Model reference · open weights

s2-pro

Audio fishaudio Text→speech 1 build Its own licence terms 344k dl/mo

s2-pro is an open-weight audio or speech model from fishaudio. s2-pro (BF16) weighs 11.0 GB; the smallest configuration that runs it is RTX 4060 Ti 16 GB.

  • Fish Audio S2 Pro is a 4.6B parameter text-to-speech model designed for fine-grained control of prosody and emotion.
  • It supports over 80 languages, including Chinese, English, Japanese, and Korean, and utilizes a dual-autoregressive architecture for efficient inference.
  • The model is released under the Fish Audio Research License, which permits free research and non-commercial use.

Summary of the fishaudio/s2-pro model card, 2026-10-01

What it is

Released byfishaudio
Released2026-03-09
Parameters4.6B
VRAM11.0 GB for the weights

What it runs on

Memory and cards for s2-pro (BF16)

11.0 GBweights, file size
1.6 GBruntime overhead
CardOne streamMemory
RTX 3060 12 GBdoes not fit11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

From the model card

What fishaudio says about s2-pro

Read the model card

Technical Report | GitHub | Playground

Fish Audio S2 Pro is a leading text-to-speech (TTS) model with fine-grained inline control of prosody and emotion. Trained on over 10M+ hours of audio data across 80+ languages, the system combines reinforcement learning alignment with a dual-autoregressive architecture. The release includes model weights, fine-tuning code, and an SGLang-based streaming inference engine.

Architecture

S2 Pro builds on a decoder-only transformer combined with an RVQ-based audio codec (10 codebooks, ~21 Hz frame rate) using a Dual-Autoregressive (Dual-AR) architecture:

  • Slow AR (4B parameters): Operates along the time axis and predicts the primary semantic codebook.
  • Fast AR (400M parameters): Generates the remaining 9 residual codebooks at each time step, reconstructing fine-grained acoustic detail.

This asymmetric design keeps inference efficient while preserving audio fidelity. Because the Dual-AR architecture is structurally isomorphic to standard autoregressive LLMs, it inherits all LLM-native serving optimizations from SGLang — including continuous batching, paged KV cache, CUDA graph replay, and RadixAttention-based prefix caching.

Fine-Grained Inline Control

S2 Pro enables localized control over speech generation by embedding natural-language instructions directly within the text using [tag] syntax. Rather than relying on a fixed set of predefined tags, S2 Pro accepts free-form textual descriptions — such as [whisper in small voice], [professional broadcast tone], or [pitch up] — allowing open-ended expression control at the word level.

Common tags (15,000+ unique tags supported):

[pause] [emphasis] [laughing] [inhale] [chuckle] [tsk] [singing] [excited] [laughing tone] [interrupting] [chuckling] [excited tone] [volume up] [echo] [angry] [low volume] [sigh] [low voice] [whisper] [screaming] [shouting] [loud] [surprised] [short pause] [exhale] [delight] [panting] [audience laughter] [with strong accent] [volume down] [clearing throat] [sad] [moaning] [shocked]

Supported Languages

S2 Pro supports 80+ languages.

Tier 1: Japanese (ja), English (en), Chinese (zh)

Tier 2: Korean (ko), Spanish (es), Portuguese (pt), Arabic (ar), Russian (ru), French (fr), German (de)

Other supported languages: sv, it, tr, no, nl, cy, eu, ca, da, gl, ta, hu, fi, pl, et, hi, la, ur, th, vi, jw, bn, yo, xsl, cs, sw, nn, he, ms, uk, id, kk, bg, lv, my, tl, sk, ne, fa, af, el, bo, hr, ro, sn, mi, yi, am, be, km, is, az, sd, br, sq, ps, mn, ht, ml, sr, sa, te, ka, bs, pa, lt, kn, si, hy, mr, as, gu, fo, and more.

Production Streaming Performance

On a single NVIDIA H200 GPU:

  • Real-Time Factor (RTF): 0.195
  • Time-to-first-audio: ~100 ms
  • Throughput: 3,000+ acoustic tokens/s while maintaining RTF below 0.5

Links

Technical Report

If you find our work useful, please consider citing our report:

@misc{liao2026fishaudios2technical,
      title={Fish Audio S2 Technical Report},
      author={Shijia Liao and Yuxuan Wang and Songting Liu and Yifan Cheng and Ruoyi Zhang and Tianyu Li and Shidong Li and Yisheng Zheng and Xingwei Liu and Qingzheng Wang and Zhizhuo Zhou and Jiahua Liu and Xin Chen and Dawei Han},
      year={2026},
      eprint={2603.08823},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2603.08823},
}

License

This model is licensed under the Fish Audio Research License. Research and non-commercial use is permitted free of charge. Commercial use requires a separate license from Fish Audio — contact business@fish.audio.

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

How it works

How audio & music work

Audio or textinputAudio modelrecognise / synthesiseText or audiooutputSpeech-to-text turns audio into text; text-to-speech and music models turn text into audio.
© 2026 AxForge · EU-hosted AI infrastructure Pricing Docs Trust Privacy Terms