5, by any means. But we come back to the last point — when it works, it really does work.

5. DLSS 5 will probably age like a fine wine (ahem)

My final point is a simple — but important — one. And okay, I've said this before, but I think it bears repeating. Rewind time back to when Nvidia revealed the original DLSS, the very first take on this tech that was purely about upscaling, and it had some quite pronounced flaws. Problems like blurriness, ghosting and artifacts proved a blight on the upscaled graphics, but these were issues that Nvidia resolved with the next iteration of the tech.

I'd expect there will be examples of DLSS 5 which show the visuals going off the rails in a similar kind of way, although it already looks off to a far better start than DLSS 1. The point being that whatever we think now, at launch, may change quite drastically in a year or two, and there's a genuine potential for DLSS 5 to be revolutionary in polishing up gaming graphics — albeit that caveats around its misuse and situational nature aren't going to go away.

• Nvidia's latest graphics driver has a frustrating bug
• Version 616.56 is causing distracting screen flickers and color corruption
• A patch is coming, and there are potential workarounds — but gamers are getting fed up with the prevalence of bugs in GeForce drivers

Nvidia's latest graphics driver is causing chaos for some GeForce GPU owners in the form of a glitch that makes the screen flicker.

Wccftech spotted the bug with Nvidia's Game Ready Driver version 616.56, and as flagged by Renan Maniero on X, Team Green has said it's testing a fix for the issue (as revealed on the GeForce forums).

The screen is reportedly flickering white or black and exhibiting other brief flashes of color corruption, and this is happening in certain games (The Last of Us and Minecraft are mentioned, among others) or on the Windows desktop. It's also occurring in web browser sessions and while playing YouTube videos, based on Reddit reports — of which there are plenty.

There's no shortage of gamers losing their temper with Nvidia, too, and blasting Team Green for the quality of its graphics drivers. Many are venting with an observation that GeForce drivers just haven't been the same since the launch of the RTX 5000 series.

For example, this Redditor says: "It's been particularly bad since Blackwell [RTX 5000] release. Just on Blackwell alone, between the whole DisplayPort 2.1 not working with HDR, screen flickering, and black screens on the initial release, it's been a complete mess."

Another gamer complains: "It is pretty shocking seeing this from a trillionaire company on a stable build. Nothing about this driver is stable."

Yet another Redditor grumbles: "It's crazy how things are now. You used to be able to update each time or be one driver behind at worst. Now I'm half a year outdated and thinking I'll just leave it."

Analysis: more drivers, more problems? There are possible workarounds though

This seems like quite a widespread issue and one that affects modern Nvidia graphics cards all the way back to RTX 2000 models.

If you're getting frustrated by this bug — random screen flickering gets pretty old, pretty fast, if it's happening regularly — Maniero also shared an apparent potential workaround on X that you can try while waiting for the official fix.

Seemingly, this is a bug that mostly affects monitors in 8-bit mode, and if you switch to 10-bit color (assuming your display supports this), the problem may disappear. Maniero also suggests that you try turning on Windows Auto Color Management (ACM).

Other folks on Reddit have shared various possible remedies, including switching from DisplayPort to an HDMI connector instead, and disabling Multi-Plane Overlay (MPO) in Windows 11, as one Redditor suggested. Nvidia provides a Registry file for turning off MPO (and enabling it again), but as ever with anything in this area of Windows, proceed at your own risk. (Although this method should be much safer than trying to edit the Registry directly yourself).

Your other choice is simply to roll back driver 616.56 to an earlier version, and there's no shortage of gamers who've done exactly that and report that the problem vanishes.

Hopefully Nvidia's official flicker-begone patch will be coming soon enough in the form of a hotfix, because this is an unduly annoying gremlin in the GeForce works that needs to be sorted out promptly.

• Nvidia unveiled DLSS 5 at Gamescom 2026, showing it off in NBA 2K27
• DLSS 5 will launch alongside NBA 2K27, and be available from September 3, 2026
• DLSS 5 is exclusive to RTX 5000 GPUs, but Nvidia is working to eventually make it available on older GeForce cards

It's no secret that Nvidia's reveal of DLSS 5 earlier this year led to instant controversy and a backlash from gamers, not to mention game developers. The technology was branded as generative 'AI slop', effectively changing the look and style of character models, notably Leon S. Kennedy and Grace Ashcroft in Resident Evil Requiem.

Since then, Nvidia has worked on developing its neural rendering tech, and DLSS 5 is now ready for launch — and it's arguably being used in the game that's most appropriate for it.

DLSS 5 will debut on September 3, 2026, and will be first available in NBA 2K27 on September 4. The new tech will be exclusive to RTX 5000 GPUs, but Nvidia made it clear that it will explore ways to bring DLSS 5 to older generations of GeForce graphics cards eventually.

At Nvidia's Gamescom 2026 booth, I was treated to a brief hands-on sample of DLSS 5 running in NBA 2K27, on multiple systems including an RTX 5060 gaming laptop and also on GeForce Now.

Much to my surprise, DLSS 5 looks absolutely amazing with NBA 2K27's environments and character models, providing a level of realism that can only be described as the next leap in visuals for gaming.

The level of detail in character faces in terms of lighting and shadows is truly next-level, and it's all possible thanks to AI-enhanced lighting on the rendered frame, which Nvidia states is trained to 'preserve artistic intent'.

When DLSS 5 was first revealed in March, I was bewildered by what Nvidia was attempting, which appeared to be generative AI used to make everything in-game more lifelike. If it wasn't clear already, I have strong feelings against generative AI in gaming, but my initial fears were misplaced, as this isn't what DLSS 5 is about.

DLSS 5 uses three different models, with each including options for structure intensity, tone intensity, and masking. Structure and tone are both responsible for aspects such as ambient occlusion, contact shadows, reflections, and broader lighting.

Masking allows manual or automatic control of where each effect is applied, and Nvidia has designed DLSS 5 for developers to have full control over the final frame that's rendered.

The DLSS 5 model running in NBA 2K27 was fine-tuned directly by the game's developer, not Nvidia, and the result is way different from the first glimpse of DLSS 5 in March. What was illuminating here is that the team at Nvidia stressed that the initial reveal had the sliders for each of those models at maximum levels.

As I saw with NBA 2K27, when put in the hands of developers, it's easier to see just how great DLSS 5 is when used appropriately. Developers will be able to adjust the intensity for each scene for both the environment (foliage and other objects) as well as character models.

Performance is a different ball game too

DLSS 5 isn't exactly easy to run, which isn't a huge surprise considering how realistic the results are. However, Nvidia has made significant progress in six months: DLSS 5 required two RTX 5090 GPUs to function at the initial reveal, and now works with any RTX 5000 series GPU.

The RTX 5060 gaming laptop running NBA 2K27 displayed very smooth performance, only using Frame Generation x2 with DLSS 5 enabled. This was a big surprise to say the least, and suggests that it may not take as long as expected to introduce this new tech to RTX 4000 series GPUs (and older).

My only concern at this stage isn't related to Nvidia at all, in fact. DLSS 5 on its own now looks very useful for producing lifelike visuals, and seems set to be the future for impressively detailed graphics.

Visual Concepts, the developer behind NBA 2K27, has done enough here to quell my fears that DLSS 5 would somehow mess with game art and design direction in a negative way.

However, we're yet to see how other developers will implement the tool in their games. I'm somewhat worried that many could fall into the trap of using DLSS 5 as a shortcut for great game visuals, rather than an added bonus on top of already well-crafted graphics.

I shared similar concerns regarding Nvidia's Multi Frame Generation, and how developers may rely on this very useful tool as a band-aid for poor game optimization.

Fortunately, though, if NBA 2K27 is anything to go by in terms of what to expect from the likes of Capcom, Bethesda, and Ubisoft, then I'm excited to see DLSS 5 implemented in upcoming games. After all, it is an optional game setting, so if you don't like it, you don't have to use the tech.

Nvidia's DLSS 5 has been nothing short of a bubbling cauldron of controversy ever since the next-gen gaming tech was first aired. That initial reception shocked Nvidia as what seemed like a legion of PC gamers took up arms and vowed, well, all sorts of colorful things — most of them involving the term 'AI slop' in some fashion.

However, there are signs that this overwhelmingly negative tide of opinion is turning courtesy of a fresh revelation this week. This comes in the form of a leak rather than anything official from Nvidia, with Team Green's only DLSS revelations at Gamescom 2026 pertaining to the current incarnation of the feature (namely DLSS 4.5 Ray Reconstruction for better quality ray-traced graphics, alongside some interesting GeForce Now announcements).

To refresh your memory and recap — in a nutshell, as there's a lot more to it than this — Nvidia has billed DLSS 5 as a 'real-time neural rendering model' that polishes up a game's visuals using AI (without altering the game assets, and with the developer being given a decent level of control over the exact implementation).

What actually happened here was that on Friday, VideoCardz spotted that following NBA 2K27's early access going live, a DLSS 'neural rendering' DLL was discovered in the build. It didn't take long at all before modders (in the RenoDX community) fudged things to get this working in games ('SpeedLemur' being the principal modder who "made this happen").

So, in theory this is effectively our first glimpse at DLSS 5 in the wild, with those modders demonstrating what it looks like by using the third-person fling-stuff-about action-adventure Control – as seen on Reddit. However, do note that the tech is only working for application to character models for now (not the environment or objects).

Nuts and bolts

There have been some very interesting revelations from those experimenting with this apparent leak of DLSS 5 in terms of how it works, how it runs — and perhaps most telling is the broad reaction to this spillage, which I'll return to shortly.

First, the nitty-gritty. In this leaked form — so add a whole heap of seasoning, because nothing here is remotely official — DLSS 5 seems to have a small set of adjustable parameters, including seven different 'styles' and various sliders to play with intensity, tone and structure. We're told that neural rendering doesn't need much in the way of data to do its stuff, and works off much the same inputs as regular DLSS (basic upscaling – where all this started, remember?).

It's also for Nvidia RTX 5000 GPUs only (although that's still not fully confirmed, it was always likely to be the case anyway). The news on the performance front goes a bit awry, though, with the discovery that in Control the frame rate is cut in half by the AI polishing up the visuals. With an Nvidia RTX 5070 Ti running Control at 4K with ray tracing on high and DLSS (Quality), the frame rate was 71 fps and it dropped to 35 fps with neural rendering.

That is, of course, a nasty hit indeed. However, this is a piece of leaked code – in an unknown state as far as the stage of development is concerned (one clue suggests that the model may date back to the start of July) — extracted and fudged to work on an old game. Given all that, we can't take this as anything like an indication of what the finished version of DLSS 5 might be like performance-wise.

Although it's at least comforting that it works in a playable (enough) manner on a single RTX 5070 Ti graphics card, because if you recall, Nvidia's demos used not one, but two, RTX 5090 GPUs. Clearly a 50% frame rate drop won't fly, granted, but Nvidia wouldn't release this neural rendering trick if the hit was anything like that, because no gamer would use it in that state.

Change in tone

What we can really take from this leak and the modding efforts thereafter is quite limited, then. But what's clear is that as mentioned, there's been a marked turnaround in the commentary and debate on the image quality on offer with neural rendering.

As one Redditor observes: "Remarkable difference in tone of the reactions compared to when the [initial] Resident Evil footage was released."

Someone replying to that says: "People freaked out about what was obviously just a bad demo, and failed to see what was actually going on with the underlying tech.

"There were a few talking about how different tone mapping fixed the issue with minimal effort, or how it wasn't actually adding/changing details, and it turns out they were correct. People freaked out over nothing imo."

Another gamer notes: "This looks like legit magic. I was saying this when the reveal happened and people wanted to burn Nvidia down: the tech is amazing, the demo might be off because it's too heavy handed, but the tech itself is incredibly impressive."

And a further Redditor enthuses: "Insanely huge graphical update. There's no going back."

You get the idea, then, and it's quite an eye-opener how many comments there are along these lines. Quite a lot of gamers are impressed by this leaked spin on DLSS 5 — and I can see why, frankly, at least with the Control material presented here.

And remember, this is with DLSS 5 working on character models, with the facial tinkering and tweaking being one of the main causes of concern with Nvidia's initial demos. The likes of Flight Simulator addicts are positively drooling about what this might mean for the graphics of the landscapes beneath their virtual wings.

And there's a lot of excitement about how the tech might be applied to older games like Control to make them look a good deal better.

Skeptics remain

Naturally, not everyone is convinced. The detractors remain and are unswayed by the material which has popped up around this leak so far. They argue that the AI-enhanced Jesse (Control's protagonist) is still all too 'uncanny valley' in appearance, and that DLSS 5 is still very much a visual downgrade.

Others also worry that there aren't enough fine-grained controls for the developer in what we see here. Although again, we can't take this leak as evidence of what DLSS 5 will turn out to be eventually, whether that's the end result of the graphics themselves or the suite of dev controls under the hood.

The performance hit has been seized on, too — as noted, though we can't judge on that yet, not with an early leak — and some feel that while screenshots might look good, this doesn't hold up in motion.

Simply put: it is still too early to judge, and we need to grab large handfuls of seasoning with all this. But the general sentiment on DLSS 5 appears to be turning around in quite a sizable shift of opinion — and Nvidia may yet convert PC gamers to its AI-enhanced vision of the future (providing any performance hurdles are cleared, of course).

• Intel shows three agentic AI architectures at Hot Chips 2026: the 256-core Diamond Rapids Xeon, the Crescent Island inference GPU, and the already-shipping Wildcat Lake client SoC
• Diamond Rapids matches AMD's EPYC Venice on cores and bandwidth but arrives in 2027 with half the threads, while Wildcat Lake's 17 TOPS NPU falls short of Copilot+'s 40+ TOPS certification
• Intel's Crescent Island will support up to 480 GB via third-party partner cards, but the Intel-branded variant will be limited to 160 GB, even as it currently does not publish the memory bandwidth that determines its token economics.

Intel used its slot at Hot Chips 2026 to lay out three architectures it says will carry agentic AI from the rack to the laptop.

The already-shipping Wildcat Lake Core Series 3 SoC is for mainstream client and edge machines, Crescent Island is an inference-optimized data center GPU, and Diamond Rapids is its next-generation enterprise-class data center CPU that can be configured with up to 256 cores.

Pushkar Ranade, Intel's chief technology officer, said in a statement accompanying the announcement that agentic AI is changing how the company designs computing from the transistor upward.

Plenty of compute promises, sans some GPU numbers

Intel's Diamond Rapids, which it plans to brand as Xeon 7, is where the chipmaker provides the most information, unsurprisingly, in an industry that plans purchases and upgrades years in advance.

Its flagship offering can encompass as many as 256 cores, backed by 1.28G of fast last-level cache, 16 memory channels, 128 PCIe 6 lanes, and CXL 3.0. ServeTheHome reported that the maximum configuration uses 16-core chiplets, built on Intel's 18A-P process node.

Rival chipmaker AMD also offers a 256-core trim: the EPYC 9996, built on TSMC's 2nm node, keeps hyperthreading in play, effectively doubling its thread count versus Intel's flagship.

Its Crescent Island GPU is arguably the most interesting design of the three, but the least detailed: a 350W air-cooled PCIe card built on its Xe3P GPU architecture, with 32 cores feeding 256 third-generation XMX engines and 32 MB of unified L2 cache. It surprisingly uses LPDDR5X rather than HBM, but the choice seems rationalized to offer capacity at a power and cost profile that lets Intel compete meaningfully with Nvidia and AMD.

Interestingly, the 480GB figure Intel touts in its press release isn't what it will ship; Intel-branded cards cap at 160GB, and 480GB is a ceiling available to ODM partners building their own configurations. Intel also remains mum on memory bandwidth specifics and told Chips and Cheese it won't disclose the figure; this is crucial for many AI applications, as memory bandwidth determines decode throughput, and decode throughput essentially determines token economics.

