ComfyUI: AI Workflow Engine for Diffusion Models
/ComfyUI
ComfyUI is a node-based interface for running diffusion models — Stable Diffusion, Flux, and other image, video, audio, and 3D generators — where you wire together nodes instead of typing into a single prompt box. Reach for it if you want to see and control every step of a generation pipeline; skip it if you just want one-click output, because the node graph has a real learning curve.
What is ComfyUI?
ComfyUI is an AI creation engine built around a graph/nodes interface: you assemble models, samplers, encoders, and post-processing steps as connected nodes instead of running a fixed pipeline behind a single form. It handles image, video, 3D, and audio generation, runs locally on Windows, Linux, and macOS or in Comfy Cloud, and exposes a local API so a finished node graph can be called from other applications.
Who is ComfyUI for?
ComfyUI fits visual professionals and technical hobbyists who want to see and adjust every stage of a generation pipeline — swapping a sampler, chaining a LoRA, or bypassing a node with Ctrl+B — rather than accept whatever a single-prompt app decides for them. App Mode lets a builder hand a finished workflow to a non-technical teammate as a plain form, so a studio can have one person design pipelines and others just run them. Skip it if you want to type a prompt and get an image in one step with no setup — a hosted, single-purpose generator will get you there faster.
Getting Started with ComfyUI
ComfyUI documents three ways to run it locally, plus a paid cloud option. The desktop application (Windows and macOS) is what the README calls the easiest and best way to start for new users. A Windows portable package bundles the latest commits and needs no separate Python setup, but the README says it isn't recommended for regular users — it ships with Python 3.13 and CUDA 13.0 pytorch, with a separate build (pytorch CUDA 12.6, Python 3.12) for Nvidia 10-series and older cards, since the main portable build only supports 20-series GPUs and above. Manual install works on Windows, Linux, and macOS with NVIDIA, AMD, Intel, or Apple Silicon GPUs, plus Ascend NPUs: clone the repo, drop checkpoints into models/checkpoints and VAEs into models/vae, install the GPU-matched pytorch build (the README gives separate pip commands for ROCm on AMD, XPU on Intel, and CUDA on Nvidia), then run pip install -r requirements.txt. You can also install via comfy-cli with pip install comfy-cli followed by comfy install. For anyone without the hardware, Comfy Cloud is the official paid hosted version.
Core Capabilities
- ✓A visual node graph — essentially visual programming for AI pipelines — for building image, video, audio, and 3D workflows without writing code, with reusable subgraphs and shareable workflow templates.
- ✓App Mode turns a finished node graph into a simple form-based UI, so the same workflow can be built by one person and run by someone else.
- ✓Local execution features: asynchronous queueing, partial graph re-execution, and what the README calls smart VRAM and RAM management, including model offloading and support for quantized models.
- ✓Loads full checkpoints or separate model components — diffusion models, VAEs, text encoders, LoRAs, ControlNets, adapters, and upscalers — so a workflow can mix and swap individual pieces.
- ✓Built-in tools for inpainting, outpainting, reference conditioning, masking and compositing, model merging, upscaling, frame interpolation, segmentation, and depth estimation.
- ✓Workflows save and load as JSON, and ComfyUI can recover a full workflow and its seed straight from a generated image or video that still carries that metadata.
- ✓Runs fully offline by default — the core doesn't download anything unless you ask it to — and --disable-api-nodes forces every built-in function to stay offline by disabling the optional paid Comfy API nodes.
- ✓Extensible through custom nodes, and optional API nodes reach closed-source models like Nano Banana, Seedance, and Hunyuan3D alongside the natively supported open-source models; a local API endpoint lets other applications call a finished workflow directly.
Strengths
- ✓Full visibility into every step of a generation pipeline — you see and can change the sampler, model, and each post-processing node instead of trusting a black-box prompt.
- ✓App Mode bridges the gap between pipeline builders and end users: build once as a graph, run repeatedly as a simple form.
- ✓Broad GPU support in one project — NVIDIA, AMD, Intel, Apple Silicon, and Ascend NPUs are all documented install paths, not an Nvidia-only tool.
- ✓Genuinely offline-capable: nothing downloads without being asked, and --disable-api-nodes gives a hard guarantee that only local, built-in functionality runs.
- ✓Workflows are portable JSON files, and finished media can carry its own workflow and seed for later recovery — reproducibility is built into the file format, not bolted on.
Current Considerations
- △The node graph is the whole interface — there's no simple single-prompt mode in core ComfyUI, so new users face real setup and a learning curve before they generate anything.
- △The Windows portable build is explicitly not recommended for regular users per the README; everyday users are steered to the desktop app instead.
- △Manual installs are GPU- and driver-sensitive: the README calls out separate pytorch builds for AMD ROCm, Intel XPU, and different Nvidia CUDA versions depending on GPU generation, and recommends updating pytorch if it's more than 6 months old.
- △Commits outside the stable release tags can be unstable and break custom nodes, per the README's own release-process notes.
- △Full offline use requires knowing to pass --disable-api-nodes; without it, the optional paid API nodes for closed-source models remain part of the default setup.
- △Licensed under GPL-3.0, which is more restrictive for downstream commercial redistribution than a permissive MIT/Apache license.
Choosing an AI Workflow Tool
Common Questions
ComfyUI is a node-based interface for running diffusion models — you build image, video, audio, and 3D generation pipelines by connecting nodes for models, samplers, and post-processing instead of using a single prompt box.
ComfyUI installs as a desktop application on Windows and macOS (the README's recommended path for new users), as a Windows portable package, via comfy-cli (pip install comfy-cli, then comfy install), or by cloning the repo for a manual install on Windows, Linux, or macOS.
ComfyUI natively supports current open-source diffusion models for image, video, audio, and 3D generation, and its optional API nodes add access to closed-source models such as Nano Banana, Seedance, and Hunyuan3D, per the README.
ComfyUI can run completely offline: the core doesn't download anything unless requested, and --disable-api-nodes turns off the optional paid API nodes so everything stays local, per the README.
ComfyUI's manual install supports NVIDIA, AMD, and Intel GPUs, Apple Silicon (M1 through M4), and Ascend NPUs, according to the README; the Windows portable build specifically targets Nvidia 20-series GPUs and above, with a separate legacy build for 10-series and older cards.
ComfyUI is licensed under GPL-3.0, a copyleft license: if you distribute a modified version, you're required to release that modified source under the same license.
The problem it solves
Most Stable-Diffusion-era tools hide the generation pipeline behind a single prompt box, so when something in the middle — a sampler, a LoRA, an upscale pass — needs adjusting, you're stuck with whatever the app's author decided, or you switch tools entirely. ComfyUI solves this by exposing the whole pipeline as a graph of nodes you wire yourself, and App Mode lets that same graph be repackaged as a simple form once it's built, so the trade-off between control and simplicity becomes a setting, not a different application.
Best use cases
- •Building a custom image or video generation pipeline that chains a specific sampler, LoRA, and upscaler, then saving it as a reusable workflow template.
- •Running a finished workflow behind a simple form via App Mode so a non-technical teammate can generate output without touching the node graph.
- •Integrating generation into another application through ComfyUI's local API endpoint instead of building a UI from scratch.
- •Working entirely offline with open-source models when a project can't send data to a hosted API.
- •Recovering the exact workflow and seed used to produce a past image or video by loading that file back into ComfyUI.
Related repositories
Is ComfyUI worth your time?
ChatGPT, Claude and Perplexity can all read this page. Ask one of them what it makes of ComfyUI.