qwen-tts
Qwen-TTS python package
Decision gist · record as of 2026-08-14
Yes, if you need multilingual text-to-speech with voice cloning and instruction-based control. The low install friction and permissive license are favorable. However, the package is very recent (first release 2026-01-22) with aging maintenance status, so expect potential API changes and monitor for updates. Test thoroughly before production use, especially for latency-sensitive applications.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9+; model weights auto-download on first use (can be pre-downloaded via modelscope or huggingface-cli if network-constrained).
- Low friction: pure Python wheel with no compiled dependencies.
- Aging status (189 days since release) suggests early-stage maintenance; monitor for updates as the package matures.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; attribution required but no copyleft obligations.
last release 2026-02-06 (189 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 223,339 downloads/mo, #9,247 on PyPI
Alternatives
Verify before relying
pip install qwen-tts
from qwen_tts import TTS
tts = TTS(model="Qwen3-TTS-12Hz-1.7B-CustomVoice")
audio = tts.generate("Hello world")- Actual latency and quality characteristics in production deployments (description claims 97ms end-to-end but real-world variance is unknown).
- Memory and GPU requirements for each model variant (0.6B and 1.7B sizes mentioned but resource profiles not detailed).
- Stability and API surface maturity given first_release is 2026-01-22 (very recent).
What it is and what it does
Qwen-TTS is a Python wrapper for Alibaba's Qwen3-TTS speech generation models. It lets you convert text to speech in 10 languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, Italian) with fine-grained control over voice characteristics. The package supports three main workflows: custom voice generation from text descriptions, voice cloning from a 3-second audio sample, and instruction-based voice design where you describe desired acoustic properties (timbre, emotion, prosody) and the model adapts output accordingly.
The underlying models use a discrete multi-codebook language model architecture for end-to-end speech generation, avoiding cascading errors from traditional pipeline approaches. Both streaming (output starts after a single character) and non-streaming modes are supported. Runtime dependencies include transformers, torchaudio, librosa, and onnxruntime for inference, plus gradio for the optional web UI. Model weights download automatically from Hugging Face or ModelScope on first use.
Use it for
- Generate natural-sounding voiceovers for videos or podcasts in multiple languages with custom voice profiles.
- Clone a speaker's voice from a short audio clip and use it to synthesize new speech in the same voice.
- Build interactive voice assistants that respond with emotionally appropriate speech based on text instructions.
- Create accessible audio versions of documents by converting text to speech with fine-tuned prosody and tone.
- Prototype multilingual speech applications without training custom models from scratch.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need multilingual text-to-speech with voice cloning and instruction-based control.
The low install friction and permissive license are favorable. However, the package is very recent (first release 2026-01-22) with aging maintenance status, so expect potential API changes and monitor for updates. Test thoroughly before production use, especially for latency-sensitive applications.
Install
qwen-tts on PyPI
Before you install
Low friction: pure Python wheel with no compiled dependencies. Aging status (189 days since release) suggests early-stage maintenance; monitor for updates as the package matures.
Requires Python 3.9+; model weights auto-download on first use (can be pre-downloaded via modelscope or huggingface-cli if network-constrained).
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; attribution required but no copyleft obligations.
Quickstart
pip install qwen-tts
from qwen_tts import TTS
tts = TTS(model="Qwen3-TTS-12Hz-1.7B-CustomVoice")
audio = tts.generate("Hello world")Verify before relying
- Actual latency and quality characteristics in production deployments (description claims 97ms end-to-end but real-world variance is unknown).
- Memory and GPU requirements for each model variant (0.6B and 1.7B sizes mentioned but resource profiles not detailed).
- Stability and API surface maturity given first_release is 2026-01-22 (very recent).
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 9 packagestransformersaccelerategradiolibrosatorchaudiosoundfilesoxonnxruntimeeinops |
| Maintenance | Aging 189 days since the last release |
| First released | |
| Downloads | 223,339 / month, #9,247 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Programming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9 |
Evidence: qwen_tts-0.1.1-py3-none-any.whl
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See also qwen-asr · voxcpm · chatterbox-tts · omnivoice · pocket-tts · TTS · transformers-stream-generator · qwen-agent · coqui-tts · mlx-audio