Of the three architectures that Intel talked about, Wildcat Lake is the only one you can pick up off a shelf (as a miniPC or laptop) today; it launched as Intel's Core Series 3. Intel stated that it replaced the Foveros packaging used in Panther Lake with an organic multi-chip package, eliminating the base die and, with it, assembly cost and yield loss. Compute die area fell by 38 percent, and I/O tile area by 15 percent.

The 17 TOPS NPU available to such CPUs sits well below the 40 TOPS Microsoft requires for Copilot+ certification. The 40 TOPS Intel cites is a platform total across CPU, GPU, and NPU, which arguably can be met elsewhere, but it's a sticking point for the chipmaker's AI push, which has otherwise been concentrated on capturing enterprise and hyperscale customers.

• Nvidia GPUs are about to run out of road in Windows 10
• Game Ready Driver support finishes in just two months
• With the last such driver coming in October, you need to bear in mind issues around game performance optimization and fixes – but you'll still get security updates

Gamers running Windows 10 need to be aware that if they have an Nvidia GPU, they're only two months away from that graphics card running out of road for support with drivers.

VideoCardz reminded us that Nvidia's deadline for ditching Windows 10 support is now nearly upon us, with the final Game Ready Driver that supports the older operating system arriving in October 2026.

Does that mean you need to be thinking about upgrading to Windows 11 if you have an Nvidia graphics card?

No, it doesn't – well, not necessarily, although there is a major downside to remaining on Windows 10 after October of this year. In case you're at all unsure, let's dive into the exact ins-and-outs of what's happening here – as well as touching on the subject of whether Nvidia might just have a change of heart here.

You'll still be secure with an Nvidia GPU

The key point to remember is that while the Game Ready Driver that comes out in November 2026 won't support Windows 10, Nvidia will still provide security updates for your graphics card. As Team Green explained in a short FAQ: "Windows 10 driver support will transition to a quarterly security update for a period of three years where critical bug fixes will be delivered to end users through October 2029."

That means Windows 10 users will get an update every three months to fix any critical bugs or security flaws with the Nvidia drivers. This will continue for another three years, so effectively to the end of the decade.

At that point, when 2030 is about to roll around, you will then potentially be risking exposure to a vulnerability as any driver security holes will no longer be patched. But that's still a good long way off.

So what does the end of Game Ready Driver support really mean?

After October, Windows 10 PCs will only get the benefit of these quarterly security updates, and they won't be covered by Nvidia's regular Game Ready Driver packages. That means as new games come out, Windows 10 users won't get the performance optimizations that these driver releases contain – or bug fixes for these titles.

As time goes on, then, more and more PC games will be left out in the cold in terms of that tweaking and optimization. That's bad news, of course, although it doesn't mean those games will be somehow unplayable. In fact, in many cases they might be just fine – but there are no guarantees, and you may get subpar frame rates (indeed, that's quite likely to be the case to some extent).

Of course, existing games will continue to run just as they always have, and you shouldn't run into any issues on that score.

Could there yet be a reprieve from Nvidia?

If you're not happy about the idea of not getting the latest patches, tweaks, and optimizations for new PC games, then you'll have to seriously start to think about planning your upgrade to Windows 11.

Assuming you have an upgrade path, that is, because your PC may not meet the hardware requirements of the newer OS. (Although bear in mind that a simple BIOS tweak may be all that's needed to ensure compatibility with the TPM requirement). If you're looking at a major PC upgrade, or an entirely new rig, that's a painful prospect given the RAM crisis and all the price hikes around that.

As one Redditor puts it: "'This is terrible news considering PC prices."

However, as another gamer on that Reddit thread observes, there may yet be a glimmer of hope of a reprieve from Nvidia. If you recall, just a couple of months ago, Microsoft quietly extended consumer support for Windows 10 for a further year, through to October 2027.

Now, when Nvidia announced the end of driver support for October 2026, which happened last year, as far as Team Green was concerned, it was aligning the curtailment of Game Ready Driver releases for Windows 10 with Microsoft's original consumer support extension. But now Microsoft has pushed out extended support for another additional year to October 2027 – could Nvidia mirror this move?

It doesn't seem likely, in all honesty, and I'd think Nvidia would have announced this already if it was the intention. Concrete driver plans are likely already in place that can't be changed. That said, you never know – and we can't fully rule out the notion of a last-minute reprieve. Watch this space.

• Windows 11 can remove a discrete GPU driver as part of its clean-up routines, as shown on Reddit
• This can happen if the laptop has been in Eco mode for an extended period
• Because the GPU is effectively gated off from the system, the driver is marked as unused and therefore deleted by the OS during clean-up – but you can stop this from happening

Apparently, Windows 11 can end up stripping away the discrete GPU driver from your laptop in certain scenarios if the OS is left to run in Eco mode for a long time – and that's a distinct annoyance if you own a gaming laptop, as per a report on Reddit.

Wccftech spotted a Redditor who posted about their Asus ROG Zephyrus G14 gaming laptop with a discrete Nvidia RTX 5070 Ti, and how Windows turned off that GPU.

At this point, some of you may immediately be thinking: who runs their gaming laptop in Eco mode? And that's a fair point, and one raised in the Reddit thread – I'll come back to that.

First, let's look at the mechanics of how this works, based on the Redditor's investigation of what went on (they noted that it "took me months to work this out"). When the laptop is put into Eco mode, power is completely cut to the discrete GPU, effectively leaving it offline (just as if it were an unplugged USB stick, as the Redditor describes).

That's not a problem – obviously it's a power-saving measure – but the issue is that Windows 11 runs a driver clean-up process from time to time as part of routine system maintenance. By default, this happens every 30 days, though the Redditor notes their laptop was set to 15 days, and this can be modified.

What happens is that if the laptop has been in Eco mode for a long time, with the GPU effectively walled off and not present as far as the system is concerned, and the clean-up happens, it judges the driver to now be superfluous, and it's removed.

When Eco mode is subsequently switched off, the driver doesn't return – it remains ditched, and the GPU shows as a 'Microsoft Basic Display Adapter' instead of an Nvidia GPU in Windows 11's Device Manager.

The Nvidia graphics driver must then be reinstalled to get the GeForce graphics card functional again – and the same is reportedly true of AMD discrete GPUs.

Analysis: a niche problem, but an annoying one – here's how to avoid it

Let's return to that question: who runs a gaming laptop in Eco mode? No gamer really does this, at least not when they're regularly playing some of the top PC games on their notebook. However, someone might be a student cramming for finals and using the laptop for work, having given up gaming distractions for a few months. In this case, with Eco mode enabled to keep battery life up while studying, Windows 11 could disable the GPU.

Okay, so it's something of a niche situation – and the Windows 11 clean-up routines are useful for keeping the system streamlined. But it's not an unthinkable scenario, and Microsoft's OS should be tuned to be more careful around GPU drivers – and it'd be useful if the system could give a warning of such a clean-up happening (so it could be avoided).

That said, this may not happen in all situations. Another Redditor notes that they have had their Zephyrus G16 in Eco mode for two months, and the Nvidia RTX 5070 Ti is still present and correct.

Whatever the case, if you run into this problem yourself, at least you know why it's happening. The fix is to simply reinstall the Nvidia driver, although the same thing could happen again if you're one of those people who regularly uses Eco mode on your gaming laptop.

You can apply a Registry fix to permanently stop the clean-up process, but I wouldn't recommend messing with those settings unless you're confident (see the Reddit post for instructions). Also note that you'll miss out on other clean-up duties, not just GPU-related activity.

A better solution is to simply remember to take your laptop out of Eco mode now and then (every couple of weeks), which will bring the discrete GPU back into play, and save the driver from being earmarked for removal.

The Redditor notes: "Or just keep the GPU visible now and then. Optimized mode in G-Helper turns the dGPU [discrete GPU] on whenever you plug in. Flipping to Standard [mode] every couple of weeks does the same thing. Resets the counter, no Registry editing."

• GPU price hikes are coming later this year, PC Partner Group warns
• The parent company of Zotac notes that entry-level GPUs will suffer 'more severe shortages'
• A manufacturer of gaming monitors, KTC, has also warned on price hikes

PC gamers should be aware that there are further signs that GPUs could get more expensive, and gaming monitors too, so you might want to consider buying now rather than waiting.

First off, the gloomy GPU news which comes from PC Partner Group (PC PG), an Asian graphics card giant based in Singapore and the parent company of Zotac, Inno3D, and Manli.

VideoCardz reports that PC PG just published its latest fiscal results that came with a warning on GPU pricing as part of the trends and conditions which are likely to affect the company's finances in the upcoming year.

PC PG notes that "graphics memory costs are expected to rise further, leading to a substantial increase in VGA Card costs in the second half of the year." VGA Card simply refers to discrete PC graphics cards, and although it's a well outdated term now, it's one still used behind the scenes in the industry.

PC PG says that shipments of GPUs "declined substantially" in the first half of this year, and that they're likely to drop further in the second half of 2026. The firm writes that: "Beyond the price increases, entry-level VGA Cards are expected to face even more severe shortages, which may further drive ASP [the 'average selling price'] upward in the second half of 2026."

The company also highlights that other PC components, including system RAM and CPUs, are taking longer to get hold of.

VideoCardz also noticed that monitor pricing could be on an upward trajectory, too, as manufacturer KTC has issued a notice of a likely 'product price adjustment' in the future.

KTC observes that the "production cost of monitors has increased significantly" and that it can no longer absorb those pressures, therefore: "KTC's monitor product line may see a price increase in the future."

While that's just a 'may' rather than a 'will' or a certainty, it sounds like there's a high likelihood of it happening. Particularly because KTC advises: "For users with a clear need to purchase a device [monitor] in the near future, the current pricing window offers excellent value for money, and we recommend planning your purchase time accordingly."

And at the end of its statement, KTC talks about price adjustments being a "necessary measure", so it sounds pretty much like they're coming no matter what.

Analysis: is anything immune to the component crisis?

This isn't the only warning on monitor price increases, as AOC recently said that the rising cost of components for its products will mean price hikes starting from this month. Is this the start of a growing trend? The bigger monitor producers will, of course, have more financial wherewithal to weather component rises, but it may only be so long before even those firms start to jack up prices.

The way things are going, I wouldn't bet against it, and this latest news has people on social media asking what isn't immune to the RAM crisis – and what might we expect to see hit next?

How about pricier PC cases, one Redditor jokes: "Wouldn't you enjoy a simple case costing like $300?"

The crisis does feel rather relentless at this point, but the clearest worry is now GPUs. PC Gamer is tracking graphics card prices on a weekly basis, and there have been some clear cost increases coming through in the last few weeks, which suggests that PC PG's prediction is on the money here. And there are multiple other rumors of late warning that graphics cards are set for considerable price hikes. For me, this noise is becoming too consistent to ignore.

As I recently advised, if you need a graphics card upgrade, or think you will in the next year or two, I believe now is the right time to get in and buy. It's particularly notable that according to this latest rumor, entry-level GPUs are mentioned as apparently coming under more pressure, meaning that mainstream buyers are going to be suffering.

The effects of pricier video RAM, and other pressures besides, are no longer going to be mostly about high-end (or 16GB) cards becoming ridiculously expensive, and we could see some unfortunate hikes with lower-end GPUs.

There's very little good news of late across the gamut of PC components, and as we've already seen today, RAM and SSDs are getting even more expensive.

It appears that the RAM crisis is getting worse than ever as we head further into 2026. I've been closely watching and reporting on memory price hikes — which were soon followed by other PC component cost increases — since this crisis first began, and the worrying thing is, I can't recall a gloomier stream of negative news than I've witnessed over the past few weeks.

That includes Samsung recently declaring that the RAM crisis is going to become more severe in 2027, and rumors that even mighty Apple is floundering in its attempt to secure new RAM supplies from China (as other notebook makers consider this alternative route to the three main memory chip giants: Micron, Samsung and SK Hynix).

Previous to that, we saw laptop maker Framework break news of a truly eye-opening cost increase for mobile RAM, just as one gauge of DDR5 pricing saw it jump in price to a new all-time high (after plateauing earlier this year). On top of that, the boss of SK Hynix voiced the opinion that 2027 will be the worst year in the RAM industry's history, and that the crisis is likely to be drawn out to the next decade.

This isn't just about RAM, of course, but other components, including CPU price rises, and devices themselves — PCs and laptops (and phones). But most notably over the past month it's been graphics cards in the crisis limelight. We've witnessed the resurrection of old GPUs to try to bolster stock levels of more affordable cards, and more recently we've been subjected to what seems like an endless parade of negativity about imminent price hikes.

Apparently, Gigabyte is set to increase the price tags of its graphics card to the tune of 20% to 40% in Japan, and MSI is going to jack up prices of Nvidia GPUs in China by 20% or more. Asus is supposedly preparing a similar 20% hike (as Wccftech reported).

Another recent gloom nugget is the assertion that Nvidia RTX 5000 models will get hikes of 30% in South Korea this month, and all of this pain is mainly rooted in the increased price of video RAM, of course. (Those cost increases are the reason the RTX 5000 Super refreshes have been delayed, according to the grapevine, as those rumored cards are packed with VRAM).

While a good deal of this is individual pieces of regional activity with GPU pricing, it's obvious that these hikes are happening as part of a concerted shift, one that will surely be reflected globally — it's not like Asian markets are in a bubble of their own.

The overarching theme is a worsening of price hike misery, and that the pricing storm is likely to intensify this year, and probably in 2027, too. While previously the RAM crisis has been more of a light-and-shade affair, now it feels like the depression has been turned up a notch. Whereas before, there was certainly more darkness than light, we've had notable spots of relief where an exec in the memory industry stepped forward and theorized that maybe things aren't as bad as we think. But lately those embers of optimism appear to have burned out.

To me, it feels like there's a shift underway towards a full acknowledgement that we really are going to experience a lot more pricing pain in the foreseeable future. If it's so bad that even Apple is purportedly scrambling to secure RAM supplies, and is having trouble doing so, I think it's time to turn up the worry meter by a notch or two.

What should you do?

Here's my advice on the current landscape with PC components and hardware (season it appropriately). Obviously, worrying isn't going to help you, but awareness of what might be sensible upgrades or purchases to make now will, based on the likelihood of hikes (we could call it the 'hike-lihood' – or maybe not). Nothing is certain about the future of components, of course, but it does feel like there's a clear area in which the potential price hikes are a bigger threat: GPUs.

As I discussed above, there's a lot of recent evidence that graphics card pricing is going up. Yes, it's a collection of rumors in the main, but there's a lot of it all pointing in a very similar direction — and a video RAM toll was always going to be exacted in the end. We've seen it already with higher-end graphics cards, and now I believe we're going to see it in the mid-range, and even budget models. Indeed, top-end GPUs are likely to get even more expensive as well.

If you're thinking about a GPU upgrade for this year or next, given all this, I think now really is the time to buy — especially with a lower-tier model, as you can still get more affordable graphics cards at their MSRP. Ditto for mid-rangers, although it's tougher to recommend higher-end Nvidia boards when they are already so expensive.

As noted, though, that could get worse. And granted, you may still want to wait for Black Friday — it's not that far off, and there might be some GPU deals then. However, I wouldn't bank on anything hugely compelling (or discounts that aren't offset by the price rises which are predicted to take hold in the next few months).

So, if there's one PC component that I think you should buy now, it's a graphics card. I think the signs are pretty clear on that (and see here for my recommendations on different models to consider). By extension, higher-end gaming laptops could also be a wise move for purchasing sooner rather than later. That's for the same reason, really — they have beefy (mobile) GPUs (with plenty of VRAM in some cases).

I don't think it's a bad move to buy any laptop, by the way, gaming or not (away from the higher-end), come your earliest window of opportunity. I think we'll see further price rises here, too, and RAM is going to cause more upward pricing pressures for notebooks — just look at Framework's recent revelation as mentioned.

