# SWivid/F5-TTS

Official code for "F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching"

Repository: https://github.com/SWivid/F5-TTS
Canonical: https://ross.abutalabs.com/products/f5-tts
Homepage: https://arxiv.org/abs/2410.06885
Language: Python
License: MIT
License Family: permissive
Last push: 2026-07-23T09:20:37+00:00

## Health v2 (maintenance only)
Score: 85/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 94, release rhythm 94, longevity 49
- inputs: {"age_days": 694, "days_push": 41, "days_rel": 41, "gap_med": 17, "n_releases_24m": 22}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 15167, forks 2203 (observed 2026-08-28T04:11:09.313724+00:00)

## What it is
F5-TTS is the official implementation of a fully non-autoregressive text-to-speech system based on flow matching with a Diffusion Transformer, trained on 100K hours of multilingual speech. It provides zero-shot voice cloning, code-switching, and fast inference (RTF 0.15) via a Python package, CLI, and Gradio app.

## Use cases
- clone a voice from a short reference audio clip
- generate natural speech from text in English and Chinese
- run fast text-to-speech inference on a GPU
- fine-tune a TTS model on custom speech data
- build a voiceover or audiobook generation pipeline
- experiment with flow matching based speech synthesis

## When to choose
- you need high-quality zero-shot voice cloning without phoneme alignment or duration models
- you want fast diffusion-based TTS with an MIT license
- you need multilingual or code-switching speech generation
- you want a pip-installable TTS with CLI and web UI

## When to avoid
- you need a lightweight CPU-only TTS for embedded devices
- you require real-time streaming synthesis with very low latency
- you need a mature commercial-grade TTS with extensive language coverage
- you want a simple rule-based or parametric TTS without GPU requirements

## Facets
- artifact type: library
- maturity: active
- function: tts, machine-learning, deep-learning, audio-processing
- domain: speech-processing, machine-learning, artificial-intelligence
- platform: python, windows, cli
- tags: text-to-speech, flow-matching, diffusion-transformer, zero-shot-voice-cloning, non-autoregressive, pytorch, audio, linux, macos, gpu

## Member repositories
- SWivid/F5-TTS (main) score 85

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:09.313724+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:06:35.038116+00:00, confidence not recorded.
  - readme: https://github.com/SWivid/F5-TTS (fetched 2026-08-28T04:11:09.313724+00:00, sha 83f3269af2a0)
  - homepage: https://arxiv.org/abs/2410.06885 (fetched 2026-08-29T08:04:34.862081+00:00, sha aed4042cb84d)
  - site_page: https://info.arxiv.org/about/donate.html (fetched 2026-08-29T08:04:34.865523+00:00, sha cca9c3a11c56)
  - site_page: https://info.arxiv.org/about/ourmembers.html (fetched 2026-08-29T08:04:34.870127+00:00, sha 47cbc55ff1de)
  - site_page: https://info.arxiv.org/about (fetched 2026-08-29T08:04:34.873573+00:00, sha a1f16f915a9a)
  - registry_pypi: https://pypi.org/pypi/f5-tts/json (fetched 2026-08-29T08:04:34.878203+00:00, sha 972bb6522519)
  - site_page: https://info.arxiv.org/labs/index.html (fetched 2026-08-29T08:04:34.868012+00:00, sha b14a8d05a0ec)
- Data as of 2026-08-30T08:39:29.467469+00:00.