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The most powerful and modular AI engine for content creation.
ComfyUI is the AI creation engine for visual professionals who demand control over every model, every parameter, and every output. Its powerful and modular node graph interface empowers creatives to generate images, videos, 3D models, audio, and more...
- ComfyUI natively supports the latest open-source state of the art models.
- It is by far the most optimized inference engine for diffusion models in the world with a focus on local consumer hardware.
- Can run even the biggest open source models on as low as 4GB vram + 8GB ram relatively quickly (saturating your GPU compute) using our state of the art asynchronous weight streaming technology.
- Partner nodes provide access to the best closed source models such as Nano Banana, Seedance, Hunyuan3D, etc.
- It is available on Windows, Linux, and macOS, locally with our desktop application, our portable install or on our cloud.
- The most sophisticated workflows can be exposed through a simple UI thanks to App Mode.
- It integrates seamlessly into production pipelines with our API endpoints.
- The easiest way to get started.
- Available on Windows & macOS.
Supports all operating systems and GPU types (NVIDIA, AMD, Intel, Apple Silicon, Ascend).
- Our official paid cloud version for those who can't afford local hardware.
See what ComfyUI can do with the newer template workflows or old example workflows.
- A visual node graph for building and reusing image, video, audio, 3D, and text workflows without code.
- Reusable subgraphs, workflow templates, App Mode, and a local API for integrating workflows into applications.
- Efficient local execution with asynchronous queueing, partial graph re-execution, smart VRAM and RAM management, model offloading, and support for quantized models.
- Broad native model support. This is a representative list; browse the workflow library for maintained, ready-to-run templates.
- Image generation: Stable Diffusion 1.5, SDXL, SD3.5, Flux.1, Flux.2, Qwen Image, Z-Image, Hunyuan Image 2.1, HiDream, Lumina Image 2.0, Chroma, Anima, LongCat Image, Ideogram 4, Krea 2, MageFlow, Microsoft Lens, PixelDiT, Kandinsky 5, Ernie Image and Moss Image.
- Image editing: Flux Kontext, Flux.2 Klein, Qwen Image Edit, HiDream E1.1 and O1, OmniGen2, Boogu, JoyImage Edit, MageFlow Edit, and LongCat Image Edit.
- Video generation: Wan 2.1 and 2.2, LTX-Video 2 and 2.3, HunyuanVideo 1.5, Kandinsky 5 Video, CogVideoX, Cosmos Predict2, Bernini-R, SCAIL 2, and Mochi.
- Audio and video generation: MiniMax H3 and LTX-AV.
- Audio generation: ACE-Step 1.5, Stable Audio 3, MiniMax Music 3 and Yue 2.
- 3D and vision: Hunyuan3D 2.1, TripoSplat, SeedVR2, SUPIR, Depth Anything 3, MoGe, SAM 3 and 3.1, RT-DETRv4, and BiRefNet.
- Text generation: Gemma 3 and 4, Qwen3, Qwen3.5, and Qwen3-VL, including multimodal inputs.
- Load complete checkpoints or separate diffusion models, VAEs, text encoders, LoRAs, ControlNets, adapters, and upscalers from supported model formats.
- Built-in tools for inpainting, outpainting, reference conditioning, masks and compositing, model merging, upscaling, frame interpolation, segmentation, depth estimation, and media processing.
- Save and load workflows as JSON, or recover complete workflows and seeds from supported generated media.
- Runs fully offline: core does not download anything unless you request it. Use
--offlineto disable the optional paid Comfy API nodes and force all built-in functionality to stay offline, or--disable-partner-nodesto only disable the API nodes. - Extend ComfyUI with custom nodes
- Configure additional model locations with
extra_model_paths.yaml. - Support for saving and loading high bit depth images and videos: 16 bit PNG images, 32 bit EXR, 10 bit AVIF are supported and more.
- Support for saving and loading HDR videos and images in various formats.
ComfyUI follows a weekly release cycle targeting Monday but this regularly changes because of model releases or large changes to the codebase. There are three interconnected repositories:
- Releases a new major stable version (e.g., v0.7.0) roughly every 2 weeks.
- Starting from v0.4.0 patch versions will be used for fixes backported onto the current stable release.
- Minor versions will be used for releases off the master branch.
