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OpenMOSS (SII) avatar

MOSS-TTS

Open speech and sound model family for TTS, dialogue, and effects

  • AI media
  • AI models and runtimes
View on GitHub
Website

What it is

MOSS-TTS is a set of open-weight models for generating speech and audio: long-form narration, multi-speaker dialogue, voice cloning, voice design from text prompts, environmental sound effects, and low-latency streaming speech. Sizes range from a roughly 100M-parameter model that runs on a CPU to a 4B model with 48 kHz stereo output, and the repo includes inference code, fine-tuning tutorials, and support for serving backends such as SGLang, vLLM-Omni, llama.cpp, and mlx-audio. Developers building podcasts, dubbing, narration, or voice features into their own products can run and adapt the models locally.

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Facts

Stars
4,231 GitHub stars.
4,231

Forks
409
Commits
75
Contributors
20
Language
Python
License
Apache-2.0
Last commit
Sep 6, 2026
On GitHub since
February 2026
Platforms
Linux, library
Self-hostable
No
Alternative to
ElevenLabs, OpenAI TTS
Tags
  • text-to-speech
  • open-weights
  • voice-cloning
  • local-ai
  • fine-tuning

Last synced from GitHub on Oct 20, 2026

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