ComfyUI Guide: What It Is, Features, and How to Get Started

What it is

ComfyUI is a modular graphical user interface (GUI), application programming interface (API), and backend execution engine built for running generative diffusion models. Instead of presenting users with a conventional form-based dashboard, the software organizes complex computational steps as an interactive node graph on an infinite visual canvas. In this environment, individual functional blocks—referred to as nodes—handle distinct operational tasks such as loading neural network weights, processing text prompts, applying mathematical adjustments, or decoding latent representations into final graphics. Users connect these individual nodes using virtual patch cables or wires, directing the exact flow of data through each phase of generation.

To understand the architecture, several foundational artificial intelligence concepts are helpful. A diffusion model generates media by learning to reverse a process of gradual data degradation, progressively turning random noise into structured images, sounds, or videos. Checkpoints are large unified data files containing the trained parameters and weights of a model. Latent representations are compressed mathematical descriptions of media that require specialized decoders, known as Variational Autoencoders (VAEs), to become viewable media files. Video random access memory (VRAM) refers to the dedicated high-speed memory located directly on a computer’s graphics card, while system RAM resides on the motherboard.

ComfyUI manages these system resources through partial graph re-execution, dynamic model offloading, and an asynchronous queueing system. Because the engine tracks which nodes have been modified, it only recomputes parts of the graph where parameters or connections have changed, saving computing cycles during iterative work.

According to the project README, ComfyUI describes itself as “the fastest local inference engine in the world” and “by far the most optimized inference engine for diffusion models in the world with a focus on local consumer hardware.” The software is designed to run locally across Windows, macOS, and Linux operating systems as a desktop application, a standalone portable directory, or a manual installation, while also offering a hosted cloud deployment through Comfy Cloud. Project repository metadata indicates that the core software is published under the GNU General Public License v3.0 (GPL-3.0).

What it can do

ComfyUI natively supports a diverse array of generative media modalities, including still images, animations and videos, synthesized audio, multimodal combinations, 3D geometry, and language generation. Rather than restricting users to a single architecture, the interface can run a broad selection of open-source models across various domains.

For text-to-image creation and image editing, the platform natively supports models such as 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, and Ernie Image. For dedicated image manipulation tasks, supported frameworks include Flux Kontext, Flux.2 Klein, Qwen Image Edit, HiDream E1.1 and O1, OmniGen2, Boogu, JoyImage Edit, MageFlow Edit, and LongCat Image Edit.

For video synthesis, the engine accommodates models such as 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 production is supported through models like ACE-Step 1.5, Stable Audio 3, MiniMax Music 3, and Yue 2, while combined audiovisual generation is available via models including MiniMax H3 and LTX-AV. In the realm of 3D vision, depth analysis, and spatial modeling, ComfyUI supports Hunyuan3D 2.1, TripoSplat, SeedVR2, SUPIR, Depth Anything 3, MoGe, SAM 3 and 3.1, RT-DETRv4, and BiRefNet. The platform also handles natural language and multimodal processing using models such as Gemma 3 and 4, Qwen3, Qwen3.5, and Qwen3-VL.

In addition to foundational model inference, ComfyUI incorporates dedicated nodes for tasks including inpainting, outpainting, reference conditioning, image compositing, model merging, upscaling, frame interpolation, depth estimation, and semantic segmentation. Inpainting refers to regenerating or modifying a specific masked region of an existing picture, while outpainting extends the borders of an image into empty space. The platform allows users to load whole checkpoints or modular components, such as individual text encoders, VAEs, Low-Rank Adaptations (LoRAs), ControlNets, and adapter weights.

Workflows created on the canvas can be saved, exported, and shared as portable JSON files. Because generation metadata and seeds can be embedded directly into output files, users can also recover an entire workflow simply by dragging and dropping a supported generated image or video back onto the ComfyUI canvas. For complex pipelines, an integrated App Mode allows creators to collapse detailed node arrangements into an uncluttered interface. According to the official website, ComfyUI also features Comfy Agent, an automated assistant that can plan, construct, and execute workflows on the canvas from natural language descriptions.

ComfyUI is built to function fully offline. The core framework does not download external assets without user initiation. To ensure that environments remain strictly isolated from online services, users can launch the program with the --offline command-line flag, which disables optional paid API nodes while keeping native functionality offline, or use --disable-partner-nodes to turn off external partner integrations. The platform also accommodates high-end digital imaging standards, supporting high bit-depth files—such as 16-bit PNG, 32-bit EXR, and 10-bit AVIF—as well as HDR image and video outputs.

How to get started

ComfyUI can be deployed through multiple installation routes depending on the user’s operating system, technical comfort level, and hardware configuration.