- Patch versions may still be used for releases on the master branch in cases where a backport would not make sense.
- Commits outside of the stable release tags may be very unstable and break many custom nodes.
- Serves as the foundation for the desktop release
- Builds a new release using the latest stable core version
- Every 2+ weeks frontend updates are merged into the core repository
- Features are frozen for the upcoming core release
- Development continues for the next release cycle
| Keybind | Explanation |
|---|---|
Ctrl + Enter | Queue up current graph for generation |
Ctrl + Shift + Enter | Queue up current graph as first for generation |
Ctrl + Alt + Enter | Cancel current generation |
Ctrl + Z/Ctrl + Y | Undo/Redo |
Ctrl + S | Save workflow |
Ctrl + O | Load workflow |
Ctrl + A | Select all nodes |
Alt + C | Collapse/uncollapse selected nodes |
Ctrl + M | Mute/unmute selected nodes |
Ctrl + B | Bypass selected nodes (acts like the node was removed from the graph and the wires reconnected through) |
Delete/Backspace | Delete selected nodes |
Ctrl + Backspace | Delete the current graph |
Space | Move the canvas around when held and moving the cursor |
Ctrl/Shift + Click | Add clicked node to selection |
Ctrl + C/Ctrl + V | Copy and paste selected nodes (without maintaining connections to outputs of unselected nodes) |
Ctrl + C/Ctrl + Shift + V | Copy and paste selected nodes (maintaining connections from outputs of unselected nodes to inputs of pasted nodes) |
Shift + Drag | Move multiple selected nodes at the same time |
Ctrl + D | Load default graph |
Alt + + | Canvas Zoom in |
Alt + - | Canvas Zoom out |
Ctrl + Shift + LMB + Vertical drag | Canvas Zoom in/out |
P | Pin/Unpin selected nodes |
Ctrl + G | Group selected nodes |
Q | Toggle visibility of the queue |
H | Toggle visibility of history |
R | Refresh graph |
F | Show/Hide menu |
. | Fit view to selection (Whole graph when nothing is selected) |
| Double-Click LMB | Open node quick search palette |
Shift + Drag | Move multiple wires at once |
Ctrl + Alt + LMB | Disconnect all wires from clicked slot |
Ctrl can also be replaced with Cmd instead for macOS users
We highly recommend using the desktop app:
The desktop app is the easiest and best way to use ComfyUI for new users.
There is a portable standalone build for Windows that should work for running on Nvidia GPUs or for running on your CPU only. It is not recommended for regular users. Regular users should use the desktop app above.
Direct link to download (nvidia)
Simply download, extract with 7-Zip or with the windows explorer on recent windows versions and run. For smaller models you normally only need to put the checkpoints (the huge ckpt/safetensors files) in: ComfyUI\models\checkpoints but many of the larger models have multiple files. Make sure to follow the instructions to know which subfolder to put them in ComfyUI\models\
If you have trouble extracting it, right click the file -> properties -> unblock
The portable above currently comes with python 3.13 and pytorch cuda 13.0. Update your Nvidia drivers if it doesn't start.
Portable for Nvidia GPUs (supports 20 series and above).
Portable for Nvidia GPUs with pytorch cuda 12.6 and python 3.12 (Supports Nvidia 10 series and older GPUs, DO NOT USE THIS ON NEWER 20 SERIES AND ABOVE GPUS).
See the Config file to set the search paths for models. In the standalone windows build you can find this file in the ComfyUI directory. Rename this file to extra_model_paths.yaml and edit it with your favorite text editor.
You can install and start ComfyUI using comfy-cli:
pip install comfy-cli comfy installPython 3.14 works but some custom nodes may have issues. The free threaded variant works but some dependencies will enable the GIL so it's not fully supported.
Python 3.13 is very well supported. If you have trouble with some custom node dependencies on 3.13 you can try 3.12
torch 2.7 is minimally supported but using a newer version is extremely recommended. Using a cu130 or above version of pytorch is required on Nvidia 20 series and above. Some features and optimizations might only work on newer versions. We generally recommend using the latest major version of pytorch with the latest cuda version unless it is less than 2 weeks old. If your pytorch is more than 6 months old, please update it.
Git clone this repo.
