Coqui, The Jouster's Review

The Essentials

• Open source AI TTS and voice cloning
• Pay as you go, models available on Hugging Face for free
• XTTS model for multilingual cloning, realistic synthesis
• Suited for developers and researchers who want AI voice with total control over their data

What is Coqui?

Coqui is a company that developed open source text-to-speech (TTS) and voice cloning models. The most notable project is TTS (formerly Mozilla TTS) and more recently XTTS, a model capable of cloning a voice from a few seconds of audio and generating speech in that voice across multiple languages. Models are available on Hugging Face and PyPI. Coqui.ai also offered a commercial API, but the company's situation has evolved. The open source models remain active and widely used.

Strengths

XTTS: multilingual voice cloning from seconds of audio

XTTS is the flagship model. It can clone a voice from 3 to 30 seconds of reference audio and generate speech in that voice in multiple languages. The quality of voice matching is very good for an open source model.

Total control via open source

Since models are open source and deployable locally, you maintain complete control over your data. No voice or text sent to third-party servers. For sensitive use cases (audiobooks, dubbing, confidential content), it's a decisive advantage.

Rich community ecosystem

XTTS is integrated into ComfyUI, AllTalk TTS, and many open source projects. A large community of developers builds around Coqui models.

Limitations

Requires technical skills for deployment

Installing and running XTTS locally requires Python, specific dependencies and preferably a GPU. It's not a plug-and-play tool for non-developers.

Coqui's company situation is uncertain

Coqui.ai as a company has faced difficulties. Open source models continue to be maintained by the community, but commercial support and official updates are less clear. Check the current state on GitHub before committing a critical project to it.

CPU generation speed too slow for production

On CPU alone, generation is slow. An NVIDIA GPU with CUDA considerably speeds up generation time. For large-scale production, GPU costs can exceed the pay-as-you-go of competing APIs.

Pricing

Pay as you go on the coqui.ai API (availability to check). Open source models are free. Check coqui.ai and the project's GitHub for the current situation.

Alternatives

For a more stable commercial TTS API: ElevenLabs. For general public AI voice: Murf. For another open source model: StyleTTS2 or Bark.

Verdict

Coqui and XTTS remain a technical reference for open source TTS. If you have the skills to deploy it, multilingual cloning and data control are significant advantages. For production use without DevOps skills, ElevenLabs or Murf are more accessible.

FAQ

Can XTTS clone a voice in languages other than English?

Yes, XTTS supports many languages. The quality of cloning is generally good.

How many seconds of audio do you need to clone a voice with XTTS?

XTTS can clone a voice from 3 seconds of audio. A few extra seconds improve matching quality. Between 10 and 30 seconds is the sweet spot.

Can XTTS cloned voices be used commercially?

XTTS license terms allow commercial use under certain conditions. Check the license on Coqui's GitHub for exact terms before any commercial use.

What GPU is recommended for XTTS?

An NVIDIA GPU with at minimum 6 GB VRAM is recommended. An RTX 3060 or higher offers acceptable generation times.

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