What about RAM and SSDs themselves? While system memory kits and storage have already seen huge price rises, it now looks like there's worse to come (somehow).

On the other hand, there's a ceiling as to how expensive this stuff can get before buyers withdraw from what they see as an increasingly unrealistic and out-of-touch market. This is a much more difficult call to make, but if you can find something that looks relatively reasonably priced, I don't think you'll regret the purchase in the next couple of years. But that said, I can't recommend a RAM upgrade in particular at current pricing levels, unless it's unavoidable, frankly.

Above all, though, consider a GPU upgrade if you're in the market for a new card, or you think you'll need one in the next couple of years (yes, I think it's wise to be looking quite far down the road here).

The other thing to bear in mind is that there's a danger there will be a rush for GPUs, a flurry of buying that puts further strain on supply and therefore prices. As VideoCardz reports, one Japanese retailer has warned of Nvidia RTX 5000 graphics card sales increasing "sharply", even just with the news of rumored price increases — let alone the confirmation. Prices are already rising and restocks of the RTX 5070 Ti and RTX 5080 are already being labelled as "unstable", hinting that inventory could start to dry up quickly.

That's just one report, of course, and it pertains to the high-end of the market, so it's not something to start panicking about yet. But it does make some sense that if pricing begins to creep up, more PC owners may start to act on GPU upgrades. I wouldn't blame them, frankly.

• Someone made a tool for Asus Astral RTX 5080 and 5090 GPUs
• It's designed to prevent a melting connector, shutting down the PC before this happens
• This third-party utility – and the response to it – shows the level of paranoia out there when it comes to this issue

Do you have a high-end Nvidia Blackwell GPU, and if so, are you worried about the perils of a melted power connector? It appears that definite concerns remain in this area, to the point that a new utility has been crafted to address those worries.

An enterprising Redditor has made their own open source tool for Windows which is designed for Asus Astral RTX 5090 and 5080 graphics cards, acting as a monitoring app that will (hopefully) step in to prevent any melting disasters before they happen.

The creator, Humza Khalid, tells us how the small utility, which is available to grab on GitHub, works: "It reads per pin 12VHPWR current straight from the card's own sensor chip and force shuts down your PC if any pin stays over 9.5A for 15 seconds, before the connector can melt."

The idea is that it's a lightweight and standalone app which is an easy way to defend against the situation where there's a sustained level of too much current flowing to the Nvidia graphics card.

As noted, the PC is forced to shut down in these cases (in a safe manner, with any running or interfering apps being force-closed, we're told), before any damage is done.

The creator has taken a suggestion on board from the comments, and Khalid notes that the tool will be changed from initiating a shutdown to dropping the power limit (via the Nvidia management API) for a much faster response. (Shutting down can take a while). That change will happen in a future version of the utility, Khalid tells us.

The creator also reminds us: "This only works on Astral 5080/5090 cards because those are the only ones with per pin sensors. Windows only, needs Python. And it doesn't replace seating your connector properly, it's a last line of defense not a first one."

Analysis: default paranoia

That's all good in theory, of course, but I'd always be careful about what you're installing on your PC. Not to say this isn't a trustworthy app – I don't know whether it is or not, and that's the point. However, it is open source, so that's good, as it provides visibility into what it's doing under the hood.

Another point to note is that a co-creator of the app is listed as 'Claude', meaning that this AI has been used in making the tool. Khalid explains that they wrote the original utility, but it was based on HWiNFO, so they wanted the app rejigged to be standalone, and Claude "did a lot of the rewrite".

At any rate, Asus Astral GPU owners can make their own decision about what's worth installing, or not, although I wouldn't personally recommend installing a third-party utility from an unknown developer. As ever, if you do install such software, you do so very much at your own risk.

Regardless, what this does show is the clear level of concern about Nvidia's RTX 5090 and 5080 GPUs. One Redditor sums it up: "As a 5090 owner, I can confirm the card comes with a default paranoia about bursting into flames."

That received some pushback from other Redditors who said their overclocked RTX 5090s were just fine, and in turn, there was a further story relayed about a melting incident. Obviously, all that is anecdotal (on both sides of the coin), but the paranoia is real enough.

Cable melting worries began with the RTX 4090, of course, before the RTX 5090, and when we looked into the issues with the Blackwell flagship back at the start of last year, Nvidia firmly denied that any of this is its fault. Cable melts remain a controversial topic, though, and more recently we've even had a report of an exploding RTX 5090, no less, which PC gamers who run these high-end graphics cards probably didn't take much comfort from.

• MSI's Nvidia GPUs are rumored to be getting price hikes
• They'll be 20% more expensive (or worse) in China, and that kind of increase will surely be seen elsewhere
• This is happening against a backdrop of wider price hikes for graphics cards – although Nvidia is offering a rare chance at an RTX 5080 or 5090 at MSRP

As fresh rumors reveal that another graphics card maker is set to hike prices, Nvidia has a plan to let you buy a Founders Edition Blackwell GPU at the MSRP, even in the case of the RTX 5090 — although you'll need to travel.

And you'll need to move very fast, attend QuakeCon in Texas, which starts today, and get yourself to the GeForce booth (hat tip to VideoCardz) before supplies of RTX 5070, 5080, and 5090 Founders Edition graphics cards run out. And I don't think that they will last for long (a matter of minutes, at a guess, although hopefully that won't be the case).

Nvidia describes this as 'Verified Priority Access' in real life, and at least it does give gamers a chance to buy an RTX 5080 and 5090 at the intended price, which is not something you can get anywhere near when purchasing one of these high-end Nvidia GPUs at retail.

As for the most recent news on GPU price hikes, Wccftech spotted that MSI is the latest graphics card maker to announce that its products will be considerably more expensive.

This is just a rumor, one that arrives via the Board Channels in China, and so should be served with some seasoning — but the theory is that MSI's Nvidia GPUs are set for price hikes of 20% or more. This is due to rising memory prices, of course, and what Nvidia charges its partners for video RAM modules (as Team Green is paying more, it passes that bill on, of course).

The price increase is in the order of $300 (£220 / AU$420) for the RTX 5080 over in China (converting from RMB), around $200 (£150 / AU$280) for the RTX 5070 Ti, and approximately $100 (£75 / AU$140) for RTX 5060 models (and not far off that for the RTX 5050).

Sadly, not only will current-gen Nvidia GeForce graphics cards be affected, but also RTX 4000 and 3000 models (with GDDR6 video RAM getting costlier, as well as GDDR7).

Analysis: pricey times

While this is a rumored cost increase for MSI products in China, these exact same pricing pressures are, of course, happening globally, so there's no reason to believe that MSI's GPUs in other regions won't follow suit.

What's more, this isn't just a problem that pertains to MSI, but Nvidia's other card-making partners, and those companies are also rumored to be implementing hefty price hikes. For example, just this week we've heard that Gigabyte GPU prices will jump between 20% and 40%. Also, on a regional basis, Nvidia RTX 5000 models in South Korea are looking at price hikes of up to 30%.

So, this is a coherent picture of hikes, and those percentages are all in a similar ballpark, indicating increases of at least 20% or a good deal more. They are also backed up by more general chatter from the grapevine about Nvidia's VRAM increases and AMD's Radeon GPUs becoming pricier.

I fear that getting any kind of current-gen graphics card at, or near, the MSRP could be a much tougher task before long, and those at QuakeCon better make the most of Nvidia's GeForce offerings at the firm's booth. As noted, I expect this to be the definition of a flash sale — as in they'll be gone in a flash — although you do have another shot at winning an RTX 5070 in the Quake III Arena RTX Remix and Doom: The Dark Ages challenges.

• Gigabyte graphics cards are rumored to be set for a big price rise
• It could be a hike of 20% to 40%, and other rumors are also pointing to major price hikes for GPUs more broadly
• This means now is likely a good time to make a purchase, particularly with certain cards which have avoided the worst of the hikes so far

Desktop GPU prices are set to rise if the rumor mill is right – with yet another prediction to that end being aired – and while graphics cards are already costly in some cases, now might be the time to buy certain models, based on a fresh roundup of average pricing.

First off, let's deal with the latest gloom nugget from the grapevine regarding GPU pricing, courtesy of @momomo_us on X (via Wccftech) who picked up a notice from CFD (a Japanese components supplier) warning of substantial price hikes on Gigabyte graphics cards.

The claimed rise (add seasoning, of course) is in the order of 20% to 40%, so at the latter end of that scale, we're looking at prices shooting up by almost a half in some cases. Existing orders from retailers buying boards from CFD may even be cancelled, the notice states.

I perhaps wouldn't put as much stock in this, except that it echoes a rash of recent reports contending that large price hikes are about to happen in the GPU world, which makes it all the more believable.

Only yesterday I reported on the situation in South Korea where RTX 5000 models are rumored to be getting price increases of up to 30%. So again, that's a hefty hike, and it follows other speculation about Nvidia charging its partners more for video RAM (which will push up costs, of course).

This apparent Gigabyte move will affect both Nvidia and AMD graphics cards in Japan, and there have been rumors about Team Red having Radeon price hikes in the pipeline due to more expensive VRAM, too. That only makes sense, as if VRAM is getting more costly for Nvidia, it will be for AMD too. And while some of these reports are based on regional activity, the cost issues will surely apply globally – none of these markets exist in a bubble.

Analysis: I think it's time to buy – especially with certain GPUs

The RAM crisis has a lot to answer for, and it very much looks like graphics card prices are going to be jacked up considerably during the remainder of 2026, with video memory being the primary driver here. Given that, it seems that if you are thinking about a GPU upgrade, now is likely the time to go for it, rather than waiting and being hit by price hikes.

That's especially true if you're considering a 16GB graphics card (as more gamers are these days), as the products with more VRAM are going to get hit the hardest for price rises as memory modules become even more expensive.

If we want a snapshot of the current GPU market as price tags stand, fortunately enough, TechSpot has just furnished us with an extensive (multi-region) pricing roundup as of the end of July which highlights some key points.

Firstly, low-end GPUs are still relatively unscathed, with offerings like the RTX 5050 and RTX 5060 8GB, and the 8GB spin on the 5060 Ti, not having been bumped up by all that much in the RAM crisis thus far. However, as for the 16GB incarnation of the RTX 5060 Ti, that has seen major price bumps, reinforcing that observation on 16GB pain (this card is up over 40% since November 2025 in the US, for example – and shows a 14% rise since April 2026).

In the tier above that, the RTX 5070 is holding at a reasonable price, and even if the sub-MSRP levels of late last year are well and truly gone, it remains a decent buy. (As long as you can stomach 12GB of VRAM at this price bracket, of course – and that's one of the reasons why this GPU hasn't been hit so hard, no doubt).

Above this level, Nvidia GPUs have witnessed some of the nastier price increases, as you've probably noticed.

On the AMD side, matters look more promising, particularly in the case of the Radeon RX 9070 and RX 9070 XT, with TechSpot finding that the 16GB models in the RDNA 4 family haven't suffered as much as Nvidia's GeForce offerings. The price of both these 9070 models has remained steady over the last few months, and in many regions, they're only up 10% or so compared to late 2025. (The 9070 XT is an exception in the US, mind, where it has risen by closing on 20% since last year).

If you're inclined towards one of these Radeon mid-rangers, or Nvidia's RTX 5070, I'd strongly suggest you buy now rather than wait based on what we're hearing from the rumor mill. Lower-priced graphics cards are likely worth grabbing, too, because they may be heading upwards in the pricing stakes before long – although notably the RX 9060 XT with 16GB has already become a good deal more costly, much like its RTX 5060 Ti 16GB rival.

As noted, Nvidia's higher-end graphics cards (RTX 5070 Ti and upwards) have already been hit with alarming price hikes, but they're likely to get even worse. So, this could be a case of keeping your wallet shut and holding out for possibly a lengthy time, as I can't really recommend them even at the current pricing.

The trouble is, we don't know how long the RAM crisis will continue, and some of the guesswork on that front is very bleak indeed – suggesting it might be the rest of this decade effectively. At this point, I'm inclined to believe we're in it for the long haul with PC component pricing woes, which is why I think it's best to buy a GPU now, at least with the mentioned models, assuming you're in a position to do so.

• The latest Steam survey shows GPUs with 16GB are the most popular
• They're on 25.9% and have overtaken 8GB GPUs which are just behind on 25.32%
• There's been quite a shift towards 16GB boards over the past year, but with news of more price hikes incoming, upgrading to this loadout could be a painful process for gamers

Graphics cards with 16GB of memory are the most popular GPU among Steam gamers now, although the way GPU prices are going means that people aiming for a board packing plenty of video RAM (VRAM) are looking at a rather depressing future.

TweakTown spotted that the latest Steam hardware survey for July shows that 16GB of VRAM is the most prevalent memory configuration at 25.9%, up 1.4% over last month. That means it just dethrones the previous top of the VRAM table, which was 8GB, a loadout that slipped slightly from last month down to 25.32%.

There's not much in it, of course, but nonetheless, it's a telling stat (bearing in mind the usual caveats about variance in Valve's hardware report based on how the survey is distributed).

Of course, the majority of Steam gamers are still running with less than 16GB, and only 36% have a GPU with 16GB or more. So, almost two-thirds are running less than 16GB, and just under half (47%) have a graphics card with 8GB or less.

But it's a hefty rise in the count of 16GB GPUs when you consider that less than a year ago, in August 2025, just 6.8% of Steam gamers had boards with that VRAM loadout (based on a Notebookcheck report from the time). Compared to July 2026, that's nearly quadruple the number of 16GB-equipped rigs, with a close to 20% increase — pretty eye-opening.

Analysis: 16GB ambitions and the ever-worsening RAM crisis

It seems that, at least based on Steam's stats, RTX 5060 Ti 16GB and RX 9060 XT 16GB graphics cards (and 9070 models) must have been selling well — and of course higher-end Nvidia cards. The RTX 5070 is doing well for itself, too, and is now in third position in Steam's GPU ranking (although that's a 12GB offering and it should really be 16GB).

The ranks of the 16GB GPUs on Steam will also be bolstered by older models, of course, from past generations. Also, the visibility of AMD Radeon graphics cards with 16GB of VRAM was improved by Valve earlier this year, when an issue was fixed whereby these cards were misreported (not detected and lumped in a generic Radeon category), so that will have boosted numbers too.

At any rate, the fact that more gamers are looking at future-proofing their GPU purchases only makes sense, as 8GB in particular is looking too lean at this point. But there's a problem with GPUs that have heavier VRAM configurations, and this is, of course, that the memory crisis hits these models hardest.

We've already seen that GPU price hikes are making themselves felt, and just a couple of weeks back, Nvidia seemingly told its card-making partners that the price it charges for memory supplied with its graphics chips is going up (for both GDDR6 and GDDR7). A fresh report from Tom's Hardware also talks about price hikes for RTX 5000 models in South Korea beginning this month, driven not just by the increased cost of video RAM, but also the GPU chips themselves.

We're told the upshot is that Nvidia's Blackwell GPUs could see price increases of up to 30% in the country, and similar hikes may happen elsewhere. AMD price hikes are expected for its Radeon line-up, too, and Team Red has already warned us that the second half of 2026 is going to be a tough one for PC gamers.

With those gamers craving 16GB of video RAM more often, and prices heading inexorably upwards — and the memory crisis expected to worsen as this year rolls on, with the misery to continue into 2027 by all accounts — it's a gloomy picture for beefier graphics card upgrades.

Enterprise DevOps teams have adopted AI faster than they have adapted the operational systems that support it. Large language models generate Infrastructure as Code, deployment pipelines, and configuration files in seconds.

Development teams are delivering infrastructure changes at a pace that would have been implausible five years ago. Production environments have simultaneously become harder to reproduce, more difficult to govern, and more expensive to operate.