Put your SD checkpoints (the huge ckpt/safetensors files) in: models/checkpoints
Put your VAE in: models/vae
AMD users can install rocm and pytorch with pip if you don't have it already installed, this is the command to install the stable version:
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.2
This is the command to install the nightly with ROCm 7.2 which might have some performance improvements:
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.2
Use AMD's multi-architecture PyTorch packages. The device-* extras install your GPU's kernels and the matching ROCm runtime automatically; a separate HIP SDK installation is not needed.
Use Windows 11, a current AMD graphics driver, and 64-bit Python 3.13.
The install command below uses device-all to install kernels for all supported GPUs. To reduce download size and disk usage, optionally replace both occurrences of device-all with the target for your GPU:
| GPU | Device extra |
|---|---|
| RX 9070 / XT, Radeon AI PRO R9700 | device-gfx1201 |
| RX 9060 / XT | device-gfx1200 |
| RX 7900 XT / XTX | device-gfx1100 |
| RX 7700 XT / 7800 XT | device-gfx1101 |
| RX 7600 / XT | device-gfx1102 |
| Ryzen AI Max / Max+ (Strix Halo) | device-gfx1151 |
Note: This table only lists examples. A GPU missing from it may still be supported: supported architectures include RDNA 2, RDNA 3, RDNA 3.5, and RDNA 4. Keep device-all to install kernels for all supported targets. For other models, see AMD's GPU target table and ROCm compatibility matrix.
ROCm 10.0.0 with PyTorch 2.13:
pip install --index-url https://stable.repo.amd.com/rocm/whl-next/ "torch[device-all]==2.13.0+rocm10.0.0""torchvision[device-all]==0.28.0+rocm10.0.0""torchaudio==2.11.0.2+rocm10.0.0"Intel Arc GPU users can install native PyTorch with torch.xpu support using pip. More information can be found here
- To install PyTorch xpu, use the following command:
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/xpu
This is the command to install the Pytorch xpu nightly which might have some performance improvements:
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/xpu
Nvidia users should install stable pytorch using this command:
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu130
This is the command to install pytorch nightly instead which might have performance improvements.
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu132
If you get the "Torch not compiled with CUDA enabled" error, uninstall torch with:
pip uninstall torch
And install it again with the command above.
Install the dependencies by opening your terminal inside the ComfyUI folder and:
pip install -r requirements.txt
After this you should have everything installed and can proceed to running ComfyUI.
You can install ComfyUI in Apple Mac silicon (M1, M2, M3 or M4) with any recent macOS version.
- Install pytorch nightly. For instructions, read the Accelerated PyTorch training on Mac Apple Developer guide (make sure to install the latest pytorch nightly).
- Follow the ComfyUI manual installation instructions for Windows and Linux.
- Install the ComfyUI dependencies. If you have another Stable Diffusion UI you might be able to reuse the dependencies.
- Launch ComfyUI by running
python main.py
Note: Remember to add your models, VAE, LoRAs etc. to the corresponding Comfy folders, as discussed in ComfyUI manual installation.
For models compatible with Huawei Ascend Extension for PyTorch (torch_npu). To get started, ensure your environment meets the prerequisites outlined on the installation page. Here's a step-by-step guide tailored to your platform and installation method:
- Begin by installing the recommended or newer kernel version for Linux as specified in the Installation page of torch-npu, if necessary.
- Proceed with the installation of Ascend Basekit, which includes the driver, firmware, and CANN, following the instructions provided for your specific platform.
- Next, install the necessary packages for torch-npu by adhering to the platform-specific instructions on the Installation page.
- Finally, adhere to the ComfyUI manual installation guide for Linux. Once all components are installed, you can run ComfyUI as described earlier.
For models compatible with Cambricon Extension for PyTorch (torch_mlu). Here's a step-by-step guide tailored to your platform and installation method:
- Install the Cambricon CNToolkit by adhering to the platform-specific instructions on the Installation
- Next, install the PyTorch(torch_mlu) following the instructions on the Installation
- Launch ComfyUI by running
python main.py
For models compatible with Iluvatar Extension for PyTorch. Here's a step-by-step guide tailored to your platform and installation method:
- Install the Iluvatar Corex Toolkit by adhering to the platform-specific instructions on the Installation
- Launch ComfyUI by running
python main.py
ComfyUI-Manager is an extension that allows you to easily install, update, and manage custom nodes for ComfyUI.
