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This was referenced Nov 12, 2026
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serve_batching.py takes --backend native and passes the worker the native engine's --native-device and --native-kv-dtype. It rejects what the native worker cannot serve, DFlash and the vision table, before starting the worker. BATCHING_SERVING.md covers the native export, build and launch. Served the full Muse-Glimmer-30B-KQuant-17GB-Q4_K_M export on Metal with four sessions and a prefix cache: three concurrent requests ran at 31 tokens/s against 23.5 one at a time, with the same answers, and a repeated 848-token prompt reused 842 cached tokens.
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Off-graph KV cache for the native ggml engine, through serving Muse Glimmer on it. Review bottom-up; each PR builds and passes its tests on its own.
Summary
serve_batching.py --backend nativelaunches the Muse Glimmer server on the native engine.--native-deviceand--native-kv-dtype.--data-path, before starting the worker. Sessions and the prefix cache work as on the other backends.BATCHING_SERVING.mdcovers the native export, build and launch.Test plan
test_serve_batching.py(33 pass): native options forwarded, omitted for other backends, DFlash, vision and a data path rejected./v1/chat/completionswith--max-sessions 4 --prefix-cache-entries 4:Authored with Claude Code.