ComfyUI (NVIDIA) Docker

runs in containers for enhanced host OS separation
- work with docker (and compose) or podman + WSL2 on Windows
can run multiple setups with an independent run folder (for virtual environment management and source code) shared basedir folder (for user files, input, output, custom nodes, models, etc.)
drops privileges to a regular user/preserves user permissions with custom UID/GID mapping (the running user's id -u and id -g as specified on the command line)
Integrated ComfyUI-Manager for hassle-free updates
- permits modification of ComfyUI-Manager's security level (SECURITY_LEVEL)
expose to Localhost-only access by default (-p 127.0.0.1:8188:8188)
built on official NVIDIA CUDA containers for optimal GPU performance
multiple Ubuntu + CUDA version combinations available --for older hardware: down to CUDA 12.3.2 / for 50xx GPUs: CUDA 12.8-- see the tags list
separate run and basedir folders
- run folder is used to store the ComfyUI setup (virtual environment, source code)
- basedir folder is used to store user files, input, output, custom nodes, models, etc.
command-line override
- using the COMFY_CMDLINE_EXTRA environment variable to pass additional command-line arguments set during the init script
- ability to run user_script.bash from within the container for complex customizations, installations (pip, apt, ...) and command-line overrides
pre-built container images available on DockerHub
- including Unraid compatible images
open-source: build it yourself using the corresponding Dockerfile present in the directory of the same name and review the init.bash (i.e. the setup logic)

Quick Start

Windows users, see the "Windows: WSL2 and podman" section

Make sure you have the NVIDIA Container Toolkit installed. More details: https://blg.gkr.one/20240404-u24_nvidia_docker_podman/

To run the container on an NVIDIA GPU, mount the specified directory, expose only to localhost on port 8188 (remove 127.0.0.1 to expose to your subnet, and change the port by altering the -p local:container port mapping), pass the calling user's UID and GID to the container, and select the SECURITY_LEVEL:

# 'run' will contain your virtual environment(s), ComfyUI source code, and Hugging Face Hub data
# 'basedir' will contain your custom nodes, input, output, user and models directories
mkdir run basedir


# Using docker
docker run --rm -it --runtime nvidia --gpus all -v `pwd`/run:/comfy/mnt -v `pwd`/basedir:/basedir -e WANTED_UID=`id -u` -e WANTED_GID=`id -g` -e BASE_DIRECTORY=/basedir -e SECURITY_LEVEL=normal -p 127.0.0.1:8188:8188 --name comfyui-nvidia mmartial/comfyui-nvidia-docker:latest

# Using podman
podman run --rm -it --userns=keep-id --device nvidia.com/gpu=all -v `pwd`/run:/comfy/mnt -v `pwd`/basedir:/basedir -e WANTED_UID=`id -u` -e WANTED_GID=`id -g` -e BASE_DIRECTORY=/basedir -e SECURITY_LEVEL=normal -p 127.0.0.1:8188:8188 --name comfyui-nvidia docker.io/mmartial/comfyui-nvidia-docker:latest

ComfyUI (NVIDIA) Docker

ComfyUI is a Stable Diffusion WebUI. With the addition in August 2024 of a Flux example, I created this container builder to test it. This container was built to benefit from the process isolation that containers bring and to drop the container's main process privileges to that of a regular user (the container's comfy user, which is sudo capable).

The container size (usually over 4GB) contains the required components on an Ubuntu image with Nvidia CUDA and CuDNN (the base container is available from Nvidia's DockerHub); we add the requirements components to support an installation of ComfyUI.

Multiple images are available. Each image's name contains a tag reflecting its core components. For example, ubuntu24_cuda12.5.1 is based on Ubuntu 24.04 with CUDA 12.5.1. Depending on the version of the Nvidia drivers installed, the Docker container runtime will only support a certain version of CUDA. For example, Driver 550 supports up to CUDA 12.4 and will not be able to run the CUDA 12.4.1 or 12.5.1 versions. The recently released 570 driver supports up to CUDA 12.8 and RTX 50xx GPUs. Use the nvidia-smi command on your system to obtain the CUDA Version: entry in the produced table's header. For more details on driver capabilities and how to update those, please see Setting up NVIDIA docker & podman (Ubuntu 24.04).

