F5-TTS review

Q: How do I install F5-TTS?

Run pip install f5-tts. The install section above has the other options from the project's README.

F5-TTS is an open-source Python text-to-speech system using flow matching with a Diffusion Transformer, supporting zero-shot voice cloning from reference audio.

Updated Nov 1, 2026. Review written Oct 22, 2026 from the project's own sources; usage data refreshed every Monday.

TL;DR

F5-TTS is the official code for a non-autoregressive text-to-speech model based on flow matching and a Diffusion Transformer. F5-TTS is for developers who want to generate speech from a reference audio clip, locally or with Docker. F5-TTS adds Sway Sampling at inference time and includes a Gradio app, a CLI, and finetuning tools.

15.5kGitHub stars
+53new stars, week of Oct 25
25.1kdownloads a week, +56% vs 4-week avg
#11in Voice and realtime this week

F5-TTS at a glance

Category: Voice and realtime
Maintained by: Yushen CHEN (individual, @SWivid on GitHub)
License: MIT
Language: Python, Shell, Dockerfile
Repository: github.com/SWivid/F5-TTS
Website: arxiv.org/abs/2410.06885
PyPI package: f5-tts 1.1.22
Latest release: 1.1.22 on GitHub, Jul 23, 2026
First published: Oct 8, 2024

What F5-TTS does

F5-TTS generates speech from text, using a reference audio clip and its transcript to set the voice.
F5-TTS offers a Gradio web app with chunk inference, multi-style and multi-speaker generation, and voice chat powered by Qwen2.5-3B-Instruct.
F5-TTS provides a CLI that accepts flags or a .toml config file, including multi-voice story configs.
F5-TTS can transcribe the reference audio with an ASR model when ref_text is left empty, at the cost of extra GPU memory.
F5-TTS supports training and finetuning through Hugging Face Accelerate or a finetuning Gradio app.
F5-TTS includes a deployment option using Triton and TensorRT-LLM.
F5-TTS also ships an E2 TTS implementation, described as the closest reproduction of the E2 TTS paper.

How it works

F5-TTS runs as a Python package on top of PyTorch, installed for your GPU type: NVIDIA CUDA, AMD ROCm, Intel XPU, or Apple Silicon. You run inference through the f5-tts_infer-gradio web app or the f5-tts_infer-cli command. Pre-trained base models are published on Hugging Face, Model Scope, and Wisemodel. Docker images on GitHub Container Registry serve the web interface on port 7860.

How to install and start using F5-TTS

With pip (inference only)

pip install f5-tts

With Docker (web interface)

docker container run --rm -it --gpus=all --mount 'type=volume,source=f5-tts,target=/root/.cache/huggingface/hub/' -p 7860:7860 ghcr.io/swivid/f5-tts:main f5-tts_infer-gradio --host 0.0.0.0

Requirements

Python 3.10 or later
FFmpeg
PyTorch and torchaudio built for your device (CUDA, ROCm on Linux, XPU, or Apple Silicon)
RDNA 3.5 and RDNA 4 AMD GPUs require ROCm 7.x

First steps

Create a Python 3.10 or later environment, install FFmpeg, and install PyTorch matched to your GPU.
Install the package with pip install f5-tts if you only need inference.
Launch the web interface with f5-tts_infer-gradio, or run f5-tts_infer-cli with the default settings.
Pass --ref_audio, --ref_text, and --gen_text to the CLI with --model F5TTS_v1_Base to generate speech in a chosen voice.

Who F5-TTS is for

Developers running zero-shot voice cloning text-to-speech on their own GPU
Researchers training or finetuning flow-matching TTS models
Teams serving TTS with Triton and TensorRT-LLM
Non-commercial projects that can accept the CC-BY-NC model license

Limitations to know

F5-TTS pre-trained models use the CC-BY-NC license because of the Emilia training data, though the code is MIT.
F5-TTS AMD GPU support through ROCm is Linux only.
F5-TTS uses extra GPU memory when ref_text is empty, because an ASR model transcribes the reference audio.
F5-TTS Intel XPU install requires Intel Deep Learning Essentials or oneAPI Base Toolkit, unless you use IPEX.

Is F5-TTS growing? Usage data

In the week of Oct 25–31, 2026, F5-TTS ranked #188 on the Devtoolwatch Board and #11 in Voice and realtime, with a momentum score of 46 out of 100. Its main package had 25.1k downloads that week, +56% against its own 4-week average.

New GitHub stars per week for the last 12 weeks, from GitHub's stargazer history (today's stargazers by the week they starred).

Show the weekly numbers

New GitHub stars per week for F5-TTS
Week of	New stars
Aug 9, 2026	44
Aug 16, 2026	33
Aug 23, 2026	25
Aug 30, 2026	33
Sep 6, 2026	24
Sep 13, 2026	42
Sep 20, 2026	37
Sep 27, 2026	51
Oct 4, 2026	40
Oct 11, 2026	55
Oct 18, 2026	41
Oct 25, 2026	53

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The Board ranks tools by four signals each week: new stars, new stars for the repo's size, added downloads and download growth beyond the market. How the ranking works.