The problem is easy to miss at first, because AI looks like a clear win in the early stages. A team asks an AI tool to set up some infrastructure. It works. The team expands how much they rely on it. More teams follow. More infrastructure gets created for testing, demos, experiments, and development. The organization ends up with far more moving parts than it had before, but far less ability to track them.

Not the full picture

The tools generating this infrastructure are good at describing what something should look like at the moment it's created. They're not built to watch what happens to it afterward, decide whether it's safe to make another change while one is already in progress, or notice when something has quietly drifted out of its intended state over the following weeks.

That kind of oversight used to come from experienced operations people making changes one at a time, in a predictable order, with a clear sense of what else was happening around them. AI removed the slow part of that process without replacing the judgment that made it manageable.

Now there are multiple people and multiple AI tools all making changes to the same systems around the same time, each one doing its job correctly in isolation, none of them able to see the full picture of what's happening across the environment as a whole.

The result looks familiar to anyone running infrastructure today. Environments that worked perfectly last week suddenly don't, and nobody can say exactly why. Cloud costs creep up steadily because nobody remembered to shut something down once it was no longer needed. Teams spend real, billable hours figuring out why two environments that were supposed to be identical have quietly diverged.

Security settings that were correct at launch slowly fall out of sync as everything around them keeps evolving independently. None of these are dramatic failures on their own. They're slow leaks, and slow leaks are much harder to notice and much more expensive to fix than sudden breaks.

Too much fragmentation

The teams responsible for infrastructure have been adjusting to this reality in real time. A few years ago, their main job was making things easy for developers, such as removing friction, giving people self-service access to what they needed, getting out of the way. That's still part of the job, but the role has expanded considerably.

Now they're expected to enforce rules across the organization, manage costs on increasingly expensive compute, track what's actually running where, and keep things consistent across a far more complicated set of environments than existed even two or three years ago. Bolting on another automated tool to handle some piece of that doesn't solve the underlying issue.

More often than not, it just adds another piece to a pile that's already too fragmented to manage well.

An environment isn't just the infrastructure sitting inside it. It's also everything connected to that infrastructure: who has access to what, what depends on what else, how much it actually costs to keep running, and how long it's supposed to stick around before someone should be cleaning it up.

Getting ahead of problems means building that kind of awareness directly into how infrastructure gets deployed and maintained, rather than discovering issues after the fact through documentation nobody reads regularly or incidents nobody wanted to have in the first place.

Processes should be built in

This becomes even more important as companies pour money into AI-specific hardware. Setting up GPU-powered environments isn't simply a matter of securing the hardware, it requires everything around that hardware, including networking, storage, security, and software, to come together correctly and stay that way.

Having the hardware on hand doesn't make that coordination problem any smaller. Only better processes do, and that process has to be built deliberately rather than assembled from whatever tools happened to be lying around.

The questions worth asking have changed as a result, even if a lot of organizations haven't caught up to that yet. How fast a team can generate infrastructure isn't the most useful thing to measure anymore and it was never really the hard part.

A better gauge is whether environments stay consistent over time, how often things drift without anyone noticing, how long unused environments sit around quietly costing money, and whether anyone in the organization can actually describe with confidence what's running in production at any given moment.

The companies that get the most lasting value out of AI won't necessarily be the ones using the most advanced or most numerous tools.

They'll be the ones that put just as much disciplined effort into managing what AI produces as they did into producing it in the first place and treating governance not as an afterthought, but as the thing that determines whether all that speed actually turns into something worth having.

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Racing to scale AI requires massive capital investment in data centers, with McKinsey recently estimating that global data center spending could reach $7 trillion by 2030. Perhaps more importantly, though, scaling AI requires massive architectural investment from a technology standpoint.

Modern data center infrastructure was not designed to power the cloud computing revolution and the massive surge in AI usage and development on a global scale simultaneously.

This architectural strain is driven by rising expectations – the more AI is adopted, the more demand of it there is. Enterprises are excited by AI’s promise as a time-saver that can automate and streamline employee workflows and increase productivity. To facilitate the growing complexity of AI models and datasets, GPU density and bandwidth have increased in data centers.

These increases mean AI models that can be trained faster, have lower latency interference and more. As these chips and data centers continue to increase the amount of data transferred between chips, though, cooling efforts are also needed to make sure the chips and data centers do not overheat.

As a result, while today’s data centers continue to power the AI boom, their operational runway is quickly shortening. Powering AI and the growing demand for AI capabilities is incredibly resource intensive. The technology relies heavily on electrons for computational capabilities and for moving data between chips in larger AI models. This requires vast amounts of electricity, water, rare materials, and overall technological innovation.

As operational bottlenecks persist, silicon photonics has proven an underappreciated solution to help further advance AI. Using light combination with electrons, silicon photonics enables faster, more energy-efficient data transmission. These abilities can both advance AI and scale GPU clusters and AI data centers.

The SiPh adoption delay

Photonics have been around for decades, spanning more than 40 years of research and innovation. In the 1980s, researchers realized the technology's potential due to its ability to allow the integration of photonics and electronics on a single chip.

Where before, photonic and electronic components lived on two separate chips that had to be combined, silicon photonics made it possible for both components to be functional on one single chip, resulting in increased speed, bandwidth, energy efficiency and more.

Today, silicon photonics are integral to the commercial production of communications transceivers in data centers. Fiber-optic communication predates the current AI wave by an entire generation, as does the basic principle of transmitting data as light rather than an electrical current.

The challenge of leveraging this technology in a broader setting, however, has always been its manufacturability and the need for optical components to be small and cheap enough to compete with legacy conventional solutions.

Complementary metal-oxide-semiconductor (CMOS) compatibility makes this possible.

CMOS

Silicon Photonics-based circuits converts electrical signals into optical ones, transmits them as infrared light pulses through microscopic waveguides etched into silicon, and converts them back to electrical signals at the destination.

CMOS platform unlocks efficient and high-scale integration of passive and active devices onto Photonics Integrated Circuits (PICs), used to make optical transceivers. The physics of light propagation delivers far lower loss than copper interconnects do at the data rates modern AI workloads demand.

With CMOS, silicon photonics can be fabricated using the same processes semiconductor fabs use for conventional chips. This process allows optical and electronic components to coexist on a single silicon die, with limited use of rare materials or separate production lines, enabling scalable production.

Discussions of silicon photonics tend to focus on the transceiver or circuit design. While these conversations are essential, the substrate is equally important, delivering bandwidth and energy efficiency. Leveraging substrates to help meet growing data demands has been shown to decrease energy consumption by 30-50% on average.

Engineered substrates are silicon-on-insulator (SOI) platforms designed for photonic or high-frequency applications that support a range of markets, including mobile communications, edge AI, cloud AI, Internet of Things and data centers. With the latter, there are a variety of engineered substrates that improve different performance metrics, including Photonics-SOI, PD-SOI and RF-SOI.

Substrate selection is foundational to silicon photonics performance, not incidental to it. The choices made early in the design process determine whether a photonic chip delivers its theoretical efficiency and performance or falls short in deployment.

Scaling data centers requires scaling silicon photonics—now

The semiconductor industry must accelerate silicon photonics production to keep pace with the growth of demand for tomorrow’s data centers.

The technology works. The physics is proven. The manufacturing pathway exists. What's missing is widespread industry alignment and investment to produce silicon photonics at the pace AI infrastructure will require.

Coordinated investment in silicon photonics must happen across chipmakers, substrate suppliers, packaging specialists, and hyperscalers whose data centers will ultimately run on this technology. That coordination is currently happening in pockets, and it needs to be prioritized — the AI buildout is not slowing down.

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The AI race started off with a pretty clear direction – bigger and better. The first waves were characterized by building bigger models, but it’s all change in the world of artificial intelligence and with enterprises, SMBs and consumers all finding use cases for the technology, the focus has shifted.

Now, AI firms and model developers are looking to realize a much tougher goal. Efficiency. Cost per token, performance per watt, output per input, it’s all about driving maximum efficiency.

One clear divide is between training and inference. While training models still requires huge amounts of resources, inference efficiency is starting to improve, and one company (Rebellions) now believes an opening for inference-first hardware could create a new market.

The company’s racks are said to consume around 16-20kW, compared with around 120kW for leading GPU-based inference systems that, for many use cases, are sheer overkill.

Rebellions’ rack costs are also said to be around one-third of the price, making AI inference more accessible and helping enterprises to deploy AI more widely.

This hardware shift could be the start of truly efficient AI

Memory is also another battleground, whereby huge trillion-parameter models are testing the limits of today’s hardware and the intertwined reliance on memory and compute. Something Rebellions is looking to fix by working with memory and foundry partners to align multiple roadmaps, instead of having to respond to shifts in architecture.

Ultimately, today’s black-and-white chip manufacturing landscape is now evolving, and Rebellions sees two key changes happening simultaneously. Firstly, training and inference hardware is starting to differ more drastically. Secondly, aligning multiple hardware roadmaps across memory, compute and more will drive more efficiency not just across deployments, but in terms of bringing new products to market.

I spoke to Rebellions CEO Sunghyun Park allows me to understand how and why inference and training hardware are starting to separate, as well as the importance of open standards and collaboration in the drive for all-round efficiency.

• The AI chip market seems to be splitting between training-first and inference-first architectures. Why is that happening, and why now?

This split exists because training and inference are fundamentally different problems.

Training is how you build a model. It happens once, involves a small number of organizations, and rewards raw computational flexibility because the workload keeps shifting as research moves forward.

Inference is how you actually use a model: every query answered, every transaction processed, every decision an AI system makes in production. That happens billions of times a day across nearly every industry, and it’s where AI moves from R&D into revenue.

Those two jobs need different physics. Training requires maximum FLOPS. Inference requires efficiency, reliability, and economics that hold up when you’re serving users at scale.

The industry forced a training chip into that second job because that’s what existed. Now that inference has become the larger, more urgent market, that compromise no longer holds. Enterprises and governments are asking how fast they can deploy. That’s why the conversation is splitting now.

• Where does Rebellions fit in that split, and what makes your approach to AI inference fundamentally different from your competitors?

We built for inference, from day one. Most first-generation AI chip companies emerged from the 2016-2017 training boom and adapted their architectures for inference afterward.

We started in 2020 – after that wave – with inference as the only target, which meant designing around what production AI actually needs instead of retrofitting a training chip.

The numbers reflect that choice. Our racks draw 16-20kW versus roughly 120kW for leading GPU-based inference systems, about a sixth of the power, in a market where power is the binding constraint for most operators.

Acquisition cost runs around $10 million per rack versus roughly $30 million, about a third of the cost. Our chiplet-based architecture also scales out rather than betting that a single device can handle a model’s full size, which matters now that production workloads are trillion-parameter mixture-of-experts models instead of the few-hundred-million-parameter models the first generation was built around.

It’s also why our architecture is memory-centric rather than compute-centric. The chiplet approach exists to keep memory close to logic as models scale, not just to add cores.

And we have three years of production deployments behind that architecture, not pilots. That’s the hardest part to replicate: real workloads, running at scale, today.

• A year ago, everyone in AI was talking about chiplets. Now the conversation has shifted to memory. What changed?

The chiplet conversation was about architecture: breaking a chip into modular pieces that scale independently, rather than betting everything on a single monolithic die.

That mattered because it let the industry move past an assumption the first generation of accelerators made in 2016 and 2017, that a single device would always be big enough to run any model.

That assumption broke once mixture-of-experts and trillion-parameter models arrived.

The memory conversation is the layer underneath that. Once the architecture problem is solved, the constraint becomes physical: can you actually get enough high-bandwidth memory (HBM) to build what you’ve designed?

HBM is 3D-stacked memory, and how closely you can physically stack it to compute is as much of a bottleneck as raw supply.

Every AI accelerator company is competing for the same limited supply right now, and demand has outpaced what memory makers can produce. That’s the memory-logic co-design problem: architecture and memory supply are no longer separable decisions.

We’re in a different position because our investor relationships were built around supply, not just capital. Our memory partners are also investors, and we co-design our memory architecture directly against their roadmaps rather than simply purchasing off them.

Our chiplet architecture also develops against our foundry partner’s process roadmap. When the rest of the industry was fighting for allocation, we already had a seat at the design table through those relationships.

That’s memory-logic co-design, not just secured supply. The shift from chiplets to memory tracks has moved the real constraint: from architecture to physical supply.

• Your stack runs on open-source frameworks like vLLM, PyTorch, Kubernetes, and OpenShift, tools many enterprises already use. Does that make adoption relatively plug-and-play, or is that an oversimplification?

It’s mostly true, but ‘plug-and-play’ undersells how deliberate that was, and oversimplifies in one specific way.

We built entirely on open standards: vLLM, PyTorch, Kubernetes, and Red Hat OpenShift. We’re one of only two chip companies in the PyTorch Foundation, and the only AI accelerator company fully integrated with OpenShift.

A developer who already knows how to run inference on existing infrastructure already knows how to run it on ours. There’s no proprietary runtime to learn and no migration project. That part really is close to plug-and-play.

The first generation of AI chip companies each built proprietary software stacks, and hundreds of millions of dollars went into software that didn’t survive. We came to market once the open source ecosystem had matured and chose to build on it instead of forking it.

Where it oversimplifies is assuming that means zero integration work. Production deployments still require validating performance at your specific workload and scale, and that takes real engineering time, no matter how compatible the stack is.

What open standards remove is lock-in risk and retraining cost, not the deployment work itself.

• What are the biggest challenges organizations face when trying to run AI inference outside of hyperscaler platforms?

Most organizations aren’t built like hyperscalers, and much of the available inference infrastructure assumes they are.

The first challenge is physical. Most enterprises, telcos, and governments already have data centers. They can’t wait two to three years or spend $600 million-plus on new ones, and they can’t retrofit for liquid cooling without major cost and disruption.

So the practical question is whether inference hardware runs on what they already have: standard racks, air cooling, and existing power budgets.

The second is sovereignty. Organizations increasingly want to bring compute to where their data already lives, rather than move sensitive data to wherever compute is hosted.

That’s partly regulatory, partly operational, but either way, cloud-only inference creates a dependency a lot of operators are no longer comfortable with.

We built specifically for that gap. Our systems run at 4-5kW per server on standard air-cooled infrastructure, no facility redesign required.

SK Telecom has run on our hardware for nearly three years, scaling from a small cluster to close to 100 racks and now processing 50 million API transactions a day, entirely inside their existing network.

KT Cloud runs real-time inference on highway CCTV systems nationally. Both show you don’t need hyperscaler-scale infrastructure to run AI at hyperscaler-relevant volume.

• Cerebras' IPO, and potential listings from others in the space, have put AI infrastructure in the spotlight. What do these IPOs signal about the market, and where might the hype be outpacing deployment reality?

It tells the public markets that AI infrastructure is a durable, investable asset class, not just a venture-backed bet. That validation benefits the whole sector, including us: it says purpose-built AI silicon is real, differentiated from general-purpose GPUs, and worth independent capital.

Capital flowing into the sector is necessary, but it doesn’t by itself determine who wins. The companies that define the next decade of this market won’t necessarily be the most-funded ones.

They’ll be the ones with real fundamentals: production customers, deployment scale, proven economics, durable supply chain relationships. That’s a different filter than fundraising size, and it’s the one that matters once public market scrutiny starts.

We’ve been building toward that filter since 2020, with production deployments and supply relationships with our foundry and memory partners that we secured before the rest of the industry was fighting over the same allocation. The capital is a tailwind for everyone serious about inference.

Whether it gets deployed well is a separate question, and one the market will answer over the next few years.

• Looking ahead, what trends are you watching most closely across AI infrastructure and inference over the next 12–24 months?

The buildout happening inside existing infrastructure keeps accelerating. Most enterprises, telcos, and governments aren’t waiting for new data centers.

They’re deploying inference into facilities they already have, and I expect that to become the bigger story even though it gets less attention than hyperscaler headlines.

Additionally, memory remains the physical constraint. HBM supply hasn’t caught up with demand, and as models keep moving toward trillion-parameter mixture-of-experts architectures, that pressure increases rather than eases.

