Qwen3 TTS 12Hz 0.6B CustomVoice

ProviderQwen
Categorytext-to-speech
Licenseapache-2.0
Downloads62.2K
Stars20

Overview

Qwen3 TTS 12Hz 0.6B CustomVoice is a lightweight, high-efficiency text-to-speech model designed for low-latency deployment. At 0.6B parameters, it targets developers who need to balance natural-sounding voice synthesis with strict computational constraints, making it suitable for edge computing or high-concurrency server environments. Its primary strength lies in its CustomVoice capability, allowing for precise voice cloning and identity preservation. Unlike larger, resource-heavy TTS frameworks, this model prioritizes rapid inference and easy integration into real-time conversational pipelines. It is an ideal choice for building personalized AI assistants, automated narration tools, or accessibility software where minimal memory overhead is critical.

Highlights

  • Lightweight 0.6B parameter architecture for fast inference
  • High-fidelity voice cloning via CustomVoice capabilities
  • Low-latency performance optimized for real-time applications
  • Permissive Apache-2.0 license for commercial flexibility
  • Efficient memory footprint ideal for edge deployment

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-0.6B-CustomVoice")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice")

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-0.6B-CustomVoice

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-0.6B-CustomVoice 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-0.6B-CustomVoice')

Git Download

Make sure git-lfs is installed first

Git Download 
git lfs install
git clone https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice

To skip LFS large-file downloads, use:

Skip LFS 
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice

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-0.6B-CustomVoice')
tokenizer = AutoTokenizer.from_pretrained('Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice')

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-0.6B-CustomVoice

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-0.6B-CustomVoice 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-0.6B-CustomVoice')

Git Download

Make sure git-lfs is installed first

Git Download 
git lfs install
git clone https://www.modelscope.cn/Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice.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-0.6B-CustomVoice.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-0.6B-CustomVoice')

Full Documentation

来源: HuggingFace

---
license: apache-2.0
pipeline_tag: text-to-speech
language:

  • zh

  • en

  • ja

  • ko

  • de

  • fr

  • ru

  • pt

  • es

  • it

tags:
  • tts

  • qwen

  • audio

arxiv: 2601.15621
---

Qwen3-TTS-12Hz-0.6B-CustomVoice

Qwen3-TTS is a series of advanced multilingual, controllable, robust, and streaming text-to-speech models developed by the Qwen team.

This specific checkpoint is the 0.6B CustomVoice variant, based on the 12Hz tokenizer. It supports 9 premium timbres and allows for fine-grained style control over target voices via natural language instructions across 10 major languages.

Key Features

  • Multilingual Synthesis: Supports Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian.
  • Intelligent Control: Adapts tone, rhythm, and emotional expression based on natural language instructions (e.g., "Speak in a very happy tone").
  • Low Latency: Optimized for streaming generation with the Qwen3-TTS-Tokenizer-12Hz, achieving end-to-end synthesis latency as low as 97ms.

Quickstart

To use Qwen3-TTS, you can install the qwen-tts package:

bash
pip install -U qwen-tts

Sample Usage

python
import torch
import soundfile as sf
from qwen_tts import Qwen3TTSModel

Load the model

model = Qwen3TTSModel.from_pretrained(
    "Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice",
    device_map="cuda:0",
    dtype=torch.bfloat16,
    attn_implementation="flash_attention_2",
)

Generate speech with specific instructions

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", 
)

Save the generated audio

sf.write("output_custom_voice.wav", wavs[0], sr)

Supported Speakers

For Qwen3-TTS-12Hz-0.6B-CustomVoice, the following speakers are supported. We recommend using each speaker’s native language for the best results:

| Speaker | Voice Description | Native Language |
| --- | --- | --- |
| Vivian | Bright young female voice. | Chinese |
| Serena | Warm, gentle young female voice. | Chinese |
| Uncle_Fu | Seasoned male voice, mellow timbre. | Chinese |
| Dylan | Youthful Beijing male voice. | Chinese (Beijing) |
| Eric | Lively Chengdu male voice. | Chinese (Sichuan) |
| Ryan | Dynamic male voice with rhythm. | English |
| Aiden | Sunny American male voice. | English |
| Ono_Anna | Playful Japanese female voice. | Japanese |
| Sohee | Warm Korean female voice. | Korean |

Citation

If you find Qwen3-TTS useful for your research, please consider citing:
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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