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F5-TTS

F5-TTS is an open-source text-to-speech project for generating speech from text, with command-line inference and a Gradio web interface.

Place
#159 of 232
Score
6.6
F5-TTS's website

What F5-TTS is

F5-TTS is an open-source text-to-speech project for generating speech from text, with command-line inference and a Gradio web interface. Its approach uses flow matching and a Diffusion Transformer with ConvNeXt V2; the project also includes E2 TTS, which uses a Flat-UNet Transformer. The Gradio app supports chunked inference, multiple styles and speakers, and voice chat powered by Qwen2.5-3B-Instruct. Custom inference instructions cover adding language support. Users can install it as a Python package, run it from an editable local clone, or build and run it with Docker. Training and fine-tuning are supported through Hugging Face Accelerate or a Gradio app. Installation guidance covers NVIDIA, AMD and Intel GPUs, as well as Apple Silicon; AMD ROCm instructions specify Linux. The project also describes deployment with Triton and TensorRT-LLM. Requirements include Python 3.10 or newer and FFmpeg. The code is under the MIT License, but pre-trained models use CC-BY-NC, and commercial use is listed as unavailable.

Good

  • Offers command-line and Gradio interfaces.
  • Supports multiple styles and speakers.
  • Training and fine-tuning are supported.
  • Installation guidance covers several GPU types.
  • Custom language support instructions are linked.

Watch out

  • Requires Python 3.10 or newer and FFmpeg.
  • Pre-trained models use CC-BY-NC licensing.
  • Commercial use is listed as unavailable.
  • AMD ROCm instructions specify Linux.

Who it suits

F5-TTS may suit developers and researchers seeking an open-source speech-generation project with configurable inference and training options. It is not suitable for commercial use under the listed terms for the pre-trained models.

Verdict

F5-TTS offers several ways to run and adapt speech generation, including a web interface, CLI and training paths. Review the separate code and model licenses before use, especially for commercial projects.

The facts

Each one read from F5-TTS's own pages, with the date it was checked.

What it does

API access
Yeschecked 20 Sep 2026
Commercial use
Nochecked 20 Sep 2026
Custom languages
The README links to custom inference instructions for adding language support.checked 8 Oct 2026
Deployment
The README describes a deployment solution using Triton and TensorRT-LLM.checked 8 Oct 2026
Hardware and operating systems
The installation instructions cover NVIDIA, AMD, and Intel GPUs and Apple Silicon; the AMD ROCm instructions specify Linux.checked 8 Oct 2026
Hardware requirements
The installation instructions cover NVIDIA, AMD, Intel, and Apple Silicon setups; the AMD ROCm instructions specify Linux.checked 8 Oct 2026
Inference features
The Gradio app supports basic text-to-speech with chunk inference, multi-style and multi-speaker generation, and voice chat powered by Qwen2.5-3B-Instruct.checked 8 Oct 2026
Interfaces
The project provides a Gradio web interface and command-line inference.checked 8 Oct 2026
License
The code is released under the MIT License, while the pre-trained models are licensed under CC-BY-NC.checked 8 Oct 2026
Model availability
The README links F5-TTS and E2 TTS base models on Hugging Face, Model Scope, and Wisemodel.checked 8 Oct 2026
Model design
The project describes F5-TTS as a Diffusion Transformer with ConvNeXt V2 and includes E2 TTS, a Flat-UNet Transformer.checked 8 Oct 2026
Purpose
F5-TTS is an open-source text-to-speech project that uses flow matching to generate fluent and faithful speech.checked 8 Oct 2026
Related tools
The project acknowledges Vocos and BigVGAN as vocoders and FunASR and faster-whisper among its evaluation tools.checked 8 Oct 2026
Requirements
The installation instructions call for Python 3.10 or newer and FFmpeg.checked 8 Oct 2026
Runtime benchmark
The README reports a 253 ms average latency for F5-TTS Base with Vocos at concurrency 2 on a single L20 GPU in its stated benchmark setup.checked 8 Oct 2026
Support guidance
The README recommends searching GitHub issues for help with problems encountered.checked 8 Oct 2026
Training
Training and fine-tuning are supported through Hugging Face Accelerate or a Gradio app.checked 8 Oct 2026
Voice cloning
Yeschecked 20 Sep 2026
Ways to run
The project can be installed as a Python package, run from a local editable clone, or built and run with Docker.checked 8 Oct 2026
Web interface
The project provides Gradio commands for launching a web interface and a share link.checked 8 Oct 2026

Where it runs

Platforms
web,linux,macos,api,self_hostedchecked 20 Sep 2026

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