ARC XT PRO AND WINDOWS 10 CODE
ARC XT PRO AND WINDOWS 10 SERIES
ARC XT PRO AND WINDOWS 10 ZIP

Keep in mind that the hardware has theoretical performance that's quite a bit higher than the RTX 2080 Ti (if we're looking at XMX FP16 throughput compared to Tensor FP16 throughput): 157.3 TFLOPS versus 107.6 TFLOPS. Intel's current fastest GPU, the Arc A770 16GB, managed 15.4 images per minute. Clearly, AMD's AI Matrix accelerators in RDNA 3 have helped improve throughput in this particular workload. The RX 6950 XT output 6.6 images per minute, well behind even the RX 7600. Even more alarming, perhaps, is how poorly the RX 6000-series GPUs performed. With the latest tuning in place, the RTX 4090 ripped through 512x512 Stable Diffusion image generation at a rate of more than one image per second - 75 per minute.ĪMD's fastest GPU, the RX 7900 XTX, only managed about a third of that performance level with 26 images per minute.

ARC XT PRO AND WINDOWS 10 SERIES

The RTX series added the feature in 2018, with refinements and performance improvements each generation (see below for more details on the theoretical performance). Nvidia has been pushing AI technology via Tensor cores since the Volta V100 back in late 2017. This shouldn't be a particularly shocking result. But if you're just here for the benchmarks, let's get started.

ARC XT PRO AND WINDOWS 10 CODE

upscaling) is separate from the base text to image code and would require additional modifications and tuning to extract better performance, so that wasn't part of our testing.Īdditional details are lower down the page, for those that want them. Once you have the basic steps down, however, it's not too difficult to fire up the webui and start generating images. If you have issues with the instructions in any of the linked repositories, drop us a note in the comments and we'll do our best to help out. Whether you're using an AMD, Intel, or Nvidia GPU, there will be a few hurdles to jump in order to get things running optimally. Our understanding, incidentally, is that all three companies have worked with the community in order to tune and improve performance and features. We used these webui OpenVINO instructions to get Arc GPUs running, and these webui DirectML instructions for AMD GPUs. 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.įor AMD and Intel GPUs, there are forks of the A1111 webui available that focus on DirectML and OpenVINO, respectively. 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. But there are still additional steps required to extract improved performance, using the latest TensorRT extensions.

ARC XT PRO AND WINDOWS 10 ZIP

Getting things to run on Nvidia GPUs is as simple as downloading, extracting, and running the contents of a single Zip file.

The easiest way to get Stable Diffusion running is via the Automatic1111 webui project. 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. 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. 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. How fast are consumer GPUs for doing AI inference using Stable Diffusion? That's what we're here to investigate. While more advanced tools like ChatGPT can require large server installations with lots of hardware for training, running an already-trained network for inference can be done on your PC, using its graphics card. Using trained networks to create images, videos, and text has become not just a theoretical possibility but is now a reality. Stable Diffusion and other AI-based image generation tools like Dall-E and Midjourney are some of the most popular uses of deep learning right now.

ARC XT Pro and Windows 10