The latest tag will always point to the most up-to-date build (i.e., the most recent OS+CUDA). If this version is incompatible with your container runtime, please see the list of alternative builds.

tag	aka	note
ubuntu22_cuda12.3.2-latest
ubuntu22_cuda12.4.1-latest
ubuntu24_cuda12.5.1-latest	latest
ubuntu24_cuda12.8-latest		RTX 50xx beta

During its first run, the container will download ComfyUI from git (into the run/ComfyUI folder), create a Python virtual environment (in run/venv) for all the Python packages needed by the tool, and install ComfyUI Manager into ComfyUI's custom_nodes directory. This adds about 5GB of content to the installation. The download time depends on your internet connection.

Given that venv (Python virtual environments) might not be compatible from OS+CUDA-version to version and will create a new venv when the current one is not for the expected version. An installation might end up with multiple venv-based directories in the run folder, as the tool will rename existing unusable ones as "venv-OS+CUDA" (for example, venv-ubuntu22_cuda12.3.2). To support downgrading if needed, the script will not delete the previous version, and this is currently left to the end-user to remove if not needed Using alternate venv means that some installed custom nodes might have an import failed error. We are attempting to make use of cm-cli before starting ComfyUI. If that fails, start the Manager -> Custom Nodes Manager, Filter by Import Failed, and use the Try fix button as this will download the required packages and install those in the used venv. A Restart and UI reload will be required to fix issues with the nodes.

You will know the ComfyUI WebUI is running when you check the docker logs and see To see the GUI go to: http://0.0.0.0:8188

About 10GB of space between the container and the virtual environment installation is needed. This does not consider the models, additional package installations, or custom nodes that the end user might perform.

ComfyUI's security_levels are not accessible until the configuration file is created during the first run.

It is recommended that a container monitoring tool be available to watch the logs and see when installations are completed or other relevant messages. Some installations and updates (updating packages, downloading content, etc.) will take a long time, and the lack of updates on the WebUI is not a sign of failure. Dozzle is a good solution for following the logs from a WebUI.

1. Preamble
2. Running the container
3. Docker image
4. Screenshots
- 4.1. First run: Bottle image
- 4.2. FLUX.1[dev] example
5. FAQ
6. Troubleshooting
7. Changelog

1. Preamble

This build is made to NOT run as the root user, but run within the container as a comfy user using the UID/GID requested at docker run time (if none are provided, the container will use 1024/1024). This is done to allow end users to have local directory structures for all the side data (input, output, temp, user), Hugging Face HF_HOME if used, and the entire models, which are separate from the container and able to be altered by the user. To request a different UID/GID at run time, use the WANTED_UID and WANTED_GID environment variables when calling the container.

Note:

for details on how to set up a Docker to support an NVIDIA GPU on an Ubuntu 24.04 system, please see Setting up NVIDIA docker & podman (Ubuntu 24.04)
If you are new to ComfyUI, see OpenArt's ComfyUI Academy
Some ComfyUI examples:
- ComfyUI_examples
- ComfyUI FLUX examples
Some additional reads:
- FLUX.1[dev] with ComfyUI and Stability Matrix
- FLUX.1 LoRA training

2. Running the container

In the directory where we intend to run the container, create the run and basedir folders as the user with whom we want to share the UID/GID. This needs to be done before the container is run (it is started as root, so the folders, if they do not exist, will be created as root) (or give it another name; adapt the -v mapping in the docker run below).

That run folder will be populated with a few sub-directories created with the UID/GID passed on the command line (see the command line below). Among the folders that will be created within run are HF, ComfyUI, venv

HF is the expected location of the HF_HOME (HuggingFace installation directory)
ComfyUI is the git clone version of the tool, with all its sub-directories, among which:
- custom_nodes for additional support nodes, for example, ComfyUI-Manager,
- models and all its sub-directories is where checkpoints, clip, loras, unet, etc have to be placed.
- input and output are where input images will be placed, and generated images will end up.
- user is where the user's customizations and saved workflows (and ComfyUI Manager's configuration) are stored.
venv is the virtual environment where all the required Python packages for ComfyUI and other additions will be placed. A default ComfyUI package installation requires about 5GB of additional installation in addition to the container itself; those packages will be in this venv folder.

Currently, it is not recommended to volume map folders within the ComfyUI folder. Doing so is likely to prevent proper installation (during the first run) or update, as any volume mapping (docker ... -v or - local_path:container_path for compose) creates those directories within a directory structure that is not supposed to exist during the initial execution.

The use of the basedir is recommended. This folder will be populated at run time with the content from ComfyUI's input, output, user and models folders. This allow for the separation of the run time components (within the run folder) from the user files. In particular, if you were to delete the run folder, you would still have model files in the basedir folder. This is possible because of a new CLI option --basedir that was added to the code at the end of January 2025. This option will not be available unless ComfyUI is updated for existing installations.

