Qwen3 TTS 12Hz 1.7B VoiceDesign

ProviderQwen
Categorytext-to-speech
Licenseapache-2.0
Downloads312.0K
Stars86

Overview

Qwen3 TTS 12Hz 1.7B VoiceDesign is a lightweight, high-efficiency text-to-speech model designed for developers needing low-latency audio synthesis. At 1.7B parameters, it strikes a balance between computational overhead and prosodic quality, making it suitable for edge deployment or scalable cloud microservices. Unlike traditional TTS engines, this model focuses on 'VoiceDesign,' allowing for more nuanced control over vocal characteristics and emotional inflection. It integrates easily into existing AI pipelines via a standard Apache-2.0 license, offering a flexible alternative to proprietary APIs for real-time conversational agents, accessibility tools, and automated content generation where natural-sounding cadence is critical.

Highlights

  • Low-latency synthesis optimized for real-time interactive applications.
  • 1.7B parameter architecture balances performance and resource usage.
  • Advanced VoiceDesign capabilities for nuanced vocal control.
  • Permissive Apache-2.0 license for flexible commercial integration.
  • Ideal for edge deployment and scalable TTS microservices.

Usage

Install
# Install Hugging Face transformers
pip install transformers torch
SDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance：Before downloading, install huggingface_hub with:

Guidance 
pip install -U huggingface_hub

CLI Download

Download the full repository

Download the full repository 
huggingface-cli download Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign

Download a single file to a local folder (e.g. config.json into ./dir)

Download a single file to a local folder (e.g. config.json into ./dir) 
huggingface-cli download Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

SDK Download 
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign')

Git Download

Make sure git-lfs is installed first

Git Download 
git lfs install
git clone https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign

To skip LFS large-file downloads, use:

Skip LFS 
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

Install Transformers 
pip install -U transformers torch

Load the model and run inference

Load the model and run inference 
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign')
tokenizer = AutoTokenizer.from_pretrained('Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign')

Model Download

We recommend downloading the model via the ModelScope CLI or SDK.

Guidance：Before downloading, install ModelScope with:

Guidance 
pip install modelscope

CLI Download

Download the full repository

Download the full repository 
modelscope download --model Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign

Download a single file to a local folder (e.g. README.md into ./dir)

Download a single file to a local folder (e.g. README.md into ./dir) 
modelscope download --model Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign README.md --local_dir ./dir

See the docs for more CLI options

SDK Download

SDK Download 
# 模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign')

Git Download

Make sure git-lfs is installed first

Git Download 
git lfs install
git clone https://www.modelscope.cn/Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign.git

To skip LFS large-file downloads, use:

Skip LFS 
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign.git

ModelScope 模型页直接下载模型文件；无需将模型文件放在本站服务器。

Notebook Quickstart

Install the ModelScope library

Install the ModelScope library 
pip install "modelscope[audio,cv,nlp,multi-modal,science]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html

Load the model and run inference

Load the model and run inference 
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks

p = pipeline('text-generation', 'Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign')

Full Documentation

来源: HuggingFace

---
license: apache-2.0
pipeline_tag: text-to-speech
library_name: qwen-tts
tags:

  • audio

  • tts

  • qwen

  • multilingual

---

Qwen3-TTS

<br>

<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">
&nbsp&nbsp🤗 <a href="https://huggingface.co/collections/Qwen/qwen3-tts">Hugging Face</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/collections/Qwen/Qwen3-TTS">ModelScope</a>&nbsp&nbsp | &nbsp&nbsp📑 <a href="https://qwen.ai/blog?id=qwen3tts-0115">Blog</a>&nbsp&nbsp | &nbsp&nbsp📑 <a href="https://huggingface.co/papers/2601.15621">Paper</a>&nbsp&nbsp | &nbsp&nbsp💻 <a href="https://github.com/QwenLM/Qwen3-TTS">GitHub</a>
</p>

We release Qwen3-TTS, a series of powerful speech generation models developed by Qwen, offering comprehensive support for voice cloning, voice design, ultra-high-quality human-like speech generation, and natural language-based voice control.

Overview

Qwen3-TTS covers 10 major languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) as well as multiple dialectal voice profiles. Key features:
  • Powerful Speech Representation: Powered by the self-developed Qwen3-TTS-Tokenizer-12Hz, it achieves efficient acoustic compression and high-dimensional semantic modeling.
  • Universal End-to-End Architecture: Utilizing a discrete multi-codebook LM architecture to bypass traditional information bottlenecks.
  • Extreme Low-Latency Streaming Generation: Supports streaming generation with end-to-end synthesis latency as low as 97ms.
  • Intelligent Voice Control: Supports speech generation driven by natural language instructions for flexible control over timbre, emotion, and prosody.

Quickstart

Environment Setup

Install the qwen-tts Python package from PyPI:

bash
pip install -U qwen-tts

Python Package Usage

python
import torch
import soundfile as sf
from qwen_tts import Qwen3TTSModel

Load the model

model = Qwen3TTSModel.from_pretrained(
    "Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice",
    device_map="cuda:0",
    dtype=torch.bfloat16,
    attn_implementation="flash_attention_2",
)

Custom Voice Generation

wavs, sr = model.generate_custom_voice(
    text="其实我真的有发现，我是一个特别善于观察别人情绪的人。",
    language="Chinese",
    speaker="Vivian",
    instruct="用特别愤怒的语气说",
)
sf.write("output.wav", wavs[0], sr)

Evaluation

Zero-shot speech generation on the Seed-TTS test set (Word Error Rate (WER, ↓)):

| Model | test-zh | test-en |
|---|---|---|
| Qwen3-TTS-12Hz-1.7B-Base | 0.77 | 1.24 |

Citation

If you find our paper and code useful in your research, please consider giving a star ⭐ and citation 📝:

BibTeX
@article{Qwen3-TTS,
  title={Qwen3-TTS Technical Report},
  author={Hangrui Hu and Xinfa Zhu and Ting He and Dake Guo and Bin Zhang and Xiong Wang and Zhifang Guo and Ziyue Jiang and Hongkun Hao and Zishan Guo and Xinyu Zhang and Pei Zhang and Baosong Yang and Jin Xu and Jingren Zhou and Junyang Lin},
  journal={arXiv preprint arXiv:2601.15621},
  year={2026}
}
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