Decoding AI performance on RTX AI PCs introduces new metrics like TOPS for generative tasks.

From NVIDIA: 2024-06-12 09:00:25

The era of AI PC powered by NVIDIA RTX and GeForce RTX technologies has arrived, introducing new performance metrics like TOPS for generative AI tasks. The Copilot+ PC lineup by Microsoft offers neural processing units capable of performing 40 TOPS, whereas the GeForce RTX 4090 GPU offers over 1,300 TOPS for demanding tasks.

To evaluate LLM performance, the number of tokens generated by the model plays a crucial role. Batch size, or the number of inputs processed simultaneously, also affects performance. RTX GPUs are ideal for LLMs due to their large VRAM, Tensor Cores, and TensorRT-LLM software, enabling higher batch sizes and faster performance.

Measuring image generation speed is key for evaluating performance, with Stable Diffusion enabling users to convert text descriptions into visual representations. The TensorRT extension for Automatic1111 and ComfyUI interfaces streamlines workflows, providing significant speed improvements when generating images or converting to videos.

Open-source Jan.ai integrated TensorRT-LLM into its local chatbot app, showcasing a 30-70% speed improvement over llama.cpp on the same hardware. From games to generative AI, performance metrics like TOPS, tokens per second, and batch size are crucial for determining the most efficient AI solutions transforming various interactive experiences.



Read more at NVIDIA: Decoding AI Performance on RTX AI PCs