Install the manager dependencies:
pip install -r manager_requirements.txt
Enable the manager with the
--enable-managerflag when running ComfyUI:python main.py --enable-manager
| Flag | Description |
|---|---|
--enable-manager | Enable ComfyUI-Manager |
--enable-manager-legacy-ui | Use the legacy manager UI instead of the new UI (implies --enable-manager) |
--disable-manager-ui | Disable the manager UI and endpoints while keeping background features like security checks and scheduled installation completion (requires --enable-manager) |
python main.py
Try running it with this command if you have issues:
For 6700, 6600 and maybe other RDNA2 or older: HSA_OVERRIDE_GFX_VERSION=10.3.0 python main.py
For AMD 7600 and maybe other RDNA3 cards: HSA_OVERRIDE_GFX_VERSION=11.0.0 python main.py
You can try setting this env variable PYTORCH_TUNABLEOP_ENABLED=1 which might speed things up at the cost of a very slow initial run.
Only parts of the graph that have an output with all the correct inputs will be executed.
Only parts of the graph that change from each execution to the next will be executed, if you submit the same graph twice only the first will be executed. If you change the last part of the graph only the part you changed and the part that depends on it will be executed.
Dragging a generated png on the webpage or loading one will give you the full workflow including seeds that were used to create it.
You can use () to change emphasis of a word or phrase like: (good code:1.2) or (bad code:0.8). The default emphasis for () is 1.1. To use () characters in your actual prompt escape them like \( or \).
You can use {day|night}, for wildcard/dynamic prompts. With this syntax "{wild|card|test}" will be randomly replaced by either "wild", "card" or "test" by the frontend every time you queue the prompt. To use {} characters in your actual prompt escape them like: \{ or \}.
Dynamic prompts also support C-style comments, like // comment or /* comment */.
To use a textual inversion concepts/embeddings in a text prompt put them in the models/embeddings directory and use them in the CLIPTextEncode node like this (you can omit the .pt extension):
embedding:embedding_filename.pt
Use --preview-method auto to enable previews.
The default installation includes a fast latent preview method that's low-resolution. To enable higher-quality previews with TAESD, download the taesd_decoder.pth, taesdxl_decoder.pth, taesd3_decoder.pth and taef1_decoder.pth and place them in the models/vae_approx folder. Once they're installed, restart ComfyUI and launch it with --preview-method taesd to enable high-quality previews.
Generate a self-signed certificate (not appropriate for shared/production use) and key by running the command: openssl req -x509 -newkey rsa:4096 -keyout key.pem -out cert.pem -sha256 -days 3650 -nodes -subj "/C=XX/ST=StateName/L=CityName/O=CompanyName/OU=CompanySectionName/CN=CommonNameOrHostname"
Use --tls-keyfile key.pem --tls-certfile cert.pem to enable TLS/SSL, the app will now be accessible with https://... instead of http://....
Note: Windows users can use alexisrolland/docker-openssl or one of the 3rd party binary distributions to run the command example above.
If you use a container, note that the volume mount-vcan be a relative path so... -v ".\:/openssl-certs" ...would create the key & cert files in the current directory of your command prompt or powershell terminal.
Discord: Try the #help or #feedback channels.
Matrix space: #comfyui_space:matrix.org (it's like discord but open source).
See also: https://www.comfy.org/
psst — we're hiring! Help build ComfyUI: comfy.org/careers
As of August 15, 2024, we have transitioned to a new frontend, which is now hosted in a separate repository: ComfyUI Frontend. The compiled JS files (from TS/Vue) are published to pypi and installed as a dependency in ComfyUI.
For any bugs, issues, or feature requests related to the frontend, please use the ComfyUI Frontend repository. This will help us manage and address frontend-specific concerns more efficiently.
The new frontend is now the default for ComfyUI. However, please note:
- The frontend in the main ComfyUI repository is updated fortnightly.
- Daily releases are available in the separate frontend repository.
To use the most up-to-date frontend version:
For the latest daily release, launch ComfyUI with this command line argument:
--front-end-version Comfy-Org/ComfyUI_frontend@latestFor a specific version, replace
latestwith the desired version number:--front-end-version Comfy-Org/[email protected]
This approach allows you to easily switch between the stable fortnightly release and the cutting-edge daily updates, or even specific versions for testing purposes.