Good catch on the idle-machine rerun, that is the benchmarking habit most comparisons skip. One caveat on the Ollama default: the 4,096 context it picked is much smaller than llama.cpp's per-slot context, so long prompts get silently truncated unless you raise OLLAMA_CONTEXT_LENGTH or set num_ctx. Worth noting if someone compares answer quality and not just tokens per second. Also, a first request after model load includes load time, so warming the model with a throwaway prompt keeps the single-request number clean.