AMD dual-GPU thread spotlights local serving gap

The interesting part here is not the question itself, but what it says about the state of open inference serving on AMD: the features exist, but confidence is still uneven.

• –vLLM positions itself as a high-throughput serving engine with continuous batching, an OpenAI-compatible API, and official AMD GPU support, making it the obvious "shared backend" candidate on paper
• –KoboldCpp remains attractive for GGUF-first local setups and one-file simplicity, but this post is a reminder that convenience and robust concurrent serving are not always the same thing
• –The only concrete reply in the thread points the user back toward llama.cpp with ROCm and `llama-server -np 4`, which suggests community trust still leans toward the simpler, battle-tested route
• –For AI developers running small shared workstations, backend choice is increasingly about scheduler maturity and batching behavior, not just raw tokens per second