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Decision brief
Kokoro-FastAPI is a Dockerized wrapper for the Kokoro-82M text-to-speech model using FastAPI. It supports multi-language capability and provides prebuilt images for various hardware types.
Good fit when
- You require a solution that can auto-download models and run natively on Apple Silicon (MPS) with support via UV.
- Your project needs an open-source text-to-speech model endpoint compatible with OpenAI, supporting multi-language audio synthesis.
Avoid when
- If your hardware is not supported by the provided Docker images, for example, if you do not have a compatible NVIDIA, AMD GPU or CPU setup.
- You are looking for non-Dockerized solutions. Kokoro-FastAPI focuses on containerization and might not fit environments that strictly avoid containers.
- Requirements:
- Min 4 GB RAM; Requires Docker; Hardware-specific Docker images are provided for CUDA, ROCm (experimental), and CPU support.; Users without supported GPUs can still utilize the service via a CPU image.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Active (8d since push)
- As of 3w
- Provenance
- Not a fork · Personal account
- As of 3w
- Security (OSV)
- No criticals
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install Kokoro-FastAPIHow it fits your stack(1)
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Repository hosts Docker images and Python scripts that wrap the Kokoro-82M text-to-speech model using FastAPI.
Capability facts
- MCP server
- No MCP server detected
Source: repo_scan · Jul 29, 2026
- Languages
- python, javascript
Source: github.language+package.json+pyproject.toml · Jul 29, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 29, 2026)
python docker/scripts/download_model.py --output api/src/models/v1_0Source link
Tags
README
FastKoko
Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model
- OpenAI-compatible Speech endpoint, multi-language support
- English (US/GB), Spanish, French, Hindi, Italian, Japanese, Brazilian Portuguese, Mandarin Chinese
- Per-word timestamped caption generation, voice mixing with weighted combinations
- Phoneme endpoints: generate phonemes from text, or generate audio from phonemes
- Prebuilt multiplatform images
- CPU and NVIDIA GPU (CUDA): linux/amd64 + linux/arm64
- AMD GPU (ROCm, experimental): linux/amd64 only
- Apple Silicon (MPS) supported when running directly via UV (no image)
Integration Guides
Get Started
Quickest Start (docker run)
Pre-built multi-arch images with models baked in.
:latest is available, but please pin to a release tag for stable usage.
| Your hardware | Image |
|---|---|
| No GPU (any laptop, VPS, CPU-only server) | kokoro-fastapi-cpu:latest |
| Apple Silicon (M1/M2/M3) | kokoro-fastapi-cpu:latest in Docker, or ./start-gpu_mac.sh natively for MPS |
| NVIDIA GTX 9xx, 10xx, 20xx, 30xx, 40xx (x86_64) | kokoro-fastapi-gpu:latest-cu126 or kokoro-fastapi-gpu:latest |
| NVIDIA RTX 50-series / Blackwell (x86_64) | kokoro-fastapi-gpu:latest-cu128 |
| NVIDIA on arm64 (Jetson, GH200) | kokoro-fastapi-gpu:latest (ships cu129, no cu126 arm64 wheels upstream) |
| AMD GPU | kokoro-fastapi-rocm:latest (experimental, x86_64 only) |
docker run -p 8880:8880 ghcr.io/remsky/kokoro-fastapi-cpu:latest # CPU
docker run --gpus all -p 8880:8880 ghcr.io/remsky/kokoro-fastapi-gpu:latest # NVIDIA (x86_64 or arm64)
docker run --gpus all -p 8880:8880 ghcr.io/remsky/kokoro-fastapi-gpu:latest-cu128 # NVIDIA Blackwell / RTX 50-series
docker run --device=/dev/kfd --device=/dev/dri -p 8880:8880 ghcr.io/remsky/kokoro-fastapi-rocm:latest # AMD
Configuration via environment variables, see core/config.py. The :latest and :latest-cu126 tags resolve to the same multi-arch image.
Quick Start (docker compose)
- Install prerequisites, and start the service using Docker Compose (Full setup including UI):
- Install Docker
- Clone the repository:
git clone https://github.com/remsky/Kokoro-FastAPI.git cd Kokoro-FastAPI cd docker/gpu # For NVIDIA GPU support # or cd docker/cpu # For CPU support # or cd docker/rocm # For AMD GPU (ROCm, experimental, amd64 only) docker compose up --build # *Note for Apple Silicon (M1/M2/M3) users: # The Docker GPU image is CUDA-only and won't run on Apple Silicon. With Docker, use `docker/cpu`. # For native MPS (Apple GPU) acceleration, run directly via UV with `./start-gpu_mac.sh`. cd ../.. # back to repo root for the paths below # Models will auto-download, but if needed you can manually download: python docker/scripts/download_model.py --output api/src/models/v1_0 # Or run directly via UV: ./start-gpu.sh # For GPU support ./start-cpu.sh # For CPU support
Direct Run (via uv)
- Install prerequisites ():
-
Install astral-uv
-
Install espeak-ng in your system if you want it available as a fallback for unknown words/sounds. The upstream libraries may attempt to handle this, but results have varied.
-
Clone the repository:
git clone https://github.com/remsky/Kokoro-FastAPI.git cd Kokoro-FastAPIRun the [model download scri
-
For agents
This page has a .md twin and JSON over the API.