Áudio
Kokoro-FastAPI
Turn the beloved Kokoro voice model into an OpenAI-compatible speech API with one Docker command.
★ 5,5 mil estrelasApache-2.0
Ver o guia →// audio · QwenLM/Qwen3-TTS
Qwen3-TTS
Qwen3-TTS é um projeto de áudio de código aberto de QwenLM (QwenLM/Qwen3-TTS no GitHub). Tem 13.619 estrelas no GitHub e 1.764 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 17 de março de 2026.
Alibaba's open voice models: expressive, streaming-capable speech with free-form voice design.
★ 13,6 mil estrelas⑂ 1,8 mil forksApache-2.0atualizado mar 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto
Dados do projeto
- Repositório
- QwenLM/Qwen3-TTS
- Estrelas no GitHub
- 13.619
- Forks
- 1.764
- Licença
- Apache-2.0
- Última atualização no GitHub
- 17 de março de 2026
- Categoria
- Áudio
- Tipo de ficha
- Guia de instalação completo
- Site oficial
- Read the docs
// como funciona
Como funciona
- Set up a clean environment
Create an isolated Python 3.12 environment so the audio dependencies don't clash with your other projects.
- Install the package
One pip command pulls the runtime and lets you load any released Qwen3-TTS model.
- Load a model and synthesize
Pick a model size for your hardware, feed it text, and get expressive speech — with streaming for realtime use.
- Design or clone voices
Describe the voice you want in words, or provide a short sample to clone it, then reuse it across projects.
// recursos
Por que as pessoas gostam tanto
Expressive neural voices
Natural intonation and emotion, well beyond robotic reader voices.
Streaming generation
Audio starts flowing before the full text is processed — ideal for live agents and assistants.
Free-form voice design
Describe a voice in plain language (“warm, middle-aged narrator”) and get it.
Voice cloning
Clone a voice from a short sample for consistent characters and branding.
A family of sizes
Multiple released models so you can trade quality against speed and VRAM.
Apache-2.0
Permissive licensing for personal and commercial projects.
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// execute você mesmo
Execute você mesmo
- Step 1 — Create the environment
Make a fresh, isolated Python 3.12 environment.
conda create -n qwen3-tts python=3.12 -y conda activate qwen3-tts - Step 2 — Install
Install the qwen-tts package from PyPI.
pip install -U qwen-tts - Step 3 — Save VRAM (optional)
Add FlashAttention 2 to cut GPU memory usage.
pip install -U flash-attn --no-build-isolation
// casos de uso
O que você pode criar
- Voices for conversational AI and realtime agents.
- Multilingual narration and dubbing.
- Consistent character voices for series and games.
- Prototyping voice products without API bills.
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// perguntas frequentes
Perguntas frequentes
Qwen3-TTS or Kokoro?
Qwen3-TTS brings larger, more expressive models with streaming and voice design. Kokoro is lighter and faster to run. Choose expressive depth or lightweight speed.
Do I need a GPU?
A GPU is recommended for comfortable speeds; FlashAttention 2 substantially reduces the memory footprint.
Does it stream audio?
Yes — streaming generation is a headline feature, built for realtime applications.
Who makes it?
The Qwen team at Alibaba Cloud, the same group behind the popular Qwen language models.
Can I use it commercially?
Yes — it is released under the Apache-2.0 license.
// continue explorando
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// mais em audio
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Baixe o Qwen3-TTS
Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.