Meh. DGX is Arm and CUDA. Strix is X86 and ROCm. Cuda has better support than ROCm . And x86 has better support than Arm.

Nowadays I find most things work fine on Arm. Sometimes something needs to be built from source which is genuinely annoying. But moving from CUDA to ROCm is often more like a rewrite than a recompile.

> But moving from CUDA to ROCm is often more like a rewrite than a recompile.

Isn't everyone* in this segment just using PyTorch for training, or wrappers like Ollama/vllm/llama.cpp for inference? None have a strict dependency on Cuda. PyTorch's AMD backend is solid (for supported platforms, and Strix Halo is supported).

* enthusiasts whose budget is in the $5k range. If you're vendor-locked to CUDA, Mac Mini and Strix Halo are immediately ruled out.

CUDA != Driver support. Driver support seems to be what's spotty with DGX, and iirc Nvidia jas only committed to updates for 2 years or something.