![]() ![]() ![]() The GPU will operate at a fraction of the power for lighter inferencing tasks, while scaling up to unmatched levels of performance for heavy generative AI workloads. To meet this need, RTX GPUs will add Max-Q low-power inferencing for AI workloads. Enhancements introduced last week at the Microsoft Build conference doubled performance for generative AI models, such as Stable Diffusion, that take advantage of new DirectML optimizations.Īs more AI inferencing happens on local devices, PCs will need powerful yet efficient hardware to support these complex tasks. This is thanks to Tensor Cores - dedicated hardware in RTX GPUs built to accelerate AI calculations - and regular software improvements. When optimized for GeForce RTX and NVIDIA RTX GPUs, which offer up to 1,400 Tensor TFLOPS for AI inferencing, generative AI models can run up to 5x faster than on competing devices. Generative AI models and applications - like NVIDIA NeMo and DLSS 3 Frame Generation, Meta LLaMa, ChatGPT, Adobe Firefly and Stable Diffusion - use neural networks to identify patterns and structures within existing data to generate new and original content. Generative AI is rapidly ushering in a new era of computing for productivity, content creation, gaming and more. ![]()
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