Nvidia's new VRAM trick sounds great, until you realize your RTX card can't even use it

Published May 15, 2026, 5:00 PM EDT After a 7-year corporate stint, Tanveer found his love for writing and tech too much to resist. An MBA in Marketing and the owner of a PC building business, he writes on PC hardware, technology, and Windows. When not scouring the web for ideas, he can be found building PCs, watching anime, or playing Smash Karts on his RTX 3080 (sigh). The problems surrounding insufficient VRAM rear their head whenever a new and demanding game fails to run properly on older or lower-end graphics cards. We blame everything from game optimization issues to Nvidia's habit of skimping on VRAM before going back to the status quo. The reason companies like Nvidia can keep selling GPUs with 8GB of VRAM is that gamers are forced to buy whatever they can in a terrible market. Another reason is that upscaling continues to improve, reducing the VRAM dependency on budget and mid-range cards. The latest reason 8GB VRAM GPUs aren't going anywhere is Neural Texture Compression, Nvidia's latest trick to drastically reduce VRAM usage in games. It promises astounding results, but only on Nvidia's most powerful GPUs. Older graphics cards don't have the hardware chops to adequately support this new technology, making it meaningless for the vast majority of RTX owners. Related Nvidia just solved their VRAM problem, but not by giving out more VRAM Traditional graphics rendering could be in the rearview mirror soon enough Neural Texture Compression could slash VRAM usage going forward Nvidia might have something game-changing on its hands Unlike conventional Block Compression (BCn) in games that use fixed mathematical formulas, Neural Texture Compression(NTC) is an AI-powered technique that uses neural networks to reconstruct textures in real time. NTC essentially stores a sample of high-resolution textures and recreates them on the fly using a tiny AI model, enabling incredible compression ratios that aren't as effective with Block Compression. Nvidia recently showcased NTC in action at GTC 2026, demonstrating a scene where the VRAM usage dropped from around 6.5GB to less than 1GB when using NTC textures instead of BCn textures. This massive reduction in VRAM consumption didn't come at the cost of visual quality either, as shown by the Tuscan Villa demo. NTC shifts the workload from the CUDA cores to the Tensor cores, leveraging their AI capabilities to detect patterns across textures instead of compressing texture blocks in isolation. It encodes all the texture information into a compact representation called a latent, which is then used as a reference to populate all the textures, achieving compression ratios not possible with Block Compression. The results that Nvidia showcased at GTC promise a radical change in how we think of VRAM consumption. If NTC is adopted in games in the same way, it could completely flip the value proposition of GPUs with low VRAM capacities. 8GB VRAM models will no longer seem limiting, benefiting countless gamers who can't afford to buy SKUs with 16GB or more VRAM. Related Only the latest and greatest Nvidia GPUs can enjoy the benefits of NTC It looks like another MFG situation NTC does, however, come with a performance overhead. The neural network reconstructing the latents might be small, but it requires the horsepower of the AI-powered Tensor cores to function effectively. Nvidia's GTC demo was running on the RTX 5090, the most powerful consumer GPU in existence. For your GPU to use NTC to slash VRAM usage without slashing performance at the same time, you'll need a powerful RTX 50 or RTX 40 series GPU. Only these graphics cards have the right Tensor cores to run NTC the way it's intended to run. NTC comes in different variants, and the one shown to drop VRAM usage by 85% is of the Inference on Sample variety. This variant will not show the same VRAM improvements on GPUs lacking Nvidia's latest Tensor cores, which means your RTX 20 or RTX 30 series GPU won't suddenly get a new lease on life. In its current form, NTC is mostly irrelevant for GPUs that need it the most. The latest GPUs can manage VRAM dependency much better with more advanced DLSS models, but the older cards need the most help to extend the longevity of their 8GB framebuffers. Unless NTC can somehow run better on older architectures, which I highly doubt (since it's a neural network), you'll need a fairly modern GPU to benefit at all. NTC's Inference on Load variant, however, can run on pretty much any GPU, but it doesn't offer any significant reduction in VRAM usage. Inference on Load transcodes NTC textures back to BCn textures during execution, so the VRAM benefits aren't there, but gamers can still benefit from reduced texture and game installation sizes. Similar to Multi Frame Generation, Nvidia's new VRAM trick works best on GPUs that don't need it as much. The larger userbase is still left out of the NTC ambit, fending for themselves, trying to reduce VRAM dependency by lowering graphics settings and skipping ray tracing. It's great that techniques like NTC exist, but what good are they when the real benefit is limited to a small section of gamers buying Nvidia's most expensive graphics cards? Zotac Gaming GeForce RTX 5070 Ti Solid SFF OC $1000 $1080 Save $80 The Zotac RTX 5070 Ti Solid SFF OC is one of the more affordable variants of Nvidia's mid-range graphics card, and offers excellent 1440p and decent 4K gaming. Related There are even more asterisks to be aware of Hardware gains should not be overlooked Even if you have an RTX 40 or RTX 50 series GPU with less-than-ideal VRAM, your existing game library won't magically become easier on your card. Since developers need to integrate NTC into the rendering pipeline, only future games will potentially benefit from the promised VRAM reduction. Besides, dependencies like Stochastic Texture Filtering (STF) and Cooperative Vector support in Shader Model 6.9 in DirectX are still fairly new technologies. It might still take years for widespread NTC adoption in games. Until then, sufficient VRAM remains a genuine pain point for gamers with old or budget GPUs. NTC also gives Nvidia another excuse to keep selling 8GB VRAM GPUs. It doesn't matter if the technology needs time to mature; the company has already made comments about how its old GPUs are aging like fine wine. NTC is a welcome technology, not only for its VRAM reduction capabilities, but also for potentially smaller game downloads and updates. That said, it shouldn't give manufacturers a free pass to keep handicapping the hardware on consumer GPUs. Nvidia and other companies have already made it clear that consumer hardware is no longer a priority for them. With AI-powered techniques like NTC entering the fray, GPU companies will further reduce the focus on raw hardware improvements. Irrespective of the efficiency of software innovation, gen-on-gen hardware gains can't be overlooked. Related Modern GPUs are incredible, but they broke the idea of sensible upgrades A GPU upgrade doesn't feel like one anymore, at least not the way we remember Neural Texture Compression works well, but conditions apply Nvidia has showcased a new way of compressing high-resolution textures that works tremendously well to reduce VRAM consumption in games. However, it needs the power of the latest GPUs to run effectively. Most PC gamers don't own high-end RTX 40 or RTX 50 series cards, and won't be able to see the same benefits on their PCs. Moreover, NTC will only benefit future games if developers decide to adopt it. It's a great tool, but the majority of gamers shouldn't celebrate yet.