# ComfyUI-Docker
**An automated Repo for ComfyUI Docker image builds, optimized for NVIDIA GPUs.**
[![][github-stargazers-shield]][github-stargazers-link]
[![][github-release-shield]][github-release-link]
[![][github-license-shield]][github-license-link]
[github-stargazers-shield]: https://img.shields.io/github/stars/clsferguson/ComfyUI-Docker.svg
[github-stargazers-link]: https://github.com/clsferguson/ComfyUI-Docker/stargazers
[github-release-shield]: https://img.shields.io/github/v/release/clsferguson/ComfyUI-Docker?style=flat&sort=semver
[github-release-link]: https://github.com/clsferguson/ComfyUI-Docker/releases
[github-license-shield]: https://img.shields.io/github/license/clsferguson/ComfyUI-Docker.svg
[github-license-link]: https://github.com/clsferguson/ComfyUI-Docker/blob/master/LICENSE
[About](#about) • [Features](#features) • [Getting Started](#getting-started) • [Usage](#usage) • [License](#license)
---
## About
This image packages upstream [ComfyUI](https://github.com/comfyanonymous/ComfyUI) with CUDA-enabled PyTorch and an entrypoint that handles volume permissions and custom node setup.
The base image is python:3.12-slim (Debian trixie) with CUDA 12.8 developer libraries installed via apt and PyTorch installed from the cu128 wheel index.
It syncs with the upstream ComfyUI repository, builds a Docker image on new releases, and pushes it to GitHub Container Registry (GHCR).
I created this repo for myself as a simple way to stay up to date with the latest ComfyUI versions while having an easy-to-use Docker image.
---
## Features
- Daily checks for upstream releases, auto-merges changes, and builds/pushes Docker images.
- CUDA-enabled PyTorch + Triton on Debian trixie with CUDA 12.8 dev libs so custom CUDA builds work at runtime.
- Non-root runtime with PUID/PGID mapping handled by entrypoint for volume permissions.
- ComfyUI-Manager auto-sync on startup; entrypoint scans custom_nodes and installs requirements when COMFY_AUTO_INSTALL=1.
- SageAttention build-on-start for compatible NVIDIA GPUs (Turing/SM 7.5+); enabling is opt-in via FORCE_SAGE_ATTENTION=1.
---
## Getting Started
- Install NVIDIA Container Toolkit on the host, then use docker run --gpus all or Compose GPU reservations to pass GPUs through.
- Expose the ComfyUI server on port 8188 (default) and map volumes for models, inputs, outputs, and custom_nodes.
### Pulling the Image
The latest image is available on GHCR:
```bash
docker pull ghcr.io/clsferguson/comfyui-docker:latest
```
For a specific version (synced with upstream tags, starting at v0.3.59):
```bash
docker pull ghcr.io/clsferguson/comfyui-docker:vX.Y.Z
```
### Docker Compose
For easier management, use this `docker-compose.yml`:
```yaml
services:
comfyui:
image: ghcr.io/clsferguson/comfyui-docker:latest
container_name: ComfyUI
runtime: nvidia
restart: unless-stopped
ports:
- 8188:8188
environment:
- TZ=America/Edmonton
- PUID=1000
- PGID=1000
gpus: all
volumes:
- comfyui_data:/app/ComfyUI/user/default
- comfyui_nodes:/app/ComfyUI/custom_nodes
- /mnt/comfyui/models:/app/ComfyUI/models
- /mnt/comfyui/input:/app/ComfyUI/input
- /mnt/comfyui/output:/app/ComfyUI/output
```
Run with `docker compose up -d`.
---
## Usage
- Open http://localhost:8188 after the container is up; change the external port via -p HOST:8188.
- To target specific GPUs, use Docker's GPU device selections or Compose device_ids in reservations.
### SageAttention
SageAttention is compiled at container startup when a compatible GPU (Turing SM 7.5+) is detected and cached to a volume-mapped directory for subsequent starts. It delivers 2-5x faster attention vs FlashAttention for video and high-res image workflows.
- To enable: set `FORCE_SAGE_ATTENTION=1`. If the build or import fails, ComfyUI starts normally without it.
- The first startup with SageAttention will be slower due to compilation; subsequent starts use the cached build.
- Turing GPUs (RTX 20xx) use the v1.0 branch with Triton 3.2.0; Ampere and newer use the latest release.
### Environment Variables
- PUID/PGID: map container user to host UID/GID for volume write access.
- COMFY_AUTO_INSTALL=1: auto-install Python requirements from custom_nodes on startup (default: 1).
- COMFY_FORCE_INSTALL=1: force reinstall of custom_nodes requirements even after first run.
- FORCE_SAGE_ATTENTION=0|1: compile and enable SageAttention on startup (requires compatible NVIDIA GPU).
- SAGE_MAX_JOBS=N: override the number of parallel compile jobs for SageAttention (default: auto from RAM).
- CM_*: seed ComfyUI-Manager config.ini keys on first start (e.g. CM_SKIP_UPDATE_CHECK=1).
---
## License
Distributed under the MIT License (same as upstream ComfyUI). See [LICENSE](LICENSE) for more information.
---
## Contact
- **Creator**: clsferguson - [GitHub](https://github.com/clsferguson)
- **Project Link**: https://github.com/clsferguson/ComfyUI-Docker
Built with ❤️ for easy AI workflows.