YanWenKun
ComfyUI-Docker
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🐳Dockerfile for 🎨ComfyUI. | 容器镜像与启动脚本

Last updated Jul 9, 2026
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README

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/customnodes:/root/ComfyUI/customnodes \ -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:

[cols="1,1,1,1,1,1,1,1,1", opti] |=== | GPU Architecture | Blackwell | Hopper | Ada Lovelace | Ampere | Turing | Volta | Pascal | Maxwell

| 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/buildcuda.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!

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