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Qwen3-TTS is an open-source series of TTS models developed by the Qwen team at Alibaba Cloud, supporting stable, expressive, and streaming speech generation, free-form voice design, and vivid voice cloning.
| Date | Stars |
|---|---|
| 2026-07-31 | 12692 |
| 2026-08-01 | 12692 |
| 2026-08-06 | 12823 |
Today
+131 stars today
This week
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This month
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Momentum
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# Qwen3-TTS
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<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/qwen3_tts_logo.png" width="400"/>
<p>
<p align="center">
  🤗 <a href="https://huggingface.co/collections/Qwen/qwen3-tts">Hugging Face</a>   |   🤖 <a href="https://modelscope.cn/collections/Qwen/Qwen3-TTS">ModelScope</a>   |   📑 <a href="https://qwen.ai/blog?id=qwen3tts-0115">Blog</a>   |   📑 <a href="https://arxiv.org/abs/2601.15621">Paper</a>  
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🖥️ <a href="https://huggingface.co/spaces/Qwen/Qwen3-TTS">Hugging Face Demo</a>   |    🖥️ <a href="https://modelscope.cn/studios/Qwen/Qwen3-TTS">ModelScope Demo</a>   |   💬 <a href="https://github.com/QwenLM/Qwen/blob/main/assets/wechat.png">WeChat (微信)</a>   |   🫨 <a href="https://discord.gg/CV4E9rpNSD">Discord</a>   |   📑 <a href="https://help.aliyun.com/zh/model-studio/qwen-tts-realtime">API</a>
</p>
We release **Qwen3-TTS**, a series of powerful speech generation capabilities developed by Qwen, offering comprehensive support for voice clone, voice design, ultra-high-quality human-like speech generation, and natural language-based voice control. It provides developers and users with the most extensive set of speech generation features available.
## News
* 2026.1.22: 🎉🎉🎉 We have released [Qwen3-TTS](https://huggingface.co/collections/Qwen/qwen3-tts) series (0.6B/1.7B) based on Qwen3-TTS-Tokenizer-12Hz. Please check our [blog](https://qwen.ai/blog?id=qwen3tts-0115)!
## Contents <!-- omit in toc -->
- [Overview](#overview)
- [Introduction](#introduction)
- [Model Architecture](#model-architecture)
- [Released Models Description and Download](#released-models-description-and-download)
- [Quickstart](#quickstart)
- [Environment Setup](#environment-setup)
- [Python Package Usage](#python-package-usage)
- [Custom Voice Generation](#custom-voice-generate)
- [Voice Design](#voice-design)
- [Voice Clone](#voice-clone)
- [Voice Design then Clone](#voice-design-then-clone)
- [Tokenizer Encode and Decode](#tokenizer-encode-and-decode)
- [Launch Local Web UI Demo](#launch-local-web-ui-demo)
- [DashScope API Usage](#dashscope-api-usage)
- [vLLM Usage](#vllm-usage)
- [Fine Tuning](#fine-tuning)
- [Evaluation](#evaluation)
- [Citation](#citation)
## Overview
### Introduction
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/qwen3_tts_introduction.png" width="90%"/>
<p>
Qwen3-TTS covers 10 major languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) as well as multiple dialectal voice profiles to meet global application needs. In addition, the models feature strong contextual understanding, enabling adaptive control of tone, speaking rate, and emotional expression based on instructions and text semantics, and they show markedly improved robustness to noisy input text. Key features:
* **Powerful Speech Representation**: Powered by the self-developed Qwen3-TTS-Tokenizer-12Hz, it achieves efficient acoustic compression and high-dimensional semantic modeling of speech signals. It fully preserves paralinguistic information and acoustic environmental features, enabling high-speed, high-fidelity speech reconstruction through a lightweight non-DiT architecture.
* **Universal End-to-End Architecture**: Utilizing a discrete multi-codebook LM architecture, it realizes full-information end-to-end speech modeling. This completely bypasses the information bottlenecks and cascading errors inherent in traditional LM+DiT schemes, significantly enhancing the model’s versatility, generation efficiency, and performance ceiling.
* **Extreme Low-Latency Streaming Generation**: Based on the innovative Dual-Track hybrid streaming generation architecture, a single model supports both streaming and non-streaming generation. It can Excerpt of 60,022 characters
Read on GitHub
Xiong Wang · Alibaba Qwen Team · China
11
Anton Vlasjuk
2
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4c3017c463804fd3, desc:voice cloning