When starting, the container image executes the init.bash script that performs a few operations:

Ensure we can use the WANTED_UID and WANTED_GID as the comfy user (the user set to run the container),
Obtain the latest version of ComfyUI from GitHub if not already present in the mounted run folder.
Create the virtual environment (venv) if one does not already exist
- if one exists, confirm it is the one for this OS+CUDA pair
  - if not, rename it and look for a renamed one that would match
  - if none is found, create a new one
Activate this virtual environment
Install all the ComfyUI-required Python packages. If those are already present, additional content should not need to be downloaded.
Installing ComfyUI-Manager if it is not present.
- During additional runs, we will allow the user to change the security_level from normal to another value set using the SECURITY_LEVEL environment passed to the container (see the "Security Levels" section of this document for details) to allow for the tool grant more of less functionalities
Populate the BASE_DIRECTORY with the input, output, user and models directories from ComfyUI's run folder if none are present in the basedir folder
- extend the COMFY_CMDLINE_EXTRA environment variable with the --basedir option. This variable is exported so that it should be used with any user_script.bash if the BASE_DIRECTORY is used.
Check for a user custom script in the "run" directory. It must be named user_script.bash. If one exists, run it.
- Make sure to use the COMFY_CMDLINE_EXTRA environment variable to pass the --basedir option to the tool if running the tool from within this script
Run the ComfyUI WebUI. For the exact command run, please see the last line of init.bash

2.1. docker run

To run the container on an NVIDIA GPU, mount the specified directory, expose only to localhost on port 8188 (remove 127.0.0.1 to expose to your subnet, and change the port by altering the -p local:container port mapping), pass the calling user's UID and GID to the container, provide a BASE_DIRECTORY and select the SECURITY_LEVEL:

mkdir run basedir
docker run --rm -it --runtime nvidia --gpus all -v `pwd`/run:/comfy/mnt -v `pwd`/basedir:/basedir -e WANTED_UID=`id -u` -e WANTED_GID=`id -g` -e BASE_DIRECTORY=/basedir -e SECURITY_LEVEL=normal -p 127.0.0.1:8188:8188 --name comfyui-nvidia mmartial/comfyui-nvidia-docker:latest

2.2. podman

It is also possible to run the tool using podman. Before doing so, ensure the Container Device Interface (CDI) is properly set for your driver. Please see https://blg.gkr.one/20240404-u24_nvidia_docker_podman/ for instructions. To run the container on an NVIDIA GPU, mount the specified directory, expose only to localhost on port 8188 (remove 127.0.0.1 to expose to your subnet, and change the port by altering the -p local:container port mapping), pass the calling user's UID and GID to the container, provide a BASE_DIRECTORY and select the SECURITY_LEVEL:

mkdir run basedir
podman run --rm -it --userns=keep-id --device nvidia.com/gpu=all -v `pwd`/run:/comfy/mnt -v `pwd`/basedir:/basedir -e WANTED_UID=`id -u` -e WANTED_GID=`id -g` -e BASE_DIRECTORY=/basedir -e SECURITY_LEVEL=normal -p 127.0.0.1:8188:8188 --name comfyui-nvidia docker.io/mmartial/comfyui-nvidia-docker:latest

2.3. Docker compose

In the directory where you want to run the compose stack, create the compose.yaml file with the following content:

services:
  comfyui-nvidia:
    image: mmartial/comfyui-nvidia-docker:latest
    container_name: comfyui-nvidia
    ports:
      - 8188:8188
    volumes:
      - ./run:/comfy/mnt
      - ./basedir:/basedir
    restart: unless-stopped
    environment:
      # set WANTED_UID and WANTED_GID to your user and group as obtained with `id -u` and `id -g`
      - WANTED_UID=1000
      - WANTED_GID=1000
      - BASE_DIRECTORY=/basedir
      - SECURITY_LEVEL=normal
      - NVIDIA_VISIBLE_DEVICES=all
      - NVIDIA_DRIVER_CAPABILITIES=all
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities:
                - gpu
                - compute
                - utility

This will use port 8188 (host:container). Use a run directory local to the directory where this compose.yml is, and specify the WANTED_UID and WANTED_GID to 1000 (adapt to reflect the user and group you want to run as, which can be obtained using the id command in a terminal). Make sure to create the run and basedir directories as the user with the desired uid and gid before running the docker-compose for the first time.

