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Coqui

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Coqui was an open-source speech technology project known for its text-to-speech and voice cloning models, including XTTS, aimed at developers building voice applications.

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ai-speech-synthesisai-voice-cloningtext-to-speech-2
Last Updated Nov 10, 2026

About

Coqui is best known as an open-source speech technology project focused on text-to-speech and voice cloning. Its models, most notably XTTS, let developers generate spoken audio from written text and create synthetic voices from short samples of a speaker's audio, addressing the need for flexible, self-hostable voice generation rather than locked-in commercial services.

At a high level, Coqui's software took input text, processed it through a neural speech model, and produced natural-sounding audio output, optionally in the style of a cloned voice and across multiple languages. The project grew out of earlier open-source speech research and released its code and model weights publicly so developers could run it on their own infrastructure. Readers should note that when this page was compiled, the official site at coqui.ai was not reachable and returned an error page, so current availability and support status should be verified independently.

Key Features

Text-to-speech generation: Converts written text into spoken audio using neural models trained for natural-sounding output.
Voice cloning: Allows creating a synthetic voice from a short reference recording of a target speaker, useful for personalized voice output.
Open-source availability: Model code and weights were released publicly, so developers could inspect, modify, and self-host the technology.
Multilingual support: The XTTS model supported generating speech in several languages with a single model, reducing per-language setup work.
Developer-oriented tooling: The project provided Python libraries and command-line tools designed to be integrated into larger applications and pipelines.
Self-hosted deployment: Because the software could run locally, teams could keep audio data on their own machines instead of sending it to an external service.

Pricing & Fees

  • Pricing: Not publicly listed on the pages we reviewed; check the official site for current plans.
  • Site availability: The official domain at coqui.ai returned an error page at the time of review, so links and product claims should be verified before relying on them.
  • Open-source foundation: The core models, including XTTS, were released openly, and copies continue to circulate in the open-source community even though the company behind them is no longer active.

Who It's For

Coqui's tooling was aimed primarily at developers who wanted to add speech output or voice cloning to their own applications without depending on a hosted API. Typical users included indie game creators producing character dialogue, audiobook and podcast producers generating narration drafts, and teams building accessibility features such as screen readers or alternative communication voices. Researchers experimenting with speech synthesis also valued the open model weights, since they could be fine-tuned and studied locally.

FAQ

What is Coqui?Coqui was an open-source speech technology project that produced text-to-speech and voice cloning models, including the multilingual XTTS model, for developers to run and integrate themselves.

Is Coqui free to use?The core models and code were released as open source, so they could be used without a paid license subject to the terms of the specific license; current commercial arrangements are not publicly listed on the pages we reviewed.

Is the Coqui website still working?When this page was compiled, coqui.ai returned an error page rather than product content, so readers should verify current availability through official or community channels.

Which platforms does Coqui run on?The software was distributed as Python libraries and command-line tools, meaning it could run on standard desktop and server environments where Python and suitable hardware were available.

Does Coqui require sending data to a cloud service?No; because the models were open source and self-hostable, users could generate speech entirely on their own hardware without sending text or audio to an external provider.

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