Stability AI, the developers behind the popular Stable Diffusion generative AI model, have run some first-party performance benchmarks for Stable Diffusion 3 using popular data-center AI GPUs, including the NVIDIA H100 "Hopper" 80 GB, A100 "Ampere" 80 GB, and Intel's Gaudi2 96 GB accelerator. Unlike the H100, which is a super-scalar CUDA+Tensor core GPU; the Gaudi2 is purpose-built to accelerate generative AI and LLMs. Stability AI published its performance findings in a blog post, which reveals that the Intel Gaudi2 96 GB is posting a roughly 56% higher performance than the H100 80 GB.

With 2 nodes, 16 accelerators, and a constant batch size of 16 per accelerator (256 in all), the Intel Gaudi2 array is able to generate 927 images per second, compared to 595 images for the H100 array, and 381 images per second for the A100 array, keeping accelerator and node counts constant. Scaling things up a notch to 32 nodes, and 256 accelerators or a batch size of 16 per accelerator (total batch size of 4,096), the Gaudi2 array is posting 12,654 images per second; or 49.4 images per-second per-device; compared to 3,992 images per second or 15.6 images per-second per-device for the older-gen A100 "Ampere" array.