Start it with docker compose up (with -detached to run the container in the background)

Please see docker compose up reference manual for additional details.

For users interested in adding it to a Dockge (a self-hosted Docker Compose stacks management tool ) stack, please see my Dockge blog post where we discuss directory and bind mounts (models take a lot of space).

2.4. First time use

The first time we run the container, we will go to our host's IP on port 8188 (likely http://127.0.0.1:8188) and see the latest run or the bottle-generating example.

Before attempting to run this example, restarting the container is recommended. The default security model of normal is used unless specified, but the needed configuration file is created at the first run of the container. As such, the ComfyUI Manager's default security_level can not be modified until the first container restart (after the WebUI ran the first time).

This example requires the v1-5-pruned-emaonly.ckpt file which can be downloaded directly from the Manager's "Model Manager".

It is also possible to manually install Stable Diffusion checkpoints, upscale, or Loras (and more) by placing them directly in their respective directories under the models folder. For example, to manually install the required "bottle example" checkpoint, as the user with the wanted uid/gid:

cd <YOUR_BASE_DIRECTORY>/models/checkpoints
wget https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt

After the download is complete, click "Refresh" on the WebUI and "Queue Prompt"

Depending on the workflow, some "custom nodes" might be needed. Those should usually be available in the "Manager"'s "Install Missing Custom Nodes". Other needed files could be found on HuggingFace or CivitAI.

"Custom nodes" should be installed using the "Manager". The ability to install those manually depends on the security_levels selected.

3. Docker image

3.1. Building the image

3.1.1. Using the Makefile

Running make will show us the different build targets. That list will differ depending on the available base files in the components directory

For example, you might see:

Run:

% make
Available comfyui-nvidia-docker docker images to be built (make targets):
      ubuntu22_cuda12.3.2
      ubuntu22_cuda12.4.1
      ubuntu24_cuda12.5.1

build:          builds all

It is possible to build a specific target, such as make ubuntu22_cuda12.3.2, or all the available containers.

Running a given target will create a comfyui-nvidia-docker docker buildx. As long as none are present, this will initiate a build without caching.

The process will create the Dockerfile used within the Dockerfile folder. For example, when using make ubuntu22_cuda12.3.2 a Dockerfile/Dockerfile-ubuntu22_cuda12.3.2 file is created that will contain the steps used to build the local comfyui-nvidia-docker:ubuntu22_cuda12.3.2 Docker image.

3.1.2. Using a Dockerfile

It is also possible to use one of the generated Dockerfile to build a specific image. After selecting the image to build from the OS+CUDA name within the Dockerfile folder, proceed with a docker build command in the directory where this README.md is located. To build the ubuntu24_cuda12.5.1 container, run:

docker build --tag comfyui-nvidia-docker:ubuntu24_cuda12.5.1 -f Dockerfile/Dockerfile-ubuntu24_cuda12.5.1 .

Upon completion of the build, we will have a newly created local comfyui-nvidia-docker:ubuntu24_cuda12.5.1 Docker image.

3.2. Availability on DockerHub

Builds are available on DockerHub at mmartial/comfyui-nvidia-docker, built from this repository's Dockerfile(s).

The table at the top of this document shows the list of available versions on DockerHub. Make sure your NVIDIA container runtime supports the proposed CUDA version. This is particularly important if you use the latest tag, as it is expected to refer to the most recent OS+CUDA release.

3.3. Unraid availability

The container has been tested on Unraid and added to Community Apps an 2024-09-02.

FYSA, if interested, you can see the template from https://raw.githubusercontent.com/mmartial/unraid-templates/main/templates/ComfyUI-Nvidia-Docker.xml

3.4. Nvidia base container

Note that the original Dockerfile FROM is from Nvidia, as such:

This container image and its contents are governed by the NVIDIA Deep Learning Container License.
By pulling and using the container, you accept the terms and conditions of this license:
https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license

4. Screenshots

4.1. First run: Bottle image

4.2. FLUX.1[dev] example

Template at Flux example

5. FAQ

5.1. Virtualenv

The container pip installs all required packages in the container and then creates a virtual environment (in /comfy/mnt/venv with comfy/mnt mounted with the docker run [...]—v).

This allows for the installation of Python packages using pip3 install.

