vh
099e1d7418
- chatterbox-fast experimental -> ready: browser audition verified end-to-end (operator confirmed progressive playback "excellent" 2026-06-02). - vibevoice ready -> down: no container running on irv-ml1 (connection refused); catalog status was stale. - voxtral: NOT a stale typo — its stack genuinely claimed :8197, the port now held by the live chatterbox-fast. voxtral is down, so moved IT to :8201 (catalog endpoint + source_url, stacks/voxtral/.env.example + README, host .env) rather than disturb the live service. No live clash existed (voxtral down) but it was a latent deploy-time collision I introduced by placing chatterbox-fast on 8197. No catalog_version bump (status changes + endpoint correction, additive). Validates against the schema.
86 lines
3.0 KiB
Markdown
86 lines
3.0 KiB
Markdown
# Voxtral TTS
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[mistralai/Voxtral-4B-TTS-2603](https://huggingface.co/mistralai/Voxtral-4B-TTS-2603)
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— Mistral AI's 4B open-weight streaming TTS, served via the
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[vLLM-Omni](https://github.com/vllm-project/vllm-omni) production
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serving stack (Mistral co-developed). Released March 28, 2026.
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## ⚠️ License
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**CC BY-NC.** Personal use, research, and internal tooling are fine.
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**Don't ship Voxtral output in any commercial product** without
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re-licensing from Mistral. The other TTS in this fleet (Kokoro,
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Chatterbox, Fish S2-Pro, IndexTTS-2, Qwen3-TTS, CosyVoice) are all
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open-licensed and clean for commercial work.
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## Why this stack exists
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Multilingual streaming with serious speed:
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| | use case |
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|---|---|
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| **Voxtral** | multilingual EN/FR/DE/ES/IT/PT/NL/HI streaming, 70 ms model latency |
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| Kokoro | low-latency English, fixed voice library |
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| Chatterbox Turbo | low-latency English w/ cloning + 9 paralinguistic tags |
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| Fish Audio S2-Pro | richest paralinguistic English (15k+ tags) |
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| IndexTTS-2 | English voice cloning + emotion vector / text control |
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| Qwen3-TTS-1.7B | English voice cloning (slow on official backend) |
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| CosyVoice 3 | multilingual (Chinese-leaning) |
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| VibeVoice 1.5B | long-form / multi-speaker dialogue |
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Voxtral fills the **multilingual + low-latency + cloning** slot
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that's been weak in the fleet (CosyVoice is multilingual but slow on
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English; nothing else is multilingual at all).
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## Headline numbers
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- **70 ms** model latency for a typical 10 s sample (500-char input)
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- **9.7×** realtime factor
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- **68.4%** blind A/B win rate vs ElevenLabs Flash v2.5 in voice
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cloning evaluations
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- **8 languages**: EN, FR, DE, ES, IT, PT, NL, HI
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## API
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vLLM-Omni serves an OpenAI-compatible API at
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`http://10.100.79.3:8201/v1`:
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```bash
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# Single-shot synthesis.
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curl -fsS -X POST http://10.100.79.3:8201/v1/audio/speech \
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-H 'Content-Type: application/json' \
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-d '{"model":"mistralai/Voxtral-4B-TTS-2603","input":"Hello there.","voice":"alloy","response_format":"wav"}' \
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> out.wav
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# Streaming.
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curl -fsS -X POST http://10.100.79.3:8201/v1/audio/speech \
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-H 'Content-Type: application/json' \
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-d '{"model":"mistralai/Voxtral-4B-TTS-2603","input":"long passage…","voice":"alloy","stream":true}' \
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| mpv --no-cache -
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# vLLM-Omni standard endpoints.
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curl http://10.100.79.3:8201/v1/models # confirms model loaded
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curl http://10.100.79.3:8201/v1/audio/voices # built-in + cloned voices
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```
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## Deploy
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```bash
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scripts/elway irv-ml1 --playbook playbooks/deploy-voxtral.yaml
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```
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First boot pulls Voxtral-4B (~8 GB BF16) into the HF cache + warms
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vLLM. Both are cached afterwards.
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## Hardware footprint
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- **VRAM**: ~16 GB practical (8 GB weights + KV + activation). Pinned
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to GPU 1 (RTX A6000) by default — comfortable headroom. The 3090's
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24 GB CAN fit but it's tight for long streaming sessions.
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- **Disk**: ~8 GB for the Voxtral checkpoint + HF cache.
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## Voice library
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Drop reference WAV / FLAC into `/worktank/voxtral/voices/` on the
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host. The wrapper scans on request — no restart needed.
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