Files
esh-pfi-infrastructure/stacks/kokoro
vh e0a33d0b33 stacks/kokoro: flip .env.example default from cpu → gpu (driver bump landed)
irv-ml1's driver upgrade to 595.58.03 (kernel 6.1.0-37, CUDA 13.2) is
working — both GPUs detected, modules loaded. The gpu variant of the
Kokoro-FastAPI image (which requires CUDA >= 12.9) is now the right
default for new deploys. Flipping KOKORO_VARIANT=gpu, KOKORO_USE_GPU=true,
KOKORO_GPU_DEVICES=0 (pins to the RTX 3090 — Kokoro is ~1 GB VRAM and
doesn't need the A6000).
2026-04-27 15:17:27 -07:00
..

Kokoro

hexgrad/Kokoro-82M served via remsky/Kokoro-FastAPI.

Why this stack exists

Lowest-latency English TTS in the fleet by a wide margin — ~300 ms time-to-first-audio on GPU, 35-100x realtime, ~1 GB VRAM at fp16. Native streaming (Kokoro's KPipeline.__call__ is a per-phrase generator) and the wrapper exposes it via OpenAI-compat stream=true over chunked HTTP — drop-in for any OpenAI SDK client.

Complementary to the rest of the TTS slate:

use case
Kokoro low-latency English, fixed voice library
Chatterbox Turbo low-latency English w/ voice cloning + paralinguistic tags
IndexTTS-2 English voice cloning + emotion vector / text control
Qwen3-TTS-1.7B-Base high-quality English voice cloning
CosyVoice 3 multilingual (Chinese-leaning)
VibeVoice 1.5B long-form podcast / multi-speaker dialogue

API

OpenAI-compat at http://10.100.79.3:8193:

# List built-in voices (~60 of them, named like af_bella, am_adam, jf_*, zf_*).
curl http://10.100.79.3:8193/v1/audio/voices

# Single-shot synthesis.
curl -fsS -X POST http://10.100.79.3:8193/v1/audio/speech \
  -H 'Content-Type: application/json' \
  -d '{"model":"kokoro","input":"Hello there.","voice":"af_bella","response_format":"wav"}' \
  > out.wav

# Streaming — pipe straight into a player.
curl -fsS -X POST http://10.100.79.3:8193/v1/audio/speech \
  -H 'Content-Type: application/json' \
  -d '{"model":"kokoro","input":"long passage here…","voice":"af_bella","stream":true}' \
  | mpv --no-cache -

# Voice mixing — sum voicepacks with weights.
curl -fsS -X POST http://10.100.79.3:8193/v1/audio/speech \
  -H 'Content-Type: application/json' \
  -d '{"model":"kokoro","input":"hello","voice":"af_bella(2)+af_heart(1)","response_format":"wav"}' \
  > mix.wav

Web UI at /web (browse voices + try in-place); OpenAPI at /docs.

Supported response_format: mp3 | wav | opus | flac | pcm.

Voices

  • Built-in: 60+ in 8 languages (en-US, en-GB, ja, zh, es, fr, hi, it). Discoverable via GET /v1/audio/voices — naming convention is <lang_code><gender_letter>_<name> (e.g. af_bella, am_adam, jf_alpha, zf_xiaobei).
  • Custom: drop .pt voicepacks into /worktank/kokoro/user_voices/ on the host. Wrapper auto-discovers them on next request (no restart). Training Kokoro voices is non-trivial — consult the hexgrad community for how-to.

Deploy

scripts/elway irv-ml1 --playbook playbooks/deploy-kokoro.yaml

First deploy: ~6.5 GB image pull from GHCR (~2-5 min on a fast link). No model download on first run — Kokoro-82M weights are baked in. Subsequent starts: a few seconds.

License

Apache-2.0 for both the wrapper code (remsky/Kokoro-FastAPI) and the Kokoro-82M weights (hexgrad).