Edge benchmark results
Committed JSON produced by the edge branch benchmarks (kept small; WAVs are never committed):
stream_latency/<model>/<deploy>/<timestamp>[_tag].json—stream_latency_bench.pyoutput (schema 1):meta(model, deploy config, git SHA, GPU),init(init_s, optional init timeline),resources(peak RSS, peak GPU MiB, sampling mode),requests[](per-chunk arrivals, TTFA, playback-start, stall at TTFA, RTF streamed / total) andsummary(p50/p90/max).init_profile/<timestamp>/summary.json—init_profile.pycomparison of initialization phases per configuration.hw_emulation/<timestamp>/summary.json—hw_emulation.pymatrix (emulated hardware class x TTFA / playback-start / RTF / RSS; per-case bench JSON,hw_profile.jsonand init timeline next to it).cpu_sweep/<timestamp>/summary.json—cpu_thread_sweep.py(CPU-only 8/16/32 threads + inductor variant, with per-step attribution).stream_latency/step_stats/<timestamp>/*.json— raw per-process counters from--step-stats(merged into the bench JSON understep_stats).codec_stream/—codec_stream_e2e.pyparity (server PCM vs client-decoded codec tokens, SNR) and client latency.stream_latency/timelines/— init timelines (VLLM_OMNI_INIT_TIMELINE) of the committed runs.
Metric definitions live in benchmarks/tts/stream_latency_metrics.py.