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You can run vLLM with AMD GPUs supported by ROCm: https://rocm.docs.amd.com/en/latest/how-to/rocm-for-ai/infer...

However from experience with an AMD Strix Halo, a couple of caveats: it's drastically slower than Ollama (tested over a few weeks, always using the official AMD vLLM nightly releases), and not all GPUs were supported for all models (but that has been fixed).

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vLLM ususally only plays out its strength when serving multiple users in parallel, in contrast to llama.cpp (Ollama is a wrapper around llama.cpp).

If you want more performance, you could try running llama.cpp directly or use the prebuilt lemonade nightlies.

But vLLM was half the t/s of Ollama, so something was obviously not ok.

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