Companies with secured, strategic supply relationships will have a real advantage over the next two years, not just a cost one.

Chiplets are how we get there. We’ve already mass-produced a highly advanced 4-chiplet package – a level of integration Nvidia has struggled to reach.

Reporting this year indicated Nvidia had built and demonstrated a four-chiplet Rubin Ultra design, then canceled it in favor of a dual-die architecture over manufacturability concerns: a four-die single package pushes roughly 7.5-8x past reticle limits on yield and cost. That’s the foundation.

The next layer we’re building on is performance optimization of HMB3E (3D-stacked memory) in close collaboration with memory and compute co-designed together from the start, not bolted on after the fact.

Also on my radar is the fact that as more companies in this space go public, capital will get valued against production fundamentals rather than funding rounds.

And the efficiency point matters: as inference gets cheaper per token, demand doesn’t shrink, it expands, because new use cases become viable at lower cost. That’s been true of every computing platform in history, and I don’t expect AI inference to be the exception.

• Nvidia's Olympus core architecture prioritizes single-thread IPC over frequency, using a 10-wide decode front end, deep out-of-order mid-core, and a graph prefetcher tuned for agentic AI's branch-heavy, pointer-heavy workloads
• Vera trades chiplet-style core density for a monolithic 88-core die and single-NUMA-per-socket design, a deliberate bet on agentic AI workloads that Nvidia's own engineers admit comes at the expense of legacy workload performance
• Self-reported SPEC CPU 2026 results by Nvidia paint a per-core advantage figure of anywhere between 70% and 80% versus AMD's EPYC 9755 server CPU

Nvidia's Vera CPU has a lot to prove, representing the company's first real attempt at the AI server CPU market, where traditional vendors Intel and AMD, along with third-party Arm-based providers, are all gunning for a piece of an increasingly lucrative data center pie.

To that end, Nvidia has published its most detailed technical account yet of the chip, promising substantial performance gains over the competition. Vera is the company's first server processor built around a fully in-house core design, a departure from the stock Arm cores that powered its Grace predecessor.

As Vera heads toward general availability in the second half of 2026, Nvidia is making its case on a specific front: not raw core count, but sustained per-core performance under load, the metric it argues matters most for agentic AI.

What's actually under the hood of Nvidia's Vera CPU?

At the core of every Vera CPU is Olympus, Nvidia's first custom server core, built to the Armv9.2 instruction set but designed in-house rather than derived from Arm's stock Neoverse designs, as its predecessor, Grace, was.

Nvidia's second-generation data center CPU is a completely reworked design built around a single goal: to lead in agentic workload performance.

Rather than following Intel and AMD down the chiplet route, Nvidia packs all 88 cores (176 threads) onto a single monolithic die, with a dual-socket configuration delivering 176 cores and 352 threads in one system.

Nvidia has detailed the core design extensively, and several publications have since dug into the microarchitecture. The front end runs a 10-wide decode engine paired with a neural branch predictor that can resolve up to two taken branches per cycle, designed to handle the large instruction footprints and irregular control flow of interpreters, compilers, and agent runtimes.

The mid core combines a wide rename-and-allocation engine with a large reorder buffer and dependency-breaking techniques including memory renaming and value prediction.

The execution engine schedules dynamically across integer, vector, floating-point, cryptographic, load, and store resources, while the cache subsystem adds a graph prefetcher targeting the pointer-chasing access patterns that defeat conventional streaming prefetchers.

That design has not gone unanswered. AMD has countered with estimated figures for its 256-core Zen 6 "Venice" part, claiming a 3.3x rack-level advantage over Vera, though those numbers are extrapolated rather than measured.

AMD responding first isn't surprising. Within x86, it continues taking ground from Intel, reaching 33.2% of x86 server CPU shipments in Q1 2026 per Mercury Research, up from 27.2% a year prior.

With Arm reporting that its architecture now accounts for roughly 50% of CPU compute among top hyperscalers, competition is building from several directions at once. Vera may well set a new bar for agentic AI.

• A recent report suggests Nvidia has informed its partners of GDDR6 and GDDR7 memory kit price increases
• This means retailers may increase the prices for RTX GPUs using GDDR6 and GDDR7 memory
• The potential price hike and one user's dual-GPU setup both highlight the importance of hardware preservation

The RAM crisis continues to impact PC manufacturers, with rising memory prices and shortages — ultimately leading to increased retail prices for consumers — and the trend may be set to continue with Nvidia.

According to a report on Benchlife, Nvidia is rumored to be planning an increase for prices of its GDDR6 and GDDR7 memory kits for RTX GPUs, and has informed AIB (Add-In Board) partners such as Asus, MSI, and Gigabyte, who make their own versions of Nvidia's GPUs. Unsurprisingly, the price increase for these memory kits is cited as a result of the ongoing RAM crisis.

While RTX GPU price hikes aren't guaranteed for consumers, because this will directly impact AIB partners who manufacture the GPUs, eventual retailer price increases are unfortunately likely. It's a trend we've seen with recent PC hardware.

Notably, Valve's Steam Machine was initially supposed to cost less than its eventual $1,049 / £879 / AU$1,609 price tag, which could now also be at risk of a price increase, based on hints from a Steam Machine engineer (as reported by Bloomberg). New handheld gaming PCs are also now often launching for more than $1,000, and the price of RAM and storage certainly plays a part.

Consumer struggles

The RAM crisis is a sad state of affairs for consumers and underlines the importance of PC hardware preservation. GPUs aren't cheap by any means, especially with recent suggestions that AMD would also be increasing prices of memory kits for its own AIB partners.

We've also recently seen the return of the RTX 3060, due to Nvidia's attempt to help consumers with more options amid a rough PC hardware market. However, if these price hike reports are legitimate, the RTX 3060 will likely be subject to higher prices at retailers.

That's exactly why GPU setups like one Reddit user's RTX 3090 and RTX 3050 dual-GPU rig matter now more than ever. In this case, the RTX 3050 is responsible for allowing frame generation via Lossless Scaling to function.

A game then utilizes the RTX 3090's power for high-quality visuals and performance, with the two GPUs teaming up. The user states it resulted in 144fps at a 4K resolution over the initial 71fps without frame generation.

Frankly, a dual-GPU setup isn't exactly common, nor is it actually recommended for gaming, since modern games are only designed for single-GPU rendering (even though the frame generation use case is noteworthy).

Users would also need a beefier power supply, depending on the GPUs used, and likely a new motherboard with another compatible PCIe lane.

However, what I feel is more important here is that's it's a great example of why hardware preservation is so important, serving as backup in case GPUs melt or end up faulty, or for experiments like the one I've outlined above. With no end of the RAM crisis in sight, repurposing older hardware might be one way through this.

• Nvidia again showed off DLSS 5 at its Siggraph 2026 keynote
• Team Green made it clear that developers will have a level of control, with a choice of three different AI models
• There will be two sliders to play with, and masks to keep DLSS 5 from interfering with game assets where it's not wanted – but many gamers think devs should have much more control than this

Nvidia has given us another showing of DLSS 5, the incoming tech for its GeForce GPUs which received a very stormy reception when first revealed at GTC 2026 – and unsurprisingly, changes have been made in the past few months.

Tom's Hardware reports that Nvidia revealed more about how DLSS 5 will be implemented at Siggraph 2026 over in Los Angeles, where the tech was the foremost topic in Team Green's keynote.

Nvidia was keen to point out how it has changed the neural rendering model in some key ways since DLSS 5 was first announced. Of course, it's obvious that a lot of this is about combating the idea that the tech is 'AI slop' which makes games look worse rather than better, and characters (particularly faces) look bad and have that undesirable 'uncanny valley' effect. And indeed the criticism that DLSS 5 is messing with the art direction and overall feel of a game's graphics.

On the latter point, back at the original reveal, Nvidia stressed that it would give game developers control over the end result with DLSS 5, and now we're seeing how this will work. Team Green has brought in three different AI models which offer varying levels of detail (and impact on performance), so devs can choose between three different filters, essentially.

This isn't a game-wide choice, though, as the developer can apply any of those models to any different scene, mixing and matching as needed. There are also two sliders to adjust the 'structure' and 'tone' intensity of the effects.

On top of that, the developer can mask off any game asset where they don't want DLSS 5 to be applied. That's good news as it means that, for example, character's heads (and faces) could be marked as out-of-bounds, and therefore not subject to Nvidia's tech. The developer could just get DLSS 5 to enhance background objects and details, and maybe only in a relatively minor way (by toning down those intensity sliders).

To clarify, DLSS 5 is essentially an AI filter that sits atop the existing DLSS suite of technology. Underneath that, you still have upscaling (and frame generation), and Nvidia applies what's essentially a photorealism filter on top of that in the form of this new neural rendering model.

If you want to grab some popcorn, Nvidia's full Siggraph presentation is available to watch on YouTube, check it out below. All the DLSS 5 stuff is at the start (well, past the usual preamble).

Analysis: a step forward, but the doubters remain

Has Nvidia managed to placate the DLSS 5 haters, then? No, in a word. Did you really think it would?

As one Redditor put it: "I had so much hope for DLSS in the early days, what a dumpster fire it's turned into."

Another observed: "So just confirming what anyone with a basic understanding of AI already knew. Glorified Instagram filter."

To be fair, in general the reaction has been somewhat more positive compared to the original reveal, and clearly it's a good thing that game developers can at least keep 'yassified' faces out of the mix with characters. Clearly, there is a level of control here, but despite Nvidia treading more carefully in this respect, there's still a feeling that it isn't doing enough.

A choice of three AI models and a pair of intensity sliders is relatively limited, really, and a far cry from anything like a full level of control over how DLSS 5 imposes itself on a game. Although admittedly there's still some way to go before DLSS 5 comes out – it'll supposedly arrive later this year, in the fall (so theoretically any time from September through to November) – and Nvidia could put in additional controls before the launch.

Aside from disappointment around the level of control Nvidia is giving devs, the other beef being raised is how much of a performance hit this AI filter might be burdened with. When Nvidia first demoed DLSS 5, it was running on a pair of RTX 5090 graphics cards, and in this more recent outing, there's no mention of the hardware involved.

It's fairly easy to guess that the GPU demands haven't been meaningfully reduced yet, otherwise Nvidia would likely be shouting about that – and this is being read as a worry by some. I get where they're coming from, although Nvidia has clarified that the tech will run on a single graphics card (it'll have to, of course), adding at Siggraph that DLSS 5 is "VRAM efficient" (a nicely vague assertion).

I'd expect it probably won't run on anything less than an RTX 5080 to begin with, or indeed an RTX 5090. And the other fear is that the initial incarnation could be quite rough in terms of artifacts and the like, and that's a danger with the first take on any tech. Just look at the original DLSS (version 1), which suffered from blurriness and glitches, before they were polished out and it became a seriously impressive upscaler. Perhaps the same will be true of DLSS 5, but there's a long road ahead yet, and notably, a lot more doubts and question marks here.

• Nvidia's RTX 5000 Super models are being readied, and board makers have the chips, a new rumor reckons
• However, these graphics cards are 'on hold' due to the high price of VRAM
• The Super refreshes pack a lot of VRAM, and so that cost could have an unfortunate impact on MSRPs – and none of this sounds particularly comforting for would-be buyers

Nvidia's RTX 5000 Super refreshes are apparently being readied, but they're on hold for now – and the reason why makes me even more nervous about the pricing of these GPUs when (well, if) they finally emerge.

Of course, these RTX Super models are still rumors – albeit so persistent at this point, there must be at least some validity to them – and the latest assertion comes from VideoCardz.

The tech site has apparently spoken to a source at one of Nvidia's board-making partners who claims that their company has already received 'graphics cards', which presumably refers to GPU chips (which is what Nvidia supplies, along with VRAM, to partners that make the boards).

At any rate, while this board maker supposedly has at least some of the necessary chips, it has been told by Nvidia that the RTX 5000 Super refreshes are now 'on hold'.

Why? Apparently, the delay is down to the price of the video RAM, specifically the new 3GB GDDR7 modules that are required (as per previous rumors) for the refreshed graphics cards.

Compared to the 2GB GDDR7 modules currently in use with Nvidia RTX 5000 models, the 3GB memory chips are around three times more expensive right now. Ouch.

Analysis: Super stumble?

This presents an obvious stumbling block because, due to these Super variants being packed with VRAM, the total cost of materials gets expensive quite quickly.

Remember that the grapevine believes that the RTX 5080 Super and RTX 5070 Ti Super will bristle with 24GB of VRAM, and even the RTX 5070 Super will have a weighty 18GB on board. Gamers are going to love the latter as an upgrade to the lean 12GB of the vanilla version – but not if it pushes the price of the GPU through the roof.

Going by what VideoCardz tells us about pricing in US dollars as the market currently stands, in the case of the RTX 5070 Super, the greater quantity of RAM, and more expensive modules, would mean 18GB costs in the order of $360 (maybe a bit more), versus $120 for the current RTX 5070's 12GB loadout, whacking an extra $240 on the price (or the regional equivalent elsewhere).

These graphics cards were already expected to be pricey, but that kind of additional premium lumped on top, this could make them real wallet-worriers.

The good news for those hoping for new GPUs from Nvidia is that at least these RTX 5000 Super models do seem to be happening. It's just that we may have to wait some time for them yet – although another recent rumor did suggest they were due this year. The latter speculation also theorized that an RTX 5060 Super 12GB model was incoming, but that didn't make a lot of sense, and I note that it isn't mentioned in this latest rumor. As ever, don't go lightly with the seasoning on all this.

• Palit has launched a new RTX 3060 model with 12GB of VRAM
• This continues a recent theme of old GPUs being resurrected
• These GPUs may pack 12GB of video RAM at a relatively affordable price, but they don't make sense compared to current-gen pricing

We might not have seen any new graphics cards so far from Nvidia this year — and no RTX 5000 Super refreshes are in sight (although there are rumors again) — but we're continuing to witness the resurrection of some old GeForce GPUs, with Palit officially revealing a new RTX 3060.

That popular workhorse of a gaming GPU has already made something of a comeback, returning to the shelves of retailers like Newegg as an alternative budget graphics card in a RAM-starved climate where prices of many of these current-gen boards are being hiked up (alongside other PC components, of course).

As flagged by VideoCardz, Palit has trumpeted the launch of its new GeForce RTX 3060 Infinity 2 OC graphics card as "the return of a classic", which is certainly one way of putting it.

Although to be fair, even today, the RTX 3060 remains a very popular GPU, ranking second on the Steam hardware survey for June 2026 (behind only the RTX 4060 laptop GPU in a rather bizarre twist I won't get into here).

Palit observes: "Combining a massive 12GB GDDR6 memory capacity with a clean, all-black dual-fan shroud, the Infinity 2 delivers honest, dependable performance without the premium price tag."

Analysis: let's hope for a Palit-able price tag, but so far, RTX 3060 pricing has been out of whack

The key selling point for these RTX 3060 models is that they're loaded with 12GB of video RAM (VRAM), as Palit emphasizes with this new Infinity 2 OC model. Where this is side-stepping the RAM crisis (to some extent) is that these past-gen Nvidia cards use GDDR6 VRAM, a different memory supply to tap than the GDDR7 used in RTX 5000 graphics cards (except the RTX 5050, which goes with GDDR6, but that's the outlier here).

This means Nvidia can get its partners to produce graphics cards that have 12GB of GDDR6 VRAM (a loadout a good few gamers put a priority on securing), but sit at the cheaper end of the market. Due to cost issues, these days it's a lot less tenable to sell lower-end GPUs which stack up the GDDR7 VRAM (like the RTX 5060 Ti with 16GB).

It's sad that the RAM crisis has forced us to this point, but that's the reality of the GPU world at the moment. What's also problematic for me here is that the RTX 3060 might have 12GB of VRAM at a relatively affordable price point, but looking at current pricing in the US as an example, it's not meaningfully cheaper than the RTX 5060 with 8GB.

