Model reference · open weights

sarashina2.2-tts

Audio sbintuitions Text→speech 1 build Licence not stated 7k dl/mo

sarashina2.2-tts is an open-weight audio or speech model from sbintuitions. sarashina2.2-tts (FP32) weighs 2.2 GB; the smallest configuration that runs it is RTX 3060 12 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • Sarashina2.2-TTS is an 810M parameter text-to-speech model developed by sbintuitions that supports Japanese and English.
  • It features zero-shot voice generation and handles code switching between the two languages.
  • The model has a context length of 8192 tokens and is distributed under the Sarashina Model NonCommercial License Agreement.

Summary of the sbintuitions/sarashina2.2-tts model card, 2026-10-01

What it is

Released bysbintuitions
Released2026-04-16
Parameters810M
VRAM2.2 GB for the weights

What it runs on

Memory and cards for sarashina2.2-tts (FP32)

2.2 GBweights, file size
1.6 GBruntime overhead
CardOne streamMemory
RTX 3060 12 GBfits11.6 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 sbintuitions says about sarashina2.2-tts

Read the model card

Sarashina2.2-TTS is a Japanese-centric text-to-speech system built on a large language model, developed by SB Intuitions. It supports Japanese and English, delivering high pronunciation accuracy, naturalness, and stability across diverse speaking styles, with zero-shot voice generation support.

Highlights

  • 🇯🇵 Japanese-Centric: Designed and optimized specifically for Japanese, with broad coverage of real-world use cases.
  • 🎯 High Accuracy: Delivers strong pronunciation accuracy on Japanese text through large-scale end-to-end training.
  • 🔒 Responsibly Sourced Training Data: Trained exclusively on legitimately acquired and properly licensed speech data.
  • 🎙️ Zero-shot Voice Generation: Reproduces a speaker's voice, speaking style, and acoustic characteristics from a short reference clip.
  • 🔊 Natural & Expressive: Produces highly natural speech with consistent quality, supporting a wide range of speaking styles including narration, broadcast, conversation, and customer service.
  • 🌐 Bilingual: Supports both Japanese and English text-to-speech synthesis.

Training Data

This model was trained on audio data collected from legitimately purchased audio sources, public speech archives, and data gathered in compliance with applicable domestic laws. During collection, we adhered to robots.txt directives and terms of service to ensure proper data acquisition.

Usage

For installation instructions, Docker setup, and detailed usage, please refer to the GitHub repository.

Audio Samples

The samples below demonstrate key capabilities of Sarashina2.2-TTS:

  • Speaking Style Variety: Transfers diverse speaking styles — narration, broadcast, conversation, customer service, and more — from reference audio.
  • Zero-shot Voice Cloning: Reproduces a speaker's voice from just a few seconds of reference speech, with no fine-tuning required.
  • Cross-lingual Generation: Preserves speaker identity and speaking style consistently across Japanese and English.
  • Code Switching: Handles mixed Japanese-English sentences naturally within a single utterance.
Quick Sample
Speaking Style Variety
Zero-shot Voice Generation
Cross-lingual Zero-shot
Code Switching

Acknowledgments

This model is built upon or incorporates code and models from the following open-source projects:

Citation

@misc{liu2026sarashina22ttstacklingkanjipolyphony,
      title={Sarashina2.2-TTS: Tackling Kanji Polyphony in Japanese Speech Generation via Data Scaling and Targeted Data Synthesis},
      author={Lianbo Liu and Shiao Zhu and Kai Washizaki and Reo Yoneyama and Haesung Jeon and Mengjie Zhao and Yusuke Fujita and Hao Shi and Nao Yoshida and Yuan Gao and Roman Koshkin and Yukiya Hono and Yui Sudo},
      year={2026},
      eprint={2606.25369},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2606.25369},
}

License

This model is licensed under Sarashina Model NonCommercial License Agreement.

If you are interested in using this model for commercial purposes, please feel free to contact us through our contact page.

The audio provided on this page are for research purposes only and may not be redistributed or used for commercial purposes.

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

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