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LatestKyutai1.0
KyutaiText → Speech

Kyutai Releases 1.6B Bilingual TTS Model

The French AI lab's new open-source model generates streaming audio in English and French under a permissive license.

Jun 30, 2025
NotableCC BY 4.0
Kyutai TTS 1.6B (en/fr)

French AI research lab Kyutai has released a new 1.6-billion-parameter text-to-speech (TTS) model that generates high-quality audio in both English and French. The model is available under a permissive Creative Commons license (CC-BY-4.0), allowing for broad use, including in commercial applications.

The system is built on what the team calls the Moshi stack, an adaptation of the VoiceCraft architecture. A key feature is its ability to support streaming audio generation, making it suitable for real-time applications where low latency is critical, such as conversational agents or live narration tools.

A New Voice in Open TTS

While the open-source landscape for large language models has exploded, the space for high-quality, permissively licensed TTS models is less crowded. Kyutai's release provides a significant new building block for developers creating voice-enabled products without relying on proprietary, closed-source APIs.

As a non-profit lab, Kyutai's contribution adds valuable diversity to an ecosystem often dominated by a few large tech companies. Developers can access the model weights, explore an interactive demo, and find usage examples on the official Hugging Face repository.

Sources

  • kyutai/tts-1.6b-en_fr

    Hugging Face

    Visit
OlderZhipu AI Open-Sources 9B Vision Model with 'Thinking' ModeZhipu AI · Vision-Language · last yearNewerBoson AI Releases Higgs Audio v2 for Expressive TTSBosonai · Text → Speech · last year

Get the model

Hugging Face

Specs

Parameters1.6B
LanguagesEnglish, French
Architecturetts
LicenseCC-BY-4.0
Downloads69.5K
Likes385

Can you run it?

Runs on just about anything.

  • BF16 (as published)

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    4.2 GB
  • FP8

    Any modern laptop · 8 GB RAM

    2.6 GB
Your machine
  • Precision not published; assuming 16-bit (BF16) weights.
  • Parameter count is an editorial estimate — no weights metadata on Hugging Face.

Estimated from the parameter count. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Text → Speech

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