F5-TTS alternatives

Other voice and realtime AI tools on the Board in the week of Oct 25–31, 2026, by momentum:

Voice and realtime ranked by momentum, the week of Oct 25–31, 2026
Rank	Tool	Stars	Downloads/wk
#1	faster-whisperfaster-whisper is a Python reimplementation of OpenAI's Whisper speech-to-text model built on the CTranslate2 inference engine for…	26.4k	4.4M
#2	KokoroKokoro is a Python inference library for Kokoro-82M, an open-weight text-to-speech model with 82 million parameters.	9.8k	150.7k
#3	ChatterboxChatterbox is a family of open-source text-to-speech and voice cloning models by Resemble AI, with English and multilingual variants.	27.5k	73.2k
#4	VoiceMemInfrastructure for the next generation of voice agents, designed to provide universal memory. It is divided into a left brain and a…	2.8k	–
#5	PipecatPipecat is an open-source Python framework for building real-time voice and multimodal conversational agents, maintained by Daily and…	17k	348.5k
#6	WhisperXWhisperX is a Python speech recognition tool built on Whisper that adds word-level timestamps and speaker diarization.	25k	158.6k

All voice and realtime AI tools, ranked

Recent F5-TTS releases

1.1.22, Jul 23, 2026
1.1.21, Jul 5, 2026
1.1.20, Apr 20, 2026
1.1.19, Apr 16, 2026
1.1.18, Mar 24, 2026

F5-TTS FAQ

Is F5-TTS free and open source?

Yes. F5-TTS's source code is on GitHub (SWivid/F5-TTS) under the MIT license, so you can use it for free.

How do I install F5-TTS?

Run pip install f5-tts. The install section above has the other options from the project's README.

Is F5-TTS still maintained?

Yes. The SWivid/F5-TTS repository was last updated on Oct 14, 2026, and the latest release, 1.1.22 on GitHub, came out on Jul 23, 2026.

How popular is F5-TTS?

F5-TTS has 15.5k GitHub stars as of Nov 1, 2026. It gained 53 new stars in the week of Oct 25–31, 2026, against a 12-week average of 40 a week. Its main package had 25.1k downloads that week, +56% against its own 4-week average. That made it #11 among voice and realtime AI tools on the Devtoolwatch Board.

F5-TTS vs Chatterbox: how do they compare?

F5-TTS and Chatterbox are both tracked by Devtoolwatch as voice and realtime AI tools. F5-TTS has 15.5k GitHub stars and Chatterbox has 27.5k. In the week of Oct 25–31, 2026, F5-TTS's main package had 25.1k downloads and Chatterbox's had 73.2k. Chatterbox is a family of open-source text-to-speech and voice cloning models by Resemble AI, with English and multilingual variants. Chatterbox review.

What are the best alternatives to F5-TTS?

Other voice and realtime AI tools on the Devtoolwatch Board in the week of Oct 25–31, 2026, by momentum: faster-whisper (#1), Kokoro (#2), Chatterbox (#3), VoiceMem (#4), Pipecat (#5). The alternatives table above has their numbers.

How do I use F5-TTS locally?

F5-TTS runs locally after you install PyTorch for your GPU and run pip install f5-tts. Then start the web interface with f5-tts_infer-gradio, or use f5-tts_infer-cli with a reference audio file, its transcript, and the text to generate.

Can I use F5-TTS models commercially?

F5-TTS code is MIT licensed. The pre-trained models are licensed CC-BY-NC because they were trained on the Emilia in-the-wild dataset, which restricts commercial use of those checkpoints.

Which GPUs does F5-TTS support?

F5-TTS supports NVIDIA GPUs with CUDA, AMD GPUs with ROCm on Linux, Intel GPUs through XPU or IPEX, and Apple Silicon with the stable PyTorch build.

Do I need to transcribe the reference audio for F5-TTS?

F5-TTS does not require a transcript. If you leave --ref_text empty, an ASR model transcribes the reference audio, which uses extra GPU memory.

Can I finetune F5-TTS on my own data?

F5-TTS supports training and finetuning with Hugging Face Accelerate or through a Gradio app launched with f5-tts_finetune-gradio. Use the local editable install for training.

Sources

F5-TTS README badge

Maintainers can show the tool's weekly Board rank in their README:

[![Devtoolwatch](https://index.devtoolwatch.com/badge/f5-tts.svg)](https://index.devtoolwatch.com/tools/f5-tts/)

How this page is made: Devtoolwatch writes each review from the project's README, releases, package metadata and website, with an AI model, then checks every claim against the source it cites and drops what the sources don't support. The numbers come from Devtoolwatch's daily GitHub snapshots, GitHub's stargazer history, and the npm and PyPI download APIs. Spotted an error? Email [email protected].