Linkoteca. GPU

We’ve benchmarked Stable Diffusion, a popular AI image generator, on the 45 of the latest Nvidia, AMD, and Intel GPUs to see how they stack up. We’ve been poking at Stable Diffusion for over a year now, and while earlier iterations were more difficult to get running — never mind running well — things have improved substantially. Not all AI projects have received the same level of effort as Stable Diffusion, but this should at least provide a fairly insightful look at what the various GPU architectures can manage with AI workloads given proper tuning and effort.

The easiest way to get Stable Diffusion running is via the Automatic1111 webui project. Except, that’s not the full story. Getting things to run on Nvidia GPUs is as simple as downloading, extracting, and running the contents of a single Zip file. But there are still additional steps required to extract improved performance, using the latest TensorRT extensions. Instructions are at that link, and we’ve previous tested Stable Diffusion TensorRT performance against the base model without tuning if you want to see how things have improved over time. Now we’re adding results from all the RTX GPUs, from the RTX 2060 all the way up to the RTX 4090, using the TensorRT optimizations.

For AMD and Intel GPUs, there are forks of the A1111 webui available that focus on DirectML and OpenVINO, respectively. We used these webui OpenVINO instructions to get Arc GPUs running, and these webui DirectML instructions for AMD GPUs. Our understanding, incidentally, is that all three companies have worked with the community in order to tune and improve performance and features.