After running docker exec -t comfy-nvidia /bin/bash from the provided bash, activate the venv with source /comfy/mnt/venv/bin/activate. From this bash prompt, you can now run pip3 freeze or other pip3 commands such as pip3 install civitai

5.1.1. Multiple virtualenv

Because a venv is tied to an OS+CUDA version, the tool attempts to create some internal logic so that the venv folder matches the OS+CUDA of the started container. Starting two comfyui-nvidia-docker containers with different OS+CUDA tags at the same time is likely to cause some issues

For illustration, let's say we last ran ubuntu22_cuda12.3.1, exited the container, and now attempt to run ubuntu24_cuda12.5.1. The script initialization is as follows:

check for an existing venv; there is one
check that this venv is for ubuntu24_cuda12.5.1: it is not, it is for ubuntu22_cuda12.3.1
move venv to venv-ubuntu22_cuda12.3.1
check if there is a venv-ubuntu24_cuda12.5.1 to renamed as venv if present: there is not
the script continues as if there was no venv and a new one for ubuntu24_cuda12.5.1 is created

Because of this, it is possible to have multiple venv-based folders in the "run" folder.

5.1.2. Fixing Failed Custom Nodes

A side effect of the multiple virtual environment integration is that some installed custom nodes might have an import failed error when switching from one OS+CUDA version to another. When the container is initialized ,we run cm-cli.py fix all to attempt to fix this. If this does not resolve the issue, start the Manager -> Custom Nodes Manager, Filter by Import Failed, and use the Try fix button. This will download the required packages and install those in the used venv. A Restart and UI reload will be required, but this ought to fix issues with the nodes.

5.2. user_script.bash

The run/user_script.bash user script can perform additional operations. Because this is a Docker container, updating the container will remove any additional installations not in the "run" directory, so it is possible to force a reinstall at runtime. It is also possible to bypass the ComfyUI command started (for people interested in trying the --fast, for example).

To perform those changes, be aware that:

The container image is Ubuntu-based.
The comfy user is sudo capable.

An example of one could be:

#!/bin/bash

echo "== Adding system package"
DEBIAN_FRONTEND=noninteractive sudo apt update
DEBIAN_FRONTEND=noninteractive sudo apt install -y nvtop

echo "== Adding python package"
source /comfy/mnt/venv/bin/activate
pip3 install pipx
echo "== Adding nvitop"
# nvitop will be installed in the user's .local/bin directory which will be removed when the container is updated
pipx install nvitop
# extend the path to include the installation directory
export PATH=/comfy/.local/bin:${PATH}
# when starting a new docker exec, will still need to be run as ~/.local/bin/nvitop
# but will be in the PATH for commands run from within this script

echo "== Override ComfyUI launch command"
# Make sure to have 1) activated the venv before running this command 
# 2) use the COMFY_CMDLINE_EXTRA environment variable to pass additional command-line arguments set during the init script
cd /comfy/mnt/ComfyUI
python3 ./main.py --listen 0.0.0.0 --disable-auto-launch --fast ${COMFY_CMDLINE_EXTRA}

echo "== To prevent the regular Comfy command from starting, we 'exit 1'"
echo "   If we had not overridden it, we could simply end with an ok exit: 'exit 0'" 
exit 1

The script will be placed in the run directory and must be named user_script.bash to be found.

If you encounter an error, it is recommended to check the container logs; this script must be executable and readable by the comfy user. If the file is not executable, the tool will attempt to make it executable, but if another user owns it, the step will fail.

5.3. Available environment variables

5.3.1. WANTED_UID and WANTED_GID

The Linux User ID (uid) and Group ID (gid) will be used by the comfy user within the container. It is recommended that those be set to the end-user's uid and gid to allow the addition of files, models, and other content within the run directory. Content to be added within the run directory must be created with the uid and gid.

The running user's uid and gid can be obtained using id -u and id -g in a terminal.

5.3.2. COMFY_CMDLINE_BASE and COMFY_CMDLINE_EXTRA

You can add extra parameters by adding ComfyUI-compatible command-line arguments to the COMFY_CMDLINE_EXTRA environment variable. For example: docker run [...] -e COMFY_CMDLINE_EXTRA="--fast --reserve-vram 2.0 --lowvram"

Note that the COMFY_CMDLINE_EXTRA variable might be extended by the init script to match additional parameters such as the BASE_DIRECTORY variable.

The default command line used by the script to start ComfyUI is python3 ./main.py --listen 0.0.0.0 --disable-auto-launch This is also the default value set to the COMFY_CMDLINE_BASE variable during the initialization script. It is recommended not to alter the value of this variable, as this might prevent the tool from starting successfully.

The tool will run the combination of COMFY_CMDLINE_BASE followed by COMFY_CMDLINE_EXTRA. In the above example:

python3 ./main.py --listen 0.0.0.0 --disable-auto-launch --fast --reserve-vram 2.0 --lowvram

In case of container failure, checking the container logs for error messages is recommended.

