F5-TTS

F5-TTS is an open-source text-to-speech system with more than 15,400 stars on GitHub that generates fluent, faithful, natural-sounding speech using flow matching — the official code release of the F5-TTS research paper.

Overview

Traditional TTS pipelines chain together duration models, phoneme converters, and vocoders, and each stage can introduce errors. F5-TTS takes a cleaner route: it frames speech generation as flow matching over mel spectrograms, learning to turn noise into speech in a single, elegant process conditioned on text and a short reference recording. The practical result is convincing zero-shot voice cloning — give it a few seconds of reference audio and its transcript, and it speaks new text in that voice with natural rhythm and intonation. The repository ships the full training and inference code, pretrained checkpoints, and ready-to-run demos, so researchers can reproduce the paper and developers can build on top of it. It has become a popular foundation for voice products and experiments, is MIT licensed, and remains actively maintained with updates in 2026.

Key Features

• Flow-matching generation – a Diffusion Transformer trained with flow matching produces smooth, high-fidelity speech.
• Zero-shot voice cloning – clone a voice from a short reference clip and its transcript, no fine-tuning required.
• Fluent and faithful output – designed to pronounce text accurately while sounding natural rather than robotic.
• Training and inference code – reproduce the results or fine-tune on your own dataset.
• Pretrained checkpoints – ready-made models published for immediate experimentation.
• Interactive demos – Gradio-based apps for quick synthesis tests, including multi-style and emotion experiments.
• Efficient sampling – sway sampling and modern ODE solvers keep generation fast.

💳 Pricing

F5-TTS is completely free and open source under the MIT license. You can download the code and pretrained models, run them on your own hardware, and use them in your own projects without paying the authors anything.

Who Is It For

Speech researchers, voice-product developers, and hobbyists who want state-of-the-art open text-to-speech — whether for prototyping a voice assistant, generating narration, or studying modern generative speech models.