Docker images for ComfyUI

May 18, 2026 · View on GitHub

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