The tool does not attempt to resolve quotes or special shell characters, so it is recommended that you prefer the user_script.bash method.

It is also possible to use the environment variables in combination with the users_script.bash by 1) not starting ComfyUI from the script and 2) exiting with exit 0 (i.e., success), which will allow the rest of the script to continue. The following example installs additional Ubuntu packages and allows for the environment variables to be used:

#!/bin/bash

#echo "== Update installed packages"
DEBIAN_FRONTEND=noninteractive sudo apt-get update
DEBIAN_FRONTEND=noninteractive sudo apt-get upgrade -y

# Exit with an "okay" status to allow the init script to run the regular ComfyUI command
exit 0

Note that pip installation of custom nodes is not possible in normal security level, and weak should be used instead (see the "Security levels" section for details)

5.3.3. BASE_DIRECTORY

The BASE_DIRECTORY environment variable is used to specify the directory where ComfyUI will look for the models, input, output, user and custom_nodes folders. This is a good option to seprate the virtual environment and ComfyUI's code (in the run folder) from the end user's files (in the basedir folder). For Unraid in particular, you can use this to place the basedir on a separate volume, outside of the appdata folder.

This option was added to ComfyUI at the end of January 2025. If you are using an already existing installation, update ComfyUI using the manager before enabling this option.

Once enabled, this option should not be disabled in future run. During the first run with this option, the tool will move exisiting content from the run directory to the BASE_DIRECTORY specified. This is to avoid having multiple copies of downloaded models (taking multiple GB of storage) in both locations. If your models directory is large, I recommend doing a manual mv run/ComfyUI/models basedir/. before running the container. The volumes are considered separate within the container, so the move operation within the container will 1) perform a file copy for each file within the folder (which will take a while) 2) double the model directory size before it is finished copying before it can delete the previous folder. The same logic can be applied to the input, output, user, and custom_nodes folders.

5.3.4. SECURITY_LEVEL

After the initial run, the SECURITY_LEVEL environment variable can be used to alter the default security level imposed by ComfyUI Manager.

When following the rules defined at https://github.com/ltdrdata/ComfyUI-Manager?tab=readme-ov-file#security-policy the user should decide if normal will work for their use case. You will prefer ' weak ' if you manually install or alter custom nodes. WARNING: Using normal- will prevent access to the WebUI.

5.4. ComfyUI Manager & Security levels

ComfyUI Manager is installed and available in the container.

The container is accessible on 0.0.0.0 internally to the container (i.e., all network interfaces), but it is only accessible on the exposed port outside of the running container.

To modify the security_level:

manually: by going into your "run" folder directory and editing either ComfyUI/user/default/ComfyUI-Manager/config.ini if present, otherwise custom_nodes/ComfyUI-Manager/config.ini and alter the security_level = to match your requirements (then reload ComfyUI)
automatically: use the SECURITY_LEVEL docker environment variable at run time to set it for this run.

Note that if this is the first time starting the container, the file will not yet exist; it is created the first time ComfyUI is run. After this step, stop and restart the container; the config.ini will be there at consecutive restarts

To use cm-cli, from the virtualenv, use: python3 /comfy/mnt/custom_nodes/ComfyUI-Manager/cm-cli.py. For example: python3 /comfy/mnt/custom_nodes/ComfyUI-Manager/cm-cli.py show installed (COMFYUI_PATH=/ComfyUI should be set)

5.5. Shell within the Docker image

Depending on your WANTED_UID and WANTED_GID, when starting a docker exec (or getting a bash terminal from docker compose), it is possible that the shell is started with incorrect permissions (we will see a bash: /comfy/.bashrc: Permission denied error). The comfy user is sudo-able: run sudo su comfytoo to get the proper UID/GID.

5.6. Additional FAQ

See [extras/FAQ.md] for additional FAQ topics, among which:

Updating ComfyUI
Updating ComfyUI-Manager
Installing a custom node from git

5.6.1. Windows: WSL2 and podman

The container can be used on Windows using WSL2. In the following, we will describe the method to use the podman command line interface. For Docker Desktop users, please see https://docs.docker.com/desktop/features/gpu/ for details on how to enable GPU support with Docker.

