Considering how poorly it seems to support cuda as a backend [0], I wouldn't hold my breath about non intel vendor support (amd cpu or gpu). If you want to try anyway, here's the benchmark suite [1] and I couldn't find sample results available.
As for less common gpus, there really is no good support in any library. If you ever want to go down a fun rabbit hole, try to use the gpu in a raspberry pi for something. You'll eventually find one guy who reverse engineered the drivers to make a compiler but that's it. That's also the story for most uncommon chips with gpus (amlogic, broadcom, etc) where the real vendor gives you a driver blob for linux and no documentation. On the other hand rockchip has some good things available [2].
As for less common gpus, there really is no good support in any library. If you ever want to go down a fun rabbit hole, try to use the gpu in a raspberry pi for something. You'll eventually find one guy who reverse engineered the drivers to make a compiler but that's it. That's also the story for most uncommon chips with gpus (amlogic, broadcom, etc) where the real vendor gives you a driver blob for linux and no documentation. On the other hand rockchip has some good things available [2].
[0] https://github.com/IntelPython/dpctl/discussions/1124
[1] https://github.com/IntelPython/dpbench/blob/main/README.md
[2] https://github.com/rockchip-linux/rknn-toolkit2