Yes, you're getting a lean RAM configuration with the latter current-gen graphics card, but it's still a much faster GPU — one that benefits from DLSS 4, too — and only just over 5% more expensive (at the time of writing). At this kind of price differential, the RTX 3060 12GB doesn't make a lot of sense.

If these RTX 3060 models were a lot cheaper, then there might be more of an argument. To be fair to Palit, we don't have a price tag on this new offering yet, but pricing needs to be a lot more compelling than what I'm seeing right now (especially in the UK, where the RTX 5060 8GB is actually cheaper than the 3060 at some retailers, although there isn't much stock of the latter).

• A Reddit user's Zotac GeForce RTX 5090 GPU reportedly exploded during gameplay
• The power connector wasn't damaged, but a visible burn mark was present on the PCB gold finger
• It's yet another point of concern for RTX 5090 users

Nvidia's RTX 5090 has been the subject of controversy ever since its launch, with several well-publicised cases of melting power connectors causing malfunctions — and this time, it's arguably the worst case yet.

As reported by Wccftech, a Reddit user's Zotac RTX 5090 GPU has exploded, 'five minutes' into playing the tutorial for Assassin's Creed Black Flag Resynced. Interestingly, the 16-pin power connector (often the case of the RTX 5090's woes) wasn't damaged. Instead, the user claims they heard a loud pop and crackle, followed by a cloud of smoke.

The 16-pin power connector has been blamed for several RTX 5090s melting, either due to high temperatures or connectors that aren't properly seated. It also shouldn't be a surprise that these melting complications are effectively exclusive to Nvidia's flagship GPU, since it draws a significant amount of power (575W maximum).

Instead, the PCB gold finger (the part that goes into the motherboard's PCIe slot) on the user's Zotac RTX 5090 has a visible burn mark. The cause isn't exactly clear, but speculation suggests that a crack in the circuit board may have caused the GPU to short-circuit.

Perhaps the most concerning aspect of this case is the suggestion from fellow Reddit users that the supposed crack and short circuit may be the result of GPU sag — and if that's the case, it should be a major concern for high-powered GPU users.

Plenty of modern GPUs, notably from third-party Nvidia partners, are quite chunky, which leaves little clearance to fit in smaller cases and, most importantly, not enough space to use GPU sag brackets.

Fortunately, the RTX 5080, RTX 4080, and RTX 4080 Super (which is the GPU I use) aren't cards that draw nearly as much power as the RTX 5090, so there isn't too much concern in terms of power connectors melting. However, if GPU sag can lead to a short circuit, it raises concern for any GPU that's heavier than most, especially the high-powered RTX 5090, as it's an additional issue to be wary of alongside melting connectors.

A melting or exploding GPU in this current PC hardware market is possibly the worst-case scenario, particularly for RTX 5090 users (who are seemingly most at risk), as prices are completely out of the affordable range due to the ongoing RAM crisis.

Frankly, it makes me want to steer clear of high-wattage GPUs completely (or at least undervolt them). TechRadar has contacted Nvidia for a response.

IDC projects that AI infrastructure costs at Global 1000 companies will run 30% higher than current budgets by 2027. That gap shows a mismatch between how AI workloads behave in production and how enterprise IT has historically planned for capacity.

The pattern repeats across industries. A pilot project validates an AI model on a controlled dataset, and budgets are created around those economics. When the system moves into production, the bill often outpaces what anyone originally modeled.

The natural instinct is to blame the size of the model or the cost of using tokens, but that’s not where the money goes. The cost lives in the data layer, driven by how often the system reads, how many services it touches, and how continuously those operations run.

What pilots don’t show you

A pilot runs against a narrow dataset, with a handful of concurrent users, on a request-response cadence familiar to anyone who has shipped a web application. Production looks nothing like that.

Consider a generative AI customer support agent in production. A single user prompt can trigger simultaneous lookups across session activity, CRM records, inventory systems, retrieved manuals, and other sources before the model produces a response. All of this happens under sub-100ms latency budgets, with the slowest lookup gating the rest. The operational problem becomes tail latency across many small parallel lookups.

Now layer agentic workflows on top. A user request decomposes into a plan, then into a series of steps that each issue their own lookups, write intermediate state, and read it back. What starts as one inference expands into tens or hundreds of data accesses, with the system holding session and memory state across the entire arc. The cost profile that emerges is nothing like what the pilot priced.

Where the 30% comes from

The overrun comes from a series of defensive choices made under uncertainty. When teams can’t see how data flows through a single request, they over-provision to absorb spikes. When they can’t predict cache behavior under shifting context, they duplicate data across systems to reduce dependency risk.

When one downstream service slows down, they layer another service on top to insulate against it. Each choice is locally rational. The aggregate is a system that costs 30% more than the workload requires, and that’s before anyone adds a new use case.

The underlying problems are usually the same. Fan-out per request goes unmeasured end-to-end. Context gets fragmented across feature stores, session stores, user profile systems, vector indexes, and third-party APIs. KV cache and prefix reuse get left on the table because the inference layer can’t hold or share state across calls.

Replication and tiering decisions get made per system rather than per access pattern. None of these show up in a pilot. All of them show up in the production bill.

What the AI data tier has to deliver

AI in production is a continuous, distributed system whose hot path is context assembly — many small reads per request under tight latency budgets — combined with writes that must keep multiple representations of the same entity consistent.

These systems need two things at the same time: predictable low-latency reads under high concurrency and consistent writes across the data path. The infrastructure underneath has to be sized and shaped accordingly.

A few architectural decisions end up driving most of the outcome:

Match the data tier to the access pattern Session state, agent memory, feature lookups, retrieved context, and KV cache reuse all have different read patterns, freshness requirements, and durability needs.

Treating them as different data tiers — or laying them on whatever database happens to be in the stack — is the most common source of overrun. The session store and the system of record have different access pattern demands from the same data tier.

Engineer for fan-out and predictable tail latency Throughput is the wrong primary metric for an AI data tier. The right one is the predictability of many small reads triggered by one request. A batch of parallel lookups is only as fast as its slowest member, and a single slow lookup stalls the entire context-assembly step.

Storage systems optimized for write throughput pay a read amplification penalty under this access pattern. Systems that keep the primary index in memory and resolve point lookups in a single I/O behave differently at the tail.

Treat write consistency as a correctness requirement When updates across user profiles, embeddings, feature vectors, and session state aren’t synchronized, downstream context assembly reads a mix of versions and the model produces confident output grounded in contradictory data.

These are hallucinations that have nothing to do with sampling or model probability, and they don’t yield to better prompts or bigger models.

Treat inference-time data reuse as infrastructure. KV cache reuse, prefix sharing, and agent memory persistence are first-class infrastructure concerns. Teams that figure this out early run the same workloads at lower GPU utilization than teams that haven’t. This is the largest leverage point that doesn’t appear in most AI cost models.

Where to start

The most useful first step is to trace a single production request end-to-end — counting lookups, logging sources, and measuring tail latencies. That exercise reveals more than any architectural review. Once teams can see how data moves through one interaction, they can categorize data accesses by tier and verify that each is running on infrastructure suited to its pattern.

From there, the next question is what’s being recomputed that could be reused, particularly across inference calls and agentic steps. Fan-out per interaction should become a metric teams watch as closely as p99 latency — because at scale, it drives cost just as directly.

AI cost in production is a design discipline. Teams that address it early have far more control over performance and spend than teams that wait until the bill forces the issue. In many cases, the 30% gap is the cost of learning these lessons too late.

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The PC gaming landscape has changed dramatically in the last handful of years. We've seen the slow and steady move away from native (purely rasterized) performance and onto the crutch of AI-powered upscaling technology. Whether Nvidia DLSS, Intel XeSS, or FSR 4, Multi-Frame Generation, or "fake frames", have become a core part of the experience.

It doesn't really matter how powerful the best graphics cards are anymore, as AI-powered upscaling has shifted the playable performance expectations across the board. We see this as standard in the system requirements for today's demanding PC games; it's a huge asterisk that developers use to claim otherwise unheard of FPS in intensive software.

Are the likes of Nvidia DLSS, Intel XeSS, and AMD FSR just a failsafe to make up for poor software optimization? That's part of the story, sure, but it's far more nuanced than that. As computing components become more expensive, and AI muscles its way into the territory in a more aggressive manner, the two, which used to go hand in hand, have now become inherently parasitic in a wanton race to the bottom if things are not course-corrected. Here's what AI-powered upscaling means for the future of PC gaming.

Nvidia DLSS 5 is the first symptom of a wider issue

I've been a champion of DLSS for many years, primarily for how it can boost weaker graphics cards to give users playable framerates. It's an ever-evolving AI-powered tech that's continuing to improve and deepen. Some of its best features include Ray Reconstruction, which makes Path Tracing more viable, Frame Generation/MFG, and DLAA for smoother anti-aliasing. When used as an assist to your hardware, it can be the difference between smooth and stuttering, but DLSS 5 is where things simply went too far.

Instead of being a supporting tool, as with DLSS 4.5's Dynamic MFG, the only thing people can take away from DLSS 5 is how AI is actively impacting image quality, and not for good reasons. Described as a "breakthrough in visual fidelity for games", and said to bridge the "cinematic gap", this upcoming AI model uses an algorithm to re-color and overlay motion vectors.

DLSS 5's showcase of results is troubling to say the least. At best, it slightly improves the lighting in EA FC, and at worst, it completely overwrites the distinct visual art style of PC games like Starfield, Resident Evil Requiem, and Hogwarts Legacy. Sure, the lighting is a little better, but it comes at the cost of a flat and artificial-looking brightness of the entire scene, making everything (ironically) look far more lifeless and void of personality.

Nvidia tends to be the frontrunner that AMD and Intel later catch up to. With the DLSS 5 release date still unconfirmed, but claimed to be coming in the autumn of 2026, we (likely) won't see the full ramifications of this on the wider gaming industry until next year, but when this glorified AI-filter drops, it's likely to become an ingrained option in many flagship titles. There's a reason why Team Green started by showing off some of the largest games from the most well-known publishers and developers in the business; if you enforce it at the top, the rest will follow for fear of being left behind.

The frightening reality of how expensive new graphics cards could be

It's no exaggeration to say that 2026 is one of the worst times on record to build a custom gaming PC. DDR4 and DDR5 RAM prices have skyrocketed due to the global supply of memory modules being drained en masse to build data centers, and the less said about what's happened to flash memory found in the best SSDs, the better. While these individual components doubling in price overnight is already troubling, there are even worse consequences for graphics cards, made all the more infuriating by the fact that it's a self-destructive cycle with (seemingly) no end in sight.

Graphics cards rely on VRAM to have enough bandwidth to perform properly. For Nvidia's current-generation RTX 50 series, that's the superfast, denser GDDR7, whereas AMD and Intel are still using the slower, older GDDR6 standard. As memory modules are becoming scarcer, it massively drives up the price for core components, such as the Samsung, Micron, and SK hynix memory modules needed to build the video cards in the first place.

Put simply, graphics cards will become more expensive because manufacturers are too busy building data centers with the components, meaning the end consumer ends up paying considerably more. We've already seen countless examples of this, such as the Steam Machine's overpriced nature, the Steam Deck's price increase, and even how it's made the PS5 and Xbox Series X more expensive six years in than at launch.

We've seen prices of graphics cards increase massively since the semiconductor shortage, which plagued the RTX 30 series launch. You paid more, you got less, and now the manufacturers know they can overcharge you. In a computing landscape where components can shoot up anywhere from 20 to 50% overnight, it puts the reinforced focus on DLSS, XeSS, and FSR as a necessity rather than an optional helping hand.

The future of AI-powered upscaling is a necessity

While we're heading towards more expensive graphics cards that rely on AI upscaling tech just to keep up, we can also look at what the future of DLSS, XeSS, and FSR will need to do to keep up. We've already established that DLSS 5 made a contentious call with its AI art filter, but what about real-world, practical uses in 2027 and beyond?

Intel XeSS 3 launched with Multi-Frame Generation, which was rolled out to both its Alchemist and Battlemage graphics cards, even bringing true MFG to handhelds like the MSI Claw 8 EX AI+ and Acer Predator Atlas 8. To look positively at AI-upscaling tech in this regard, its major benefit will be to make handheld gaming PCs, such as a Steam Deck or Lenovo Legion Go S successor, more competitive.

The most recent update to AMD's AI-powered upscaling tech, FSR 4 Redstone, still trails behind DLSS 4.5, which means Team Red will need to strike back with FSR 5 to have a chance at dethroning Nvidia while it is down. AMD's image quality is far better than it used to be, even though its frame pacing leaves a lot to be desired. Based on the track record, from what I've seen from Intel and AMD, XeSS and FSR look to continue to iterate on the core fundamental technologies, whereas Nvidia is looking to do its own thing in counter to what was expected.

The future of AI upscaling tech becomes two-fold. Ideally, enabling any of these settings should be as normal and natural as turning on TAA (temporal anti-aliasing) and forgetting about it. It's easy to forget that there was a time when such a setting was contentious, and now it's almost universally used across the board. It's a similar story to when Nvidia's PhysX SDK was pushed so heavily, as it's now a default setting that's enabled within game engines as standard.

So, AI-powered upscaling is best when it's not noticeable. If you're playing a game and you're noticing smooth performance and a high average FPS, then it's doing its job properly. Problems only really arise when that tech tries to overtake the core experience rather than in support of it, and chiefly as a symptom of a wider problem that we're still experiencing. AI-trained algorithms need data servers; we're making more of those, which means taking away the resources to build graphics cards, meaning you'll pay more for them when the Nvidia RTX 60 series, Intel Celestial, and AMD RDNA 5 eventually roll out.

Will native performance ever be relevant again?

I mentioned above about the asterisk of estimated performance when a game's benchmarks and recommended system requirements go live. Oftentimes, these developer/publisher-approved tables promise 30-60 FPS as standard, and try to discreetly hide that DLSS, FSR, and XeSS are needed to hit that cap. It's something that Valve is just as guilty of with its somewhat questionable claims of 4K60, which was walked back when using FSR.

When the biggest and most well-known entity in PC gaming makes a move like this, the gaming world takes notice, particularly with who Valve was targeting in the first place. If FSR is essential for playable framerates, then it becomes non-negotiable; a forced standard, an excuse for developers to rush out unoptimized games, which have plagued countless PC ports over the last five years.

We find ourselves at a crossroads then. AI-powered upscaling does just as much harm as it does good; it is simultaneously the answer to (and cause of) a fair amount of the problems we're currently experiencing as PC gamers, as the benefits and cons constantly battle out for pole position. It looks as though AMD and Intel are on the right track, even if Nvidia is pacing its own trail, one that (hopefully) isn't followed by its competition. If we're already expected to pay four figures for a "mid-range" GPU, let us hope that it can perform decently enough.

Asus ProArt RTX 5090: Two-minute review

The Asus ProArt GeForce RTX 5090 32GB GDDR7 OC Edition is a specialised flagship GPU built for a niche audience and isn’t going to appeal to those looking for a premium upgrade for a gaming build. It’s aimed at creators, AI users and compact workstation builders who want full RTX 5090 performance without the bulk of larger 3.5 or 4 slot coolers.

The ProArt uses the normal RTX 5090 spec: 21,760 CUDA cores, 32GB of 28Gbps GDDR7 on a 512-bit bus and PCIe 5.0 support. The card has a 2482MHz default clock and a 2512MHz OC mode, and a 1000W power supply is recommended.

The 32GB of VRAM helps when rendering, running larger AI models or heavily modded 4K games would exceed the memory available on lower-tier cards. The ports — HDMI 2.1b, DisplayPort 2.1b and USB-C — give excellent monitor setup flexibility.