First, follow the steps in Section 2 ("Getting Started with CUDA on WSL 2") of https://docs.nvidia.com/cuda/wsl-user-guide/index.html

Once you have your Ubuntu Virtual Machine installed, start its terminal and follow the instructions to create your new user account (in the rest of this section we will use USER to refer to it, adapt as needed) and set a password (which you will use for sudo commands). Check your UID and GID using id; by default those should be 1000 and 1000.

Then, from the terminal, run the following commands (for further details on some of the steps below, see https://blg.gkr.one/20240404-u24_nvidia_docker_podman/ ):

# Update the package list & Upgrade the already installed packages
sudo apt update && sudo apt upgrade -y

# Install podman
sudo apt install -y podman

# Install the nvidia-container-toolkit
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
  && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
    sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit

# Generate the Container Device Interface (CDI) for podman
sudo nvidia-ctk cdi generate --output=/etc/cdi/nvidia.yaml
# note that when you update the Nvidia driver, you will need to regenerate the CDI

Then you can confirm the CUDA version your driver supports with:

podman run --rm --device nvidia.com/gpu=all ubuntu nvidia-smi

with the latest driver, you can support CUDA 12.8 or above, which is needed for RTX 50xx GPUs.

In the following, we will run the latest tag but you can modify this depending on the CUDA version you want to support.

To run the container:

# Create the needed data directories
# 'run' will contain your virtual environment(s), ComfyUI source code, and Hugging Face Hub data
# 'basedir' will contain your custom nodes, input, output, user and models directories
mkdir run basedir

# Download and start the container
# - the directories will be written with your user's UID and GID
# - the ComfyUI-Manager security levels will be set to "normal"
# - we will expose the WebUI to http://127.0.0.1:8188
# please see other sections of this README.md for options
podman run --rm -it --userns=keep-id --device nvidia.com/gpu=all -v `pwd`/run:/comfy/mnt -v `pwd`/basedir:/basedir -e WANTED_UID=`id -u` -e WANTED_GID=`id -g` -e BASE_DIRECTORY=/basedir -e SECURITY_LEVEL=normal -p 127.0.0.1:8188:8188 --name comfyui-nvidia docker.io/mmartial/comfyui-nvidia-docker:latest

Once started, go to http://127.0.0.1:8188 and enjoy your first workflow (the bottle example). With this workflow, ComfyUI-Manager should offer to download the model. but since your browser runs on the Windows side, we will need to move the downloaded file to the Ubuntu VM. In another Ubuntu terminal, run (adapt USER): mv /mnt/c/Users/USER/Downloads/v1-5-pruned-emaonly-fp16.safetensors basedir/models/checkpoints/. You will see that basedir and run are owned by your USER.

After using ComfyUI, Ctrl+C in the podman terminal will terminate the WebUI. Use the podman run ... command from the same folder in the Ubuntu terminal to restart it and use the same run and basedir as before.

5.6.2. RTX 5080/5090 support

To use the RTX 5080/5090 GPUs, you will need to make sure to install NVIDIA driver 570 or above. This driver brings support for the RTX 50xx series of GPUs and CUDA 12.8. PyTorch is also installed from the nightly version (until the official release of 2.7.0 with CUDA 12.8 support).

5.6.3. Specifying alternate folder location (ex: --output_directory) with BASE_DIRECTORY

The BASE_DIRECTORY environment variable can be used to specify an alternate folder location for input, output, temp, user, models and custom_nodes. The ComfyUI CLI provides means to specify the location of some of those folders from the command line.

--output-directory for output
--input-directory for input
--temp-directory for temp
--user-directory for user Each one of those option overrides --base-directory.

The logic in init.bash moves the content of input, output, temp, user and models to the specified BASE_DIRECTORY the first time it is used if the destination folder does not exist.

The script logic is based on the BASE_DIRECTORY environment variable alone. For end-users who prefer to use one of those alternate folder command lines, those can be added to either the COMFY_CMDLINE_EXTRA environment variable or the user_script.bash script (please refer to the other sections of this document that describe those options).

Indepent of the method used the core logic is the same (the example will specify the output folder):

you will need to make sure a new folder is mounted within the container (ex: docker run ... -v /preferredlocation/output:/output)
tell the ComfyUI command line to use that location for its outputs: python3 ./main.py [...] --output-directory /output
(optional) make sure to copy the already existing content of output to the new location if you want consitency.

Please note that an output folder will still exist in the basedir location (per the BASE_DIRECTORY logic) but the comamnd line option will tell Confy to override it.

