LibreAI / Audio / Kokoro-FastAPI
// audio · remsky/Kokoro-FastAPI

Kokoro-FastAPI

Kokoro-FastAPI is an open-source audio project by remsky (remsky/Kokoro-FastAPI on GitHub). It has 5,511 GitHub stars and 908 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 1 October 2026.

Turn the beloved Kokoro voice model into an OpenAI-compatible speech API with one Docker command.

★ 5.5k stars⑂ 908 forksApache-2.0updated 2026-10
Kokoro-FastAPI interface screenshot
Image: Banner from the Kokoro-FastAPI project README (remsky/Kokoro-FastAPI), hotlinked with thanks.
// project facts

Project facts

GitHub stars
5,511
Forks
908
License
Apache-2.0
Last updated on GitHub
1 October 2026
Category
Audio
Listing
Full install guide
Official site
Try the live demo
// how it works

How it works

  1. Run one Docker command

    Pull a prebuilt image with the model baked in — CPU, NVIDIA GPU, ARM, and AMD variants exist. The server starts on port 8880.

  2. Point your client at it

    Anything written for OpenAI's /v1/audio/speech endpoint works unchanged — just change the base URL to localhost:8880.

  3. Pick voices and languages

    Choose from built-in voices, blend several into a mix, or generate a custom voicepack with the clone tuner.

  4. Generate with extras

    Request SSML for fine control, or ask for per-word timestamps to build read-along experiences and captions.

// features

Why people love it

OpenAI-compatible API

A drop-in /v1/audio/speech endpoint — swap the URL in existing apps and keep your code.

Eight languages

English (US/GB), Spanish, French, Hindi, Italian, Japanese, Brazilian Portuguese, and Mandarin Chinese.

Voice mixing & cloning

Blend voices with weighted combinations or tune custom voicepacks from samples.

SSML + phonemes

Fine-grained pronunciation control, plus endpoints to generate phonemes from text and back.

Timestamped captions

Per-word or per-chunk captions for read-along UIs, subtitles, and karaoke-style apps.

Runs anywhere

Prebuilt images for CPU, NVIDIA, ARM, and AMD GPUs — plus Apple Silicon support when run directly.

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// run it

Run it yourself

  1. Step 1 — CPU (laptops, servers)

    Start the CPU image; the model is baked in, so there is nothing else to download.

    docker run -p 8880:8880 ghcr.io/remsky/kokoro-fastapi-cpu:latest
  2. Step 2 — NVIDIA GPU

    Use the GPU image instead for much faster synthesis.

    docker run --gpus all -p 8880:8880 ghcr.io/remsky/kokoro-fastapi-gpu:latest
  3. Step 3 — Speak

    POST to the OpenAI-style endpoint, e.g. http://localhost:8880/v1/audio/speech, with your text and voice choice.

// use cases

What you can build

  • Narrate audiobooks from EPUBs and PDFs.
  • Voiceovers for videos and explainers.
  • A self-hosted TTS backend for your app or assistant.
  • Accessibility readers and read-along learning tools.

Readers working through the Audio shelf also stop at TeroSubtitler, Free, cross-platform subtitle editor with AI transcription tools. SayIt opens source voice typing for Windows — a Wispr Flow / Superwhisper alternative. The Audio shelf also holds Parrot — Meeting recorder designed for your Mac with a live AI copilot.

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// faq

Questions, answered

Is it free?

Yes — Apache-2.0 licensed and self-hosted. You pay nothing per character, unlike cloud TTS APIs.

How good is the quality?

Kokoro-82M is famous for punching far above its 82-million-parameter weight, with remarkably natural prosody for its size.

Which languages are supported?

Eight: English (US and GB), Spanish, French, Hindi, Italian, Japanese, Brazilian Portuguese, and Mandarin Chinese.

Kokoro-FastAPI or Qwen3-TTS?

Kokoro-FastAPI is lighter, faster, and dead simple via Docker. Qwen3-TTS offers larger, more expressive Alibaba models with streaming — pick by your quality-vs-speed tradeoff.

Can I use it commercially?

Yes — the Apache-2.0 license permits commercial use.

// keep exploring

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// more in audio

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Get Kokoro-FastAPI

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