GPU memory (VRAM) is the critical limiting factor that determines which AI models you can run, not GPU performance. Total VRAM requirements are typically 1.2-1.5x the model size due to weights, KV ...

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.

Memory bandwidth is crucial for GPU performance, impacting rendering resolutions, texture quality, and parallel processing. Limited memory bandwidth can result in microstutter, inconsistent frame ...

Hardware Gamers are buying fewer graphics cards according to a new research report, although Nvidia looks to be sitting pretty with roughly 94% of the market share to AMD's 5% Processors Nvidia will ...

Lightbits Labs Ltd. today is introducing a new architecture aimed at addressing one of the most stubborn bottlenecks in large-scale artificial intelligence inference: the growing mismatch between the ...