The 304 x 140 x 50mm, 2.5-slot SFF-ready design is a key selling point, as most flagship RTX 5090 cards are much chunkier, while the slimmer ProArt leaves more room for nearby expansion cards, side-panel clearance and power-cable routing.

Installation is straightforward: a 1-to-4 adapter is included and the 16-pin socket on the card is angled back for easy cable routing, plus the included adjustable GPU support can be used to help prevent sag.

Build quality is top-notch, with no obvious flex, and the GPU avoids gamer-style RGB lighting in favour of a subdued creator/workstation look with brown wood-patterned laminate trim and subtle ProArt gold markings.

Cooling is provided by two large Axial-tech fans, a vapour chamber, liquid metal on the GPU and a double-vented backplate. In OC mode, the GPU peaked at 76°C and memory at 86°C, with a 36dB peak sound level, which is reasonable for a slimmer RTX 5090 cooler. Unfortunately there was noticeable coil whine under heavy loads, and at times it was louder than the fans.

Standard mode was about 5% cooler and 6% quieter, but most importantly, barely slower, while Quiet mode was about 7% cooler and 6% quieter than OC mode, but gave around 2% less performance.

Overall performance is excellent, as expected from an overclocked RTX 5090. OC mode was about 3% faster than a stock RTX 5090, around 45% to 50% ahead of the RTX 5080 in compute loads, and up to 60% in gaming. The improvement is most obvious at 4K, in ray tracing and compute-heavy workloads.

The coil whine is frustrating given this is a card designed for creators, though it’s not so bad that you’d hear it outside a well-designed closed case.

Otherwise, the ProArt RTX 5090 OC Edition does a difficult job well. Yes, it’s expensive and specialised, but its slimmer design, quiet fans, 32GB of GDDR7 and top-end performance make it a capable choice for creators and high-end builders who can use what it offers.

That said, unless you can find it at a compelling price, it faces stiff competition from slim RTX 5090 cards that use AIO water cooling.

Asus ProArt RTX 5090: Price & availability

• How much is it? It retails for about $4,099 / £3,799 / AU$6,499
• When can you get it? The Asus ProArt RTX 5090 is available now
• Where is it available? You can buy it in the US, UK, and Australia

The Asus ProArt RTX 5090 is available now, retailing for about $4,099 / £3,799 / AU$6,499 depending on the region and retailer. That makes it around the typical price for a premium RTX 5090, though it sits above many cheaper air-cooled cards with the same spec.

While the ProArt would always be an expensive card, AI data centre demand has really pushed up prices, so it’s a tough sell unless you really need the features.

The premium price mostly gets you the compact ProArt design rather than a big performance uplift. You still get the full RTX 5090 spec, a mild factory overclock, 32GB of GDDR7, USB-C display output, a slimmer 2.5-slot cooler and a three-year warranty.

The main competition is from other RTX 5090 cards, and if you don’t need the SFF-ready form factor, cheaper air-cooled models will get you very similar core performance for less, while larger premium or all-in-one (AIO) water-cooled RTX 5090 cards may offer lower temperatures, less noise or more overclocking headroom for similar money.

If the compact creator-focused GPU is perfect for your next build, the ProArt may be a compelling buy. If you just want the cheapest route to RTX 5090 performance, wait for the price to come down a little, or look at alternatives.

• Value: 3.5 / 5

Asus ProArt RTX 5090: Specs

• Full RTX 5090 spec and 32GB of GDDR7
• Slimmer SFF-ready 2.5-slot design

• Specs: 4 / 5

Asus ProArt RTX 5090: Design

• Slimmer than most flagship RTX 5090 cards
• SFF-ready

The ProArt design is the main reason to choose this particular RTX 5090 over a more conventional option. Asus has kept the card to 304 x 140 x 50mm (12.0 x 5.5 x 2.0in) and a 2.5-slot thickness, which is much easier to work with than the very large 3.5-slot and 4-slot RTX 5090 designs.

It’s also SFF-ready, which means it fits Nvidia’s size guidelines for small-form-factor enthusiast builds rather than just being smaller than average. That doesn’t make it a tiny GPU, but it does mean the ProArt is built to work in more compact cases that support SFF-ready graphics cards, as well as larger systems where you want more room for other expansion cards or easier airflow.

Visually, it avoids the usual gaming-card look. The brown wood-patterned laminate trim and small ProArt gold details give it a more subdued workstation feel, and there’s no RGB lighting to worry about.

Cooling is handled by two large Axial-tech fans, a vapor chamber, liquid metal on the GPU and a double-vented backplate. That’s a decent cooling setup for a thinner RTX 5090, though the slimmer cooler does mean it has less heatsink volume than some of the much larger cards.

The card includes a dual BIOS switch for Performance and Quiet modes, a solid backplate and an adjustable GPU holder in the box. The 16-pin power connector is angled back toward the end of the card, which helps cable routing, but you’ll still need to be careful with bend clearance, especially in smaller cases.

Overall, the design feels practical, premium and nicely understated, but it only really makes sense if you specifically need a thinner RTX 5090.

• Design: 4.5 / 5

Asus ProArt RTX 5090: Performance

• About 3% faster than a stock RTX 5090
• Excellent cooling and low fan noise
• Very noticeable coil whine

The Asus ProArt RTX 5090 is at its best when you look beyond gaming and treat it as a compact high-end creator card. In Geekbench 6 Compute and Blender, it performs at the level expected for a tuned RTX 5090, with small but useful gains over the stock RTX 5090.

The gap is much bigger against older or lower-tier cards. Across the compute tests, the ProArt was about 50% ahead of the RTX 5080 on average, and around 40% ahead of the RTX 4090. The RTX 4090 is still a very capable GPU, but the ProArt’s combination of 32GB of faster GDDR7 and Blackwell architecture gives it a clear advantage in compute workloads and makes it a worthwhile upgrade.

While not the focus, gaming is still excellent, as you’d expect from an RTX 5090. Cyberpunk 2077 reached 98fps at 4K using Ultra Ray Tracing and balanced scaling, while Black Myth: Wukong hits 88fps at 4K with ray tracing, Cinematic settings and 50% upscaling. So while not the point of the ProArt, it’s a very capable gaming card.

Thermals are quite good for a slim RTX 5090. The ProArt peaked at 75°C, which is much warmer than larger 5090s with aftermarket cooling, which typically run about 10°C cooler. The VRAM reached 86°C, which is again higher than most 5090s but not in any way problematic.

Fan noise was also very low, with the ProArt peaking at just 36dB in my testing. That’s about the same as 5090s with big coolers.

All in all, Asus has done a good job tuning the ProArt to keep performance high and fan noise under control, even if that means letting temperatures sit a little higher than some larger cards. That trade-off is perfectly fine for a 2.5-slot RTX 5090, and the GPU and VRAM temperatures stay well within reasonable limits.

The catch is coil whine, which is an electrical buzz caused by components vibrating under heavy power load, rather than the fans themselves. In fact, most of the time it's louder than the fans themselves.

Some coil whine isn’t unusual on very high-power graphics cards, but it’s still disappointing on a premium creator-focused model where low noise is a key selling point.

Cyberpunk 2077: Ultra Ray Tracing, balanced scaling
Black Myth: Wukong: Ray Tracing, Cinematic, 50% upscaling

• Performance: 4 / 5

Should you buy the Asus ProArt RTX 5090?

Buy the Asus ProArt RTX 5090 if...

Don't buy it if...

How I tested Asus ProArt RTX 5090

• I spent about a week testing the Asus ProArt RTX 5090
• I ran synthetic, compute and gaming benchmarks
• I compared it against the stock RTX 5090, 4090 and the Asus ROG Astral RTX 5080 OC

I spent about a week with the Asus ProArt RTX 5090, testing it in OC mode and comparing it against other high-end cards. The main comparisons were stock RTX 5090 and RTX 4090 performance and the Asus ROG Astral RTX 5080 OC.

I used 3DMark for synthetic performance, Geekbench 6 Compute and Blender for creator workloads, and games including Cyberpunk 2077 and Black Myth: Wukong for real-world gaming results.

• Originally reviewed June 2026

• YouTuber bitluni has unveiled a RISC-V DIY Graphics Processing Unit
• Builder has a library of insane DIY projects on his YouTube channel
• RISC-V microcontrollers were sourced from AliExpress

YouTuber bitluni has unveiled his latest project, which might put any concerns you have over GPU pricing into context. The German DIYer, who has built up a strong following with his selection of intriguing and off-the-wall projects, has assembled a GPU using a large collection of affordable RISC-V microcontrollers (MCUs).

While the results are impressive for a DIY build, the GPU is unfortunately quite modest, and would probably have been abandoned long before now had a PCB design firm not got in touch to explore a partnership over the build.

Demonstrating the project on his channel, bitluni – real name Matthias Balwierz – expressed how difficult the build was, and how it almost drove him mad.

8000+ RISC-V MCUs output at 320x200 resolution

In his latest video, bitluni recalls a previous attempt at building a GPU in late 2025 which lead to PCB designers Altium getting involved, explaining, “The clusters I made before were already challenging my sanity. I thought I was done with the topic, but the budget and these tools would allow for a cluster of a different magnitude, and the magnitude I had in mind was just insane.”

Pushing things to the next level is a hallmark of bitluni’s videos, and the finished build has an incredible 8,192 RISC-V CH570 microcontrollers, each running at 100 MHz, with 12KB of SRAM. These are mounted on blades, which went through several revisions as the PCB company declared them “too complicated.”

Each CH570 has an array of LEDs mounted, and these correspond to each MCU, and the equivalent QVGA pixel. With 8,192 MCUs, the resulting 320x200 might seem modest, but bitluni already has plans for a more power version with 32,000 MCUs.

Graphics or hashing?

The spike in GPU prices before the AI boom was thanks to industrial-scale cryptocurrency hashing, which graphics cards a particularly suited to. It is this relationship between hashing and graphics that gives bitluni’s project some hope beyond displaying images and video.

Identifying the serial port as the bottleneck to the project’s success as a working (if unwieldy) GPU, bitluni has appealed for help from his community of viewers to find a workaround, but that didn’t bring the project to a close.

Changing tack, he used the microcontrollers for hashing and found it outperformed his PC’s 8 core CPU, with a low 4 watt power draw, so perhaps there is a use for this approach after all.

• A Reddit user's RTX 5090 has partially melted a PCIe riser cable
• Some of the riser cable's material is stuck on the RTX 5090's backplate
• It's not as serious a concern as connector melting issues, but it's worth being cautious about riser cable and GPU spacing henceforth

Building a new gaming PC in 2026 and beyond is a tough ask for any gamer amid the RAM crisis, and that's why this case of caution around hardware components is vital.

As reported by TweakTown, a Reddit user has reported a partially melted Lian Li PCIe riser cable due to heat from direct contact with the Asus TUF GeForce RTX 5090 backplate. The material chipped away from the riser cable is evident on the GPU's backplate, but fortunately it isn't a substantial amount.

Riser cables are an ideal solution for any PC builder aiming for a small case that can fit larger GPUs by placing them in a vertical position. In this case, the user specifically notes that the riser cable was stuck against the GPU's backplate during a routine PC cleanup, suggesting that the GPU's heat melted the riser cable's insulation.

It shouldn't come as a huge surprise that the RTX 5090 is involved in a case of components melting (even if it's very minimal). In case you've missed them, there have been several cases of GPU power cables melting with RTX 5090 GPUs, which stems from the high power draw (575 W).

It's important to note, though, that this can happen with other GPUs across AMD's Radeon and Nvidia's RTX cards, especially those that can get quite toasty under heavy load. However, Team Green's flagship is likely more prone to melting complications, made worse when using cheap riser cables or GPU power connectors.

Fellow Redditors argue that this isn't a melting issue, as it appears the riser cable has been chipped away instead. Regardless of the exact cause, it's best to use this as an example to proceed with caution when mounting a new GPU.

If using a riser cable is required due to space limitations, users must provide enough clearance for both the GPU and the riser cable to avoid direct contact. It's a great thing that this user caught on to the matter before any real issue arose.

We've reached out to Nvidia to see if it has any comment on this particular case, but haven't received a response yet — but I'm sure the same warning of caution will be shared.

We've seen rare but far worse cases of GPUs melting, and given how expensive it would be to buy new PC hardware, I'd go so far as to suggest users be overly cautious.

• AMD is reportedly preparing a 10% price hike on graphics memory kits for Radeon GPUs
• This means retailers could increase prices of Radeon GPUs from the likes of Sapphire or Asus
• This case is yet another example of just how hard the RAM crisis is hitting the PC market

Gaming is becoming an expensive hobby for both console and PC gamers, and it's all because of the ongoing RAM crisis. Unfortunately, another manufacturer's GPU components may be the next victim of price hikes.

As reported by VideoCardz, AMD is planning a 10% price increase on graphics memory kits for its Radeon GPUs this July, according to a new post on a Board Channels forum. This means that AMD's AIB partners, such as Sapphire and Asus, will pay more for components, which might result in higher retail prices for Radeon GPUs.

The Board Channels post states that these price hikes are a result of 'tight global supply of graphics memory chips,' including the noticeable trend of 'continuously rising market prices'.

Of course, there's no confirmation from AMD on the matter just yet, but if true, it doesn't help AMD's position in the GPU market up against its fierce rival, Nvidia. Frankly, both are in a tough spot due to higher memory costs across the board, which is well established for effectively every PC manufacturer at this stage in 2026.

While most of Team Green's RTX GPUs are fairly expensive for consumers, the advantage of better upscaling technologies and raw performance when using ray tracing in games makes them more appealing, in comparison to newer Radeon GPUs.

While we await confirmation from AMD, consumers should start buying new hardware now. Both AMD and Nvidia GPUs are still expensive across several retailers, and it's a tough spot for any gamer to be in when searching for an upgrade.

However, if you don't own a gaming PC at all, it's worth keeping an eye out for several deals — and fortunately, Best Buy's 4th of July sale is already underway, and this iBuyPower Slate Intel Arc B570 gaming PC is only $899.99 on sale.

It also comes with 16GB of DDR5 RAM (which would be expensive to buy separately), and most importantly, it's using a GPU that's perfectly capable of great gaming performance at 1080p and 1440p resolutions.

When acknowledging the messy state of the PC hardware market and the prospect of more price hikes, it's hard to ignore a deal such as this, especially when Intel's XeSS upscaling has improved over the last few years — so if it were me, I wouldn't hesitate to purchase.

• Nvidia's RTX 3060 has returned to retailers, amid the ongoing RAM crisis
• MSI, Gigabyte, and Asus models reportedly started at $339.99, but have seemingly increased
• It's a sign that the current state of the PC hardware market is in complete disarray in terms of shortages and pricing

The PC and console hardware market is in the worst place its arguably ever been, with the RAM crisis leading to high prices on components utilizing memory. That's why the return of a popular GPU is one that doesn't come as a huge surprise.

As reported by Tom's Hardware, the Nvidia GeForce RTX 3060 graphics card has returned to retailers, notably on Newegg, with numerous Asus, MSI, and Gigabyte models available.

While Tom's Hardware highlights that prices for these returning GPU models were seen at $339.99 (which is $10 above the MSRP when launched), listings range from at least $416. It's already a big ask at $339 for an old graphics card that doesn't have the same advantages of the current-gen RTX 5060, so the increase won't do it much favors.

It's worth noting that the RTX 3060 has been the most popular GPU on PC, according to Steam's Hardware & Software Survey results, consistently ranking at number one each month for several years. The same trend is evident in May's results, and likely the same for June.

The 12GB GPU is still very much capable of providing solid performance in games at 1080p or 1440p, especially when using DLSS upscaling, and that explains why it's still so popular among Steam users.

However, it's not exactly being received well among consumers. My colleague and PC enthusiast, Matthew Hanson, views the return of the RTX 3060 "like a s**t Frankenstein", and frankly, it's a reasonable observation and one that highlights just how messy the PC hardware market is.

