CPU3DAI tools for 3D, video and audio

F5-TTS: audio generator — what it does and what you need to run it

F5-TTS is an open-source speech generator that converts text into audio. The project was created by developer SWivid and is distributed as code along with ready-to-use model weights. Its main purpose is text-to-speech, i.e., synthesizing speech from written text.

What it does

As described by the author, the project is the official code for "F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching". This is the developer's claim, not the result of independent measurements. The model is available in a repository on Hugging Face, and the scientific description is published on arxiv.org.

The fact sheet does not specify supported languages, synthesis quality, generation speed, or text length limits. The authors do not provide this data.

What you need to run it

The code is written in Python and is published under the MIT license. The model weights are distributed under the cc-by-nc-4.0 license, which permits use for non-commercial purposes only.

The largest weight file is 1.3 GB, and all files together take up 3.8 GB. The f5-tts library is required to run it.

As described by the author, the platform is ROCm. The description literally states: "ROCm 7.x — these architectures (gfx1151/gfx1201) are not included in ROCm 6.x". This means that for the specified architectures, ROCm 7.x is required, not 6.x. No other hardware or operating system requirements are listed in the fact sheet.

The latest release is 1.1.22. The repository was created on October 8, 2024, and the last code change was made on July 23, 2026.

Who it suits

The project will be useful for those looking for an open-source speech generator with accessible weights and who are willing to work with Python code. The MIT license on the code allows integrating the solution into your own projects, and having a repository and model on Hugging Face simplifies getting started.

The non-commercial license on the weights limits usage: the model cannot be used in paid products or services without separate permission from the rights holder. The project is also unlikely to suit those who are not ready to deal with ROCm and GPU architectures — the authors do not indicate support for other platforms.

F5-TTS is an open-source codebase for speech synthesis with ready-to-use weights. The project is actively developed, has a public repository and a scientific description. It suits experiments and non-commercial tasks if your environment meets the ROCm requirements.

F5-TTS — audio and speech generator pipeline text-to-speech · open source · Python Input text text to be voiced arbitrary string Tokenization splitting into tokens data preparation F5-TTS model flow matching speech generation Post-processing signal cleanup final assembly Audio speech Key specs Developer: SWivid · Code license: MIT · Weights license: cc-by-nc-4.0 Library: f5-tts · Platform: ROCm · Language: Python Repo: github.com/SWivid/F5-TTS · Model: huggingface.co/SWivid/F5-TTS Latest release: 1.1.22 · Created: 2024-10-08 · Updated: 2026-07-23 Largest weights file: 1.3 GB · All weights files: 3.8 GB
How the F5-TTS pipeline works. The diagram is drawn from the tool’s fact sheet.

Fact sheet

Tasktext-to-speech source
Code licenseMIT source
Weights licensecc-by-nc-4.0 source
PlatformROCm per the author’s description source
Largest weights file1.3 GB source
All weights files3.8 GB source
Libraryf5-tts source
LanguagePython source
Last code change2026-07-23 source
Repository created2024-10-08 source
Changes often — as of 2026-08-19
Latest release1.1.22 source
Release date2026-07-23 source
GitHub stars15136 source
Forks2198 source
Downloads per month743709 source
Model updated2025-03-21 source

Values are collected automatically from official sources and were checked on 2026-08-19. Each one links to its source, and values taken from the developer’s pages also carry a verbatim quote — hover over the note. Pricing and versions are shown as of the check date and change most often; verify on the vendor’s site before buying.

See also