For Unraid users, those steps can done by editing the template from the Docker tab, Editing the container and using Add another Path, Port, Variable, Label or Device to:

add a new Path entry (name it output directory) with a Container Path with value /output, a Host Path with your selected lcoation, for example /preferredlocation/output, and an Access Mode of Read/Write.
edit the existing COMFY_CMDLINE_EXTRA variable to add the --output-directory /output option.

6. Troubleshooting

6.1. Virtual environment

The venv in the "run" directory contains all the Python packages the tool requires. In case of an issue, it is recommended that you terminate the container, delete (or rename) the venv directory, and restart the container. The virtual environment will be recreated; any custom_scripts should re-install their requirements; please see the "Fixing Failed Custom Nodes" section for additional details.

6.2. run directory

It is also possible to rename the entire "run" directory to get a clean installation of ComfyUI and its virtual environment. This method is preferred, compared to deleting the "run" directory—as it will allow us to copy the content of the various downloaded ComfyUI/models, ComfyUI/custom_nodes, generated ComfyUI/outputs, ComfyUI/user, added ComfyUI/inputs, and other folders present within the old "run" directory. If using the BASE_DIRECTORY environment variable, please note that some of that run directory content will be moved to the BASE_DIRECTORY specified.

6.3. using BASE_DIRECTORY with an outdated ComfyUI

If using the BASE_DIRECTORY option and the program exit saying the --base-directory option does not exist, this is due to an outdated ComfyUI installation. A possible solution is to disable the option, restart the container and use the ComfyUI-Manager to update ComfyUI. Another option is manually update the code: cd run/ComfyUI; git pull In some case, it is easier to create a simple user_script.bash to perform those steps; particularly on Unraid. The run/user_script.bash file content would be (on Unraid it would go in /mnt/user/appdata/comfyui-nvidia/mnt)

#!/bin/bash

cd /comfy/mnt/ComfyUI
git pull

exit 0

Make sure to change file ownership to the user with the WANTED_UID and WANTED_GID environment variables and to make it executable (on Unraid in the directory, run chown nobody:users user_script.bash; chmod +x user_script.bash)

After the process complete, you should be presented with the WebUI. Make to delete or rename the script to avoid upgrading ComfyUI at start time, and use ComfyUI Manager instead.

7. Changelog

20250216: Fix issue with empty BASE_DIRECTORY variable
20250202: Added BASE_DIRECTORY variable
20250116: Happy 2nd Birthday ComfyUI -- added multiple builds for different base Ubuntu OS and CUDA combinations + added ffmpeg into the base container.
20250109: Integrated SECURITY_LEVELS within the docker arguments + added libGL into the base container.
20240915: Added COMFY_CMDLINE_BASE and COMFY_CMDLINE_EXTRA variable
20240824: Tag 0.2: shift to pull at first run-time, user upgradable with lighter base container
20240824: Tag 0.1: builds were based on ComfyUI release, not user upgradable
20240810: Initial Release

Name		Name	Last commit message	Last commit date
Latest commit History 131 Commits
Dockerfile		Dockerfile
assets		assets
components		components
extras		extras
workflow		workflow
.gitignore		.gitignore
LICENSE		LICENSE
Makefile		Makefile
README.md		README.md
init.bash		init.bash

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ComfyUI (NVIDIA) Docker

Quick Start

ComfyUI (NVIDIA) Docker

1. Preamble

2. Running the container

2.1. docker run

2.2. podman

2.3. Docker compose

2.4. First time use

3. Docker image

3.1. Building the image

3.1.1. Using the Makefile

3.1.2. Using a Dockerfile

3.2. Availability on DockerHub

3.3. Unraid availability

3.4. Nvidia base container

4. Screenshots

4.1. First run: Bottle image

4.2. FLUX.1[dev] example

5. FAQ

5.1. Virtualenv

5.1.1. Multiple virtualenv

5.1.2. Fixing Failed Custom Nodes

5.2. user_script.bash

5.3. Available environment variables

5.3.1. WANTED_UID and WANTED_GID

5.3.2. COMFY_CMDLINE_BASE and COMFY_CMDLINE_EXTRA

5.3.3. BASE_DIRECTORY

5.3.4. SECURITY_LEVEL

5.4. ComfyUI Manager & Security levels

5.5. Shell within the Docker image

5.6. Additional FAQ

5.6.1. Windows: WSL2 and podman

5.6.2. RTX 5080/5090 support

5.6.3. Specifying alternate folder location (ex: --output_directory) with BASE_DIRECTORY

6. Troubleshooting

6.1. Virtual environment

6.2. run directory

6.3. using BASE_DIRECTORY with an outdated ComfyUI

7. Changelog

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