Users on Reddit haven't been shy about highlighting why the GPU's return doesn't make much sense, with one stating: "Even Nvidia enthusiasts would be hard-pressed to get this for $339.99. At that point, just get an RTX 5060.

"The only real benefit to this card is the VRAM, so we all know who this is really for - The AI crowd."

It's not that the RTX 3060 is a bad graphics card, because that's far from the case. However, at the current price the models from MSI and others are available at, it makes little to no sense, since the RTX 5060 is within the same price region, and it has the advantage of Multi-Frame Generation over the RTX 3060.

Regardless, one more option on the market doesn't hurt, especially since it doesn't seem as though its unstable condition will change anytime soon.

These days, if you're looking at tech news, it won't be long before you come across a mention of the RAM crisis. The dwindling supply of memory chips is proving increasingly problematic, and at this point, it seems that the AI industry hasn't just eaten the consumer's lunch, but also their dinner, pudding, and the little mints that usually arrive with the bill afterwards. And did it tip? Not likely.

I have got a tip for you, though – yeah, I know, smooth segue – or rather five tips as we face the inexorably on-rolling memory shortage, which is crushing all wallets in its path. In this article, I've picked out five pieces of computing hardware that I believe you should buy now, or in the very near future, before the PC component crisis — because it extends beyond mere RAM, of course — renders this hardware a good deal pricier.

Nothing is guaranteed in life, not even my expert predictions (ahem), so consider them with that in mind. But I'm making these recommendations — from MacBooks to SSDs — based on what's happened most recently in terms of said crisis, for good reasons that I'll expand upon when I come to each individual pick.

So here are my five devices or components which I believe you should move sooner rather than later with if they're on your shopping list. Bear in mind that with Amazon Prime Day just around the corner (and discounts on the go already), it could also be worth keeping an eye out for bargain deals at that retail giant.

1. Apple MacBooks — especially the MacBook Neo

Earlier this week, Tim Cook came forth with some information that everyone who's mulling buying a new Mac needs to know about. The Apple CEO told us that its products are going to get substantially more expensive before long, liberally sprinkling around words like "unavoidable" without going into any specifics.

Price hikes, and likely sizable ones, are coming to Apple's major products, then, and that includes MacBooks (as well as iPhones and probably iPads too, and more besides no doubt). What I'm particularly worried about though, as I discussed at the time, is what this could mean for the MacBook Neo.

Long story short: Apple ditched the entry-level Mac mini last month, the product which cost an enticing $599 (£599 / AU$999), making the next-tier-up model, which has twice the storage (512GB instead of 256GB), the cheapest option at $699 (£699 / AU$1,099). Might the same thing happen to the MacBook Neo? I believe there's a chance that Apple could mirror this move, because given the need to address MacBook pricing, when it comes to the Neo, applying a hike this early in the device's lifespan doesn't look good. Especially not when it's built entirely on its value appeal as a budget model.

So, a way of rejigging things without a price hike would be to just ditch the current entry-level Neo, just as happened with the Mac mini, leaving folks to pay a hundred notes more for the baseline model (while getting more storage, granted). Then this could be framed as a configuration adjustment rather than a cost adjustment.

With that in mind, the MacBook Neo at its current entry-level price might be a steal, and that's especially the case if you can get a bargain on the laptop. Indeed, there's already a good early Prime Day deal in the UK (at the time of writing) — and there may be others too.

Of course, there could be deals on other MacBook models, and just as with the Neo, it's likely a smart move to grab a bargain on a MacBook Air or MacBook Pro, or any Mac you might be considering buying this year. All these PCs may be hit with what'll seemingly be substantial price hikes, and so I think buying now is very much the thing to do.

A MacBook Air M5 at $950 currently (the discounted price in the US on Amazon, again as I write this) might look pretty good compared to the Neo at $700 a little way down the road, potentially.

2. SSDs

My second port of call given recent rumblings with the component crisis is to grab a relatively affordable SSD if you can, though granted, this comes with caveats — it may not be easy to find one.

Still, I think it's worth trying — again, Prime Day might help here — and to pick an example, Samsung's 990 Pro SSD has been at reasonably palatable pricing (for the current climate) of late. Okay, so a current deal on the 1TB model costs about the same as the MSRP of the 2TB flavor before the RAM crisis hit, but still, a bit over $200 in the US is not bad in the overall picture.

And the thing to bear in mind here is that earlier this week, an exec in the SSD supply chain (a VP at Silicon Motion, which makes drive controllers) gave us an alarming soundbite that ran: "The retail SSD market has almost disappeared." With SSDs all being funneled towards data centers and OEMs (PC manufacturers), there's precious little left heading to the shelves where the average consumer can pick them up.

Unlike RAM, where price inflation may not have much further room to maneuver — given that consumers will just stop buying at some point — there is still some space for SSDs to rise. What the Silicon Motion VP said all sounds rather ominous, and points to a picture where the decent deals — relatively speaking — that we can get right now on SSDs may evaporate before too long.

3. External hard drives

This comes right off the heels of the above in the world of storage, as there's evidence pointing to a rise in hard drive prices. While as noted, SSD prices have shot up — especially for larger capacity or high-end models — hard drives hadn't really been affected, at least not until a few months ago.

Based on the findings of 3D Center, which monitors the German retail market, hard drives are becoming increasingly expensive. Last month, they were 34% more expensive than a year ago, and as of June 2026, that ante was upped distinctly to 58% (effectively a price increase of close to 20% in the span of a month).

So, if you need an external hard disk for your backups or NAS — or to provide extra capacity for your Mac with a small SSD — you might want to consider buying it now before price increases shift up another gear, which looks like what's going to happen.

4. Windows 11 laptops

MacBooks aren't all you need to worry about when it comes to price hikes, as naturally the broad upward pricing pressures on components affect all notebooks.

I previously wrote about why it's a good idea to buy a Windows 11 laptop now, following Nvidia's CEO, Jensen Huang, predicting that the RAM crisis might spin onwards until the end of this decade.

The crux of the matter is that affordable notebooks are still very much a thing, especially during sales, but with the additional gloom cast on pricing woes in recent times — particularly by Huang, who is well placed to forecast — I feel there's a distinct danger that it could be harder to buy a cheap laptop before long.

I doubt you'll regret buying a Windows 11 laptop at today's prices, put it this way, particularly with a discount applied.

5. Graphics cards

Finally, if you're pondering a graphics card upgrade at some point going forward, this is another component that I reckon it'd be smart to grab soon.

While price increases for Nvidia GPUs have been more confined to higher-end models — products with more video memory (VRAM), which is where the pricing misery mainly stems from — I think that they'll apply more to mainstream cards as 2026 rolls on.

Why? For starters, I don't think it's a great sign that Nvidia is resurrecting half-decade-old GPUs from the generation before last to help bolster supply levels of its boards. (These RTX 3000 models use GDDR6 VRAM, which is a useful alternative memory vein to tap away from the GDDR7 that's in current-gen graphics cards). We've seen nasty hikes applied to the RTX 5060 Ti 16GB already, and the RTX 5070 price is creeping up too, based on the latest data from our sister site Tom's Hardware.

The RTX 5070 and RTX 5060 8GB can still be had at relatively palatable prices, though, so they may be a solid buy with a bit of a Prime Day discount in the offing perhaps. (Even if they aren't hugely well-liked GPUs, in all fairness, for one reason or another — the scant VRAM allocation being the main bone of contention for many gamers).

Where I'd be more inclined to look, though, is at the AMD RX 9070 XT. That GPU is in a similar position to the RTX 5070 in the US with a relatively mild (roughly) 10% price hike right now, the difference being that it packs 16GB of VRAM and considerably better performance (at least away from ray tracing).

We've seen some decent deals on the 9070 XT recently, and if you can grab one, I think that could be a great move as a GPU upgrade that'll last you. Particularly given that AMD's CEO Lisa Su has forecast pricing misery to come later this year, with Team Red serving up some relatively strong signals for the likelihood of incoming Radeon graphics card price hikes.

• The first HDMI 2.2 products are likely to arrive in 2027
• Massively increased bitrates with 4K 480Hz support, or 10K resolution
• Great for PC gaming, but won't make much difference to TV viewers

HDMI 2.2 is coming, and it could be a very big deal for gamers. That's because it delivers double the bandwidth of HDMI 2.1: up to 96Gbps.

That means HDMI 2.2 is capable of delivering uncompressed 4K at up to 240Hz (current HDMI can only do this using Display Stream Compression, aka DSC) or uncompressed 4K at 480Hz with 4:2:0 chroma subsampling, and it can also deliver uncompressed RGB 8K at 60Hz. And using DSC, it's capable of delivering 1440p at rates exceeding 1,000Hz.

There is an important qualifier, though: devices can be HDMI 2.2 certified without delivering the very fastest data speeds, so you'll need to study the spec sheets of any potential purchases.

As FlatpanelsHD reports, the HDMI organization expects the first HDMI 2.2 devices to go on sale in 2027; testing and certification are already taking place.

According to Rob Tobias, CEO and president of the HDMI Licensing Administrator, "We're hearing chip manufacturers will start to sample their FRL2 [Fixed Rate Link, the signalling technology used by HDMI] chips this year. And so we should start to see some 96 or up to 96 gigabit HDMI 2.2 products next year."

Will HDMI 2.2 be a big deal?

The specifications are impressive, though it'll be available in three flavors, all of which are faster than HDMI 2.1: 64Gbps, 80Gbps and 96Gbps.

The performance for gaming is particularly impressive, but we already have DisplayPort 2.1 at up to 80Gbps in many of the best gaming monitors so there isn't a hugely pressing need to upgrade. And HDMI requires licensing fees that are likely to be higher than for DisplayPort.

Chances are if you're into high-end gaming hardware you've already gone down the DisplayPort route, especially if you have a multi-monitor setup, but HDMI 2.2 should mean more choice among premium displays.

HDMI has more benefits in living rooms, thanks to features such as ARC (Audio Return Channel), CEC (Consumer Electronics Control) and ALLM (Auto Low-Latency Mode), so it's conceivable that the PlayStation 6 could embrace the higher bitrates of HDMI 2.2 — although games only rarely achieve the 4K 120Hz that's already achievable over HDMI 2.1, and we're not sure that's going to really change with the PS6.

But some 4K 240Hz games might be possible, and the best gaming TVs might offer the refresh rate to support it, so there may be some benefit for the most hardcore. For most living room uses, though, HDMI 2.1 is probably overkill — it's really best for PC connectivity when it comes to the pure data rate.

However, there's another benefit to HDMI 2.2: LIP, which stands for Latency Indication Protocol. LIP improves sound syncing on home theater setups, such as soundbars or AV receivers — this can be a pretty common problem with even the best soundbars, so we'll be keeping an eye on how well this works.

For most of us, I think HDMI 2.2 is generally something to keep an eye on rather than something to demand as soon as it debuts. HDMI 2.2 has been made with 10K resolution in mind, but the vast majority of commercial and streaming video tops out at 4K.

It's something to think about when buying new AV hardware in the future (there's good chance we'll need to wait for 2028's CES for widespread adoption in TVs), but initially at least, it'll be more about marketing than real-world benefits for most of us.

And bear in mind that HDMI adoption is really driven by the companies that provide the connection hardware.

Even today, not all high-end TVs have four HDMI 2.1 ports, because the most powerful processing chips used by many manufacturers don't support this. Some lower-tier TVs from the same makers do, because those chips have more up-to-date HDMI control elements — it's a bit of a mess. I suspect HDMI 2.2 will have the same kind of slightly chaotic support.

On PCs, we'll be relying on GPUs to support the tech, and new models aren't expected until late 2027 or after that — so there's a good chance of seeing HDMI 2.2 on them. But like HDMI 2.1, it'll probably launch on the highest-end models first.

Thinking of buying a new TV?

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• PUBG's Ally Duo mode is now in testing on Steam
• Nvidia's ACE tech is powering the AI teammates in this mode
• You can play with an AI teammate against other human + AI duos until the end of June

PUBG Battlegrounds now offers the option to play with an AI teammate — powered by Nvidia — in a new mode which is available to try in beta for the next two weeks.

As VideoCardz noticed, the Ally Duo Mode is now available through PUBG Arcade, and represents Krafton and Nvidia teaming up to use Team Green's ACE technology — as aired back at the start of the year — to create an AI teammate called Ella.

PUBG Ally was in testing early in 2026 and has now reached the point where it's ready for public consumption — at least as a beta, where the mode will be playable through to the end of June on Steam.

This is an opportunity to "collect invaluable real-world player feedback, to guide the future of AI agents in games," Nvidia tells us.

How does Ella work exactly? The best way to find out is to watch the demo in the YouTube video below.

As you can see, the idea is that you have an AI teammate you can talk to, and more to the point, give orders, or ask for help, using natural spoken language (or typed text if you prefer), with responses from the AI designed to be suitably 'human' in feeling and tone.

At least that's the idea here, but watching the brief demo leaves me with a lot of doubts about what "represents a new generation of AI game characters designed for deeper immersion" according to Nvidia.

Analysis: reaping what was sown a long time ago

It should be no surprise that Nvidia is dressing this up in a lot of fancy talk. Last year when it introduced the concept, Team Green talked about revolutionary Co-Playable Characters or CPCs, as opposed to boring old NPCs. Of course, as my colleague on TechRadar Christian Guyton noted at the time, these are just glorified bots – and we've had bots for ages (PUBG has, too).

In fact, I was deathmatching bots some 30 years ago in Quake, when the Reaper Bot mod arrived. (The Reaper was a horrifically accurate CPU-controlled creation — positively lethal if it got hold of the lightning gun – but overall it had the strategic skills and gaming savvy of a house brick, and was easily trounced by a reasonably good player, but hey, these were very early days here.)

So, this isn't a revolutionary idea, or the next step on from NPCs, or whatever accolades relating to gaming greatness that Nvidia might want to heap on PUBG Ally. However, there is more to Ella than this, in fairness to Team Green. One half of Ella is the bot intelligence to actually play the shooter well enough (hopefully), but the other side is the AI models — the Nvidia ACE trimmings.

These are small language models (SLMs requiring an Nvidia GPU with at least 8GB of video RAM) driving the AI companion's "realistic" decision-making processes, and facilitating communication via speech models. Ella is "equipped with the ability to understand and respond to game situations in a human-like manner" over and above your typical game bot, but I'm not convinced from the demo.

Ella feels painfully artificial — not human — and borderline sycophantic in the game footage shared by Nvidia. OK, so this is still early testing, but I'm not getting any real 'revolutionary' vibes about the gaming skills or chat on show here.

Maybe we'll get selectable personalities eventually — and even true-to-life gaming types. For realism there definitely needs to be an occasional AI teammate who throws a massive hissy fit about how rubbish you are before abruptly quitting, surely?

The general reaction to the emergence of PUBG Ally has been as you might expect: some gamers are curious, while others are mystified or even scathing, and there are more in the latter camp. Some are convinced this will be highly amusing: "I look forward to the comedy that this feature will produce." While others on the same Reddit thread are already trash-talking the AI's ability to play.

I'm not surprised at the feedback thus far given the way Ella has been realized by Nvidia, and the AI being overly chatty hasn't gone down well either. Players engaged in a competitive game don't want flowery chat putting them off their flow, and maybe obscuring important sound effects that are clues as to where the enemy might be and so forth.

The whole thing leaves me rather cold at this stage, frankly, but among more casual gamers — or those who don't have friends to play with at the time, and don't want to hang around in lobbies, or be exposed to toxicity in pick-ups — Nvidia's AI teammate may yet find a place.

As long as the gamer in question owns a decently beefy Nvidia graphics card, that is, and another concern of mine is how much of the GPU's resources are these AI models demanding? Presumably not a lot —they are 'small' by nature — but gamers are notoriously unhappy about anything running interference with their FPS, no matter how slight.