For Windows and macOS users looking for a straightforward setup, the project documentation points to the official desktop application available via the Comfy website as the easiest method.

Users who prefer command-line tools can install and initialize ComfyUI using the official comfy-cli utility through Python’s package manager:

pip install comfy-cli
comfy install

For Windows users who wish to run ComfyUI without modifying system-level Python environments, standalone portable packages are distributed as 7z archives for NVIDIA, AMD, and Intel graphics cards, as well as CPU-only setups. Users download the archive, extract it using 7-Zip or Windows Explorer, and launch the executable. Model checkpoint files are placed inside the ComfyUI\models\checkpoints folder, while VAE files go into models/vae. To share model libraries with other generative software without duplicating files on disk, users can rename the provided configuration template to extra_model_paths.yaml and specify custom folder locations.

For manual installations on Windows or Linux, users clone the official Git repository and configure their Python environment. Python 3.13 is well supported by the core project, while Python 3.12 remains an alternative for resolving specific custom node dependencies. Python 3.14 functions, although free-threaded builds may encounter dependency issues when third-party components enable the Global Interpreter Lock (GIL).

According to the project README, PyTorch 2.7 is the minimum baseline version, though modern releases are strongly recommended, and PyTorch builds with CUDA 13.0 or higher are required for NVIDIA 20-series GPUs and newer.

For NVIDIA hardware, stable PyTorch is installed using:

pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu130

To install the NVIDIA nightly build, the command is:

pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu132

If an error indicates that PyTorch was not compiled with CUDA enabled, the project documentation directs users to remove the existing installation:

pip uninstall torch

After removal, PyTorch can be reinstalled using the appropriate NVIDIA installation command.

For Linux users running AMD graphics cards, the stable ROCm package is installed via:

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.2

For Windows users operating supported AMD GPUs under ROCm 10.0, the multi-architecture package is installed using:

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"

For Intel Arc graphics on Windows and Linux, native PyTorch with XPU acceleration is installed using:

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/xpu

Once the application is running, users navigate the canvas using built-in hotkeys. Holding Space while dragging moves the view across the workspace, double-clicking the left mouse button opens a quick search palette to add new nodes, pressing Ctrl + Enter (or Cmd + Enter on macOS) queues the current graph for generation, and pressing Ctrl + S saves the workflow.

Pricing and requirements

ComfyUI is an open-source project distributed under the GNU General Public License v3.0 (GPL-3.0), as recorded in its repository metadata. The core application, including its desktop software and standalone local packages, can be downloaded and run locally on personal hardware free of software licensing charges.

For cloud hosting, API endpoints, developer platform features, and enterprise-grade infrastructure, pricing and plans are subject to the official page. The project website notes that Comfy Cloud provides access for users seeking hosted environments with free trial options. In addition, the official website notes that Comfy acts as the official reseller for MiniMax commercial licenses, which grant commercial usage rights for teams running MiniMax models locally on their own hardware.

Hardware requirements vary based on the scale of the models being executed. ComfyUI supports graphics hardware from NVIDIA, AMD, and Intel, Apple Silicon chips, and CPU-only operation. According to the project README, ComfyUI can run even the largest open-source models on as low as 4GB of VRAM and 8GB of system RAM relatively quickly by employing asynchronous weight streaming to maximize GPU utilization.

On the software side, manual deployments require a 64-bit Python installation (preferably Python 3.13) alongside a compatible PyTorch environment. While PyTorch 2.7 serves as the minimum requirement, the README advises updating PyTorch installations that are more than six months old, and notes that a CUDA 13.0 or higher environment is required for NVIDIA GeForce RTX 20-series graphics cards and newer.

Who it is for

ComfyUI is created for digital artists, visual effects specialists, and designers who demand granular control over every aspect of generative AI pipelines. Because every processing node, mask, latent representation, and mathematical parameter is directly visible on an open canvas, practitioners can craft custom multi-step workflows that go beyond the limitations of standard text-prompt interfaces.

The software is also structured for developers, technical directors, and pipeline engineers. Workflows constructed inside the visual editor can be saved as subgraphs or exported via API endpoints, enabling automated integration into external production tools. According to the project website, ComfyUI is utilized across commercial industries, including visual effects and animation, advertising and creative design studios, game development, and eCommerce and fashion production.

Alternatives

InvokeAI is an open-source creative engine and user interface designed for generating visual media with generative diffusion models.

Stable Diffusion WebUI is a widely used open-source browser interface built for running and managing diffusion-based image generation workflows.

Sources

• https://github.com/Comfy-Org/ComfyUI
• https://www.comfy.org/
• https://github.com/invoke-ai/InvokeAI
• https://github.com/AUTOMATIC1111/stable-diffusion-webui