Updated docs/perf_history.md to reflect the full Phase 8 work:
- New TL;DR has TWO production configs (English-only with --moonshine,
multilingual with default Kyutai). The English path is the new
headline recommendation.
- Captured live Z.AI bench numbers from the new production stack
(Q8 + stream + warmup + Moonshine + thinking-disabled): total_turn
8765 ms vs Phase 6f.q8 era 17145 ms — half the wall-clock latency
end-to-end.
- Phase 8 commit table extended to 8.4 through 8.10.
- Added an STT backend matrix (Kyutai 1B / Whisper-rs / Moonshine)
with measured RTF, build flags, and per-deploy recommendation rows.
Bench command used (single turn, real Z.AI glm-4.5 thinking-disabled,
10.43 s LibriSpeech /tmp/asr_test.flac):
target/release/examples/converse_server \\
--bind 127.0.0.1:18099 \\
--quantized-gguf /tmp/csm_q8.gguf \\
--stream-tts --moonshine \\
--llm-base https://api.z.ai/api/coding/paas/v4 \\
--llm-model glm-4.5 \\
--llm-extra-body '{"thinking":{"type":"disabled"}}'
Server-side timing:
recv_phase 0 ms (Moonshine batch — no parallel STT)
stt_post 332 ms (Moonshine transcribe at EOT)
llm_to_first_audio 1627 ms (Z.AI TTFT ~1.3 s + first TTS chunk)
conv_total 8432 ms
total_turn 8765 ms
Client TTFA: 1959 ms (vs Phase 6f.q8 era ~2 s — comparable; the dominant
remaining latency is the Z.AI provider TTFT, not anything we control).
Z.AI returned a coherent reply: "He eagerly anticipated a hearty stew
with turnips, carrots, potatoes, and savory mutton pieces for dinner."
matching the LibriSpeech ground-truth meaning.
Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>
Consolidated record of every shipped optimization, every rejected path
with the data behind the rejection, the production-recommended config,
the architectural lessons captured, and the deferred multi-session
work with realistic sizing.
Headline:
- client first_audio_ms p50 = 529 ms (mock LLM, Q8 + stream + extended warmup + VAD gate)
- real Z.AI loop: ~2 s TTFA p50
- boot cost: ~2.7 s (one-time)
Rejected paths captured (so future sessions don't redo the work):
Q4_K_M (2.85x slower than Q8), whisper-rs linkage (2-3x CSM regression),
Silero V5 via ort (protobuf 3.14 vs 3.21 conflict), Mimi codec Q8
(no candle conv-quant path), KV cache reuse (variance is content-
dependent not state-dependent), rayon for single-connection
(overhead exceeds gain on <100µs tasks), codec swaps (require
backbone retrain), custom distillation (no published checkpoint),
Kyutai 4x flush (hardware-bound on M-series).
Architectural lessons:
1. In-process linkage of external ML runtimes is a recurring trap;
default to sidecar-process pattern.
2. Bench thermals dominate single-machine A/B; 90s cooldown often
necessary.
3. First-frame compilation is the dominant cold-start cost — long
warm-ups are essential.
4. Conv-phase variance is content-dependent, not state-dependent.
5. tokio::join! polls cooperatively — spawn separate tasks for real
concurrency between sync compute and async pump.
Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>
