About ComfyUI-Docker

ComfyUI-Docker provides official Docker images and startup scripts for ComfyUI, a node-based graphical interface for generative AI workflows. This project simplifies the deployment of ComfyUI on Linux systems using containerization. It offers a variety of optimized image tags tailored to specific hardware architectures and usage needs. For NVIDIA GPU users, images support CUDA 13.0 and CUDA 12.6, with recommendations for the cu130-slim-v2 tag for beginners and cu130-megapak-pt211 for an all-in-one experience including development kits and numerous custom nodes. The package also includes support for AMD GPUs via ROCm 6 and 7, Intel GPUs using XPU, and a nightly build for testing the latest PyTorch features. The software includes detailed volume mounting examples to manage model storage, cache, user inputs, and outputs effectively. By leveraging PyTorch builds optimized for modern GPU architectures like Blackwell, Hopper, and Ada Lovelace, these images ensure high performance and stability. The repository serve

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README.md

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Docker images for ComfyUI

English | 🀄 link:README.zh.adoc[中文说明]

This repo is for https://hub.docker.com/r/yanwk/comfyui-boot[Docker images] that runs https://github.com/Comfy-Org/ComfyUI[ComfyUI] - an AIGC GUI powering node-based workflow.

Quick Start - NVIDIA GPU

mkdir -p \
  storage-cache/dot-cache \
  storage-cache/dot-config \
  storage-nodes/dot-local \
  storage-nodes/custom_nodes \
  storage-models/models \
  storage-models/hf-hub \
  storage-models/torch-hub \
  storage-user/input \
  storage-user/output \
  storage-user/user-profile \
  storage-user/user-scripts

# Add sudo if needed
docker run -it --rm \
  --name comfyui-cu130 \
  --pull=always \
  --runtime=nvidia \
  --gpus all \
  -p 8188:8188 \
  -v "$(pwd)"/storage-cache/dot-cache:/root/.cache \
  -v "$(pwd)"/storage-cache/dot-config:/root/.config \
  -v "$(pwd)"/storage-nodes/dot-local:/root/.local \
  -v "$(pwd)"/storage-nodes/custom_nodes:/root/ComfyUI/custom_nodes \
  -v "$(pwd)"/storage-models/models:/root/ComfyUI/models \
  -v "$(pwd)"/storage-models/hf-hub:/root/.cache/huggingface/hub \
  -v "$(pwd)"/storage-models/torch-hub:/root/.cache/torch/hub \
  -v "$(pwd)"/storage-user/input:/root/ComfyUI/input \
  -v "$(pwd)"/storage-user/output:/root/ComfyUI/output \
  -v "$(pwd)"/storage-user/user-profile:/root/ComfyUI/user \
  -v "$(pwd)"/storage-user/user-scripts:/root/user-scripts \
  -e CLI_ARGS="" \
  yanwk/comfyui-boot:cu130-slim-v2

CUDA Compatibility

The supported CUDA versions for each GPU architecture are shown in the table below:

| Example GPU | RTX 5090 | H100 | RTX 4090 | RTX 3090 | RTX 2080 + GTX 1660 | TITAN V | GTX 1080 | GTX 980

| cu132 | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ❌ | ❌ | ❌

| cu130 ⭐ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ❌ | ❌ | ❌

| cu126 | ❌ | ❌ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️

|===

CUDA 13.0 images are currently recommended.

** ComfyUI's https://github.com/Comfy-Org/comfy-kitchen[performance library] is currently developed based on CUDA 13.0, which is also considered one of the stable versions of https://github.com/pytorch/pytorch/issues/172663[PyTorch].

If you are unsure about your NVIDIA GPU architecture, see https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/[this article].

NOTE: __These CUDA compatibility limitations are due to the https://github.com/pytorch/pytorch/releases/tag/v2.8.0[PyTorch] toolchain, not the NVIDIA CUDA Toolkit. For more information, refer to the https://github.com/pytorch/pytorch/blob/v2.12.0/.ci/manywheel/build_cuda.sh[PyTorch build script].__

CUDA Image Tags

Slim

The slim images start with only ComfyUI and ComfyUI-Manager, yet include many dependencies to make future Custom Node installation easier. Recommended for beginners.

link:cu130-slim-v2/README.adoc[cu130-slim-v2] ⭐ ** CUDA 13.0, Python 3.13 (with GIL), No xFormers
link:cu126-slim/README.adoc[cu126-slim] ** CUDA 12.6, Python 3.12

MEGAPAK

The megapak images are all-in-one bundles, including development kits and dozens of Custom Nodes for ComfyUI.

link:cu130-megapak-pt211/README.adoc[cu130-megapak-pt211] ⭐ ** CUDA 13.0, Python 3.13 (with GIL), GCC 14, PyTorch 2.11.0
link:cu126-megapak/README.adoc[cu126-megapak] ** CUDA 12.6, Python 3.12, GCC 13, PyTorch 2.9.1

Testing

link:nightly/README.adoc[nightly] ** Using development version of PyTorch. For testing latest features.

ROCm Image Tags

link:rocm/README.adoc[rocm]

For AMD GPUs with ROCm 7. Based on PyTorch's builds (faster release).

link:rocm7/README.adoc[rocm7]

For AMD GPUs with ROCm 7. Based on AMD's builds (comprehensive functionality).

link:rocm6/README.adoc[rocm6]

** For AMD GPUs with ROCm 6 (stable version).

XPU Image Tags

link:xpu/[xpu]

** For Intel GPUs with XPU.

More Image Tags

link:cpu/[cpu]

** A smaller image for CPU only.

link:archived/[archived]

** Archived Dockerfiles of retired image tags.

License

link:LICENSE[Mulan Public License，Version 2]

This open source license is written and valid both in Chinese and English, how good is that!

ComfyUI-Docker