vllm-omni/recipes/fishaudio/Fish-Speech-S2-Pro.md

Fish Speech S2 Pro

Summary

• Vendor: FishAudio
• Model: fishaudio/s2-pro
• Task: Text-to-speech synthesis with optional voice cloning
• Mode: Online serving with the OpenAI-compatible /v1/audio/speech API
• Maintainer: Community

When to use this recipe

Use this recipe as a practical baseline for running fishaudio/s2-pro for high-quality text-to-speech synthesis. Fish Speech S2 Pro outputs 44.1 kHz audio and supports voice cloning from reference audio.

References

• User guide: docs/user_guide/examples/online_serving/fish_speech.md
• Example guide: examples/online_serving/fish_speech/README.md
• Related issue or discussion: RFC: add recipes folder

Hardware Support

This recipe documents reference GPU configuration for Fish Speech S2 Pro. Other hardware and configurations are welcome as community validation lands.

GPU

1x A800 80GB

Environment

• OS: Linux
• Python: 3.10+
• Required package: fish-speech (for DAC codec)
• CUDA 12.8
• vLLM version: 0.19.0
• vLLM-Omni version or commit: c93359bb35

# Install PortAudio dependency if missing (required by pyaudio which is a dependency of fish-speech)
# For Ubuntu/Debian:
if ! dpkg -l | grep -q libportaudio2; then
    sudo apt-get update && sudo apt-get install -y libportaudio2 portaudio19-dev
fi
pip install fish-speech

Command

vllm serve fishaudio/s2-pro --omni --port 8091

Notes:

• --omni is required.
• The default deploy config vllm_omni/deploy/fish_qwen3_omni.yaml is loaded automatically by model registry (HF model_type=fish_qwen3_omni).

Verification

Basic TTS:

curl -X POST http://localhost:8091/v1/audio/speech \
    -H "Content-Type: application/json" \
    -d '{
        "input": "Hello, how are you?",
        "voice": "default",
        "response_format": "wav"
    }' --output output.wav

output.wav

Voice cloning:

curl -X POST http://localhost:8091/v1/audio/speech \
    -H "Content-Type: application/json" \
    -d '{
        "input": "Hello, this is a cloned voice.",
        "voice": "default",
        "ref_audio": "https://example.com/reference.wav",
        "ref_text": "Transcript of the reference audio."
    }' --output cloned.wav

reference.wav
cloned.wav

Notes

• Key flags: --omni is required.
• Known limitations: Output audio is 44.1 kHz mono WAV. Voice cloning requires both ref_audio and ref_text parameters.
• Memory usage: Model loads at ~48.3 GiB, peaks at ~48.9 GiB during inference headroom for video frames and audio caches.