Nvidia AI tech claims to slash VRAM usage by 85% with zero quality loss — Neural Texture Compression demo reveals stunning visual parity between 6.5GB of memory and 970MB

(Image credit: Nvidia) Share Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Email Share this article Join the conversation Follow us Add us as a preferred source on Google Newsletter Stay On the Cutting Edge: Get the Tom's Hardware Newsletter Get Tom's Hardware's best news and in-depth reviews, straight to your inbox. By submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over. You are now subscribed Your newsletter sign-up was successful An account already exists for this email address, please log in. Subscribe to our newsletter As games become more complex and photorealistic, the industry has increasingly relied on upscaling technology to meet surging hardware demands. One of the biggest issues arising from this subpar optimization is VRAM usage, which has risen sharply over the past few years. To combat this, Nvidia has developed a technology called "Neural Texture Compression" (NTC), which was brought up again in today's GTC talk. The best graphics cards will be able to leverage Nvidia's NTC technology. Go deeper with TH Premium: GPUs (Image credit: Noctua) Desktop Roadmap Enterprise Roadmap Rubin in-depth The Stout Owl: The ultimate Noctua G2 PC Instead of conventional block-based compression techniques, NTC enables developers to use small neural networks to unpack textures in any scene. This not only dramatically reduces their size, making game installs more manageable, but also cuts down on VRAM usage at runtime. The resulting textures also look better, with Nvidia claiming up to 4x higher resolution in the final render. In the example below, Nvidia ran a Tuscan Villa Scene that was consuming 6.5 GB of VRAM with standard block compression, but switching to NTC reduced that to just 970 MB, and the image looks identical. Previously, another demo from the company showed a flight helmet with 272 MB of uncompressed textures — block compression cut that down to 98 MB, but NTC reduced it to just 11.37 MB, about 24x less than the original. Article continues below Introduction to Neural Rendering - YouTube Watch On The company also demonstrated Neural Materials, following the same concept: letting a neural network evaluate and decompress material texture data instead of relying on computationally expensive BRDF math. Typically, multiple texture maps are stacked for a material, and the GPU must calculate how light interacts with each layer simultaneously in the rendering pipeline. Neural Materials just asks the neural network how the light will react in that scenario and shades the pixel accordingly. The neural network is trained on all the texture data, so it already knows the result given the light and angle. As such, in the demo scene below, Nvidia achieved up to 7.7x faster render times at 1080p resolution with no loss in image quality. Image 1 of 2 (Image credit: Nvidia) (Image credit: Nvidia) NTC is so efficient because it uses matrix acceleration engines, which are a separate hardwar