ComfyUI Review (2026): Free Node-Based UI for Stable Diffusion & Flux

ComfyUI does not generate images on its own — it needs a diffusion model loaded into it, such as Stable Diffusion, SDXL, SD 3.5, or Flux. ComfyUI's job is to load that model's weights, run inference on your own GPU, and expose every stage of that process (checkpoint loading, text-prompt encoding, sampling, VAE decoding, upscaling) as a separate, connectable node.

This puts ComfyUI in the same category as AUTOMATIC1111's Stable Diffusion WebUI, InvokeAI, and Fooocus: all four are front-end interfaces for the same underlying diffusion models, not competing models themselves. Where they differ is the interaction paradigm — AUTOMATIC1111 and Fooocus use conventional tabs, buttons, and sliders; ComfyUI uses a node graph.

ComfyUI was created by a developer known publicly as comfyanonymous, whose real name — Yannik Marek — became public through later interviews and podcast appearances. The project was first released on GitHub in January 2023. Marek was hired by Stability AI in June 2023, and that direct employment relationship ended by June 2024; on June 21, 2024, Comfy Org was formed as a dedicated organization with Marek as co-founder alongside other core ComfyUI developers, and the project's primary GitHub repository now lives under the Comfy-Org organization rather than Marek's personal account. Comfy Org joined the Linux Foundation's Open Model Initiative in August 2024.

ComfyUI's ecosystem has grown well beyond Stable Diffusion: as of September 2026 the project and its custom-node ecosystem support image models (Stable Diffusion, SDXL, SD 3.5, Flux.1 and Flux.2, Qwen-Image), video models (Wan, LTX-Video, HunyuanVideo), and audio and 3D generation nodes — verify the current supported-model list on the official ComfyUI GitHub repository before planning a specific workflow, since new model support ships frequently.

Every ComfyUI workflow is technically a directed acyclic graph (DAG): data flows in one direction from node to node with no loops. A basic text-to-image workflow typically chains a checkpoint loader, a text (CLIP) encoder for the positive and negative prompt, a sampler (KSampler) that runs the actual diffusion steps, and a VAE decoder that turns the result into a viewable image — four to six nodes for the simplest case, though real workflows commonly grow to dozens of nodes once upscaling, ControlNet guidance, or multiple models are added.

This transparency is the main reason power users choose ComfyUI over AUTOMATIC1111 or Fooocus: because every step is a visible node, you can insert a face-restoration pass between sampling and output, swap in a different sampler mid-pipeline, or branch the same prompt into two different upscalers to compare results — none of which is possible in a UI that only exposes a fixed set of top-level settings.

Workflows are saved and shared as plain JSON files that fully describe every node and connection. This is why the ComfyUI community shares complete, reproducible pipelines (not just prompts) for specific effects — a reader can load someone else's exported workflow file and reproduce their exact pipeline, only substituting their own prompt or input image.

The trade-off is real: building a workflow from scratch requires understanding what each node does and how diffusion sampling actually works, which is a materially steeper starting point than typing a prompt into a single text box. Most ComfyUI users start from a shared or built-in template workflow and modify it, rather than building a pipeline node-by-node from an empty canvas.

ComfyUI ships several installation paths depending on your platform and comfort level with the command line.

ComfyUI is released under the GNU General Public License version 3.0 (GPL-3.0), a copyleft open-source license. This means the software is free to download, run, modify, and redistribute — including for commercial purposes — with no revenue threshold and no registration step, unlike the Stability AI Community License that covers newer Stable Diffusion versions (see our Stable Diffusion review for that distinction).

GPL-3.0's copyleft condition matters mainly for developers, not for readers who just want to generate images: if you modify ComfyUI's core code and distribute that modified version, GPL-3.0 requires you to release your changes under the same license. According to a maintainer discussion on the official repository, custom nodes that extend ComfyUI through its plugin interface (living in the custom_nodes folder) are generally treated as separate works that can carry their own license — but a fork or direct modification of ComfyUI's own core code is a derivative work and must stay GPL-3.0. Verify the license of any specific custom node you install, since community-authored nodes are not covered by ComfyUI's own license and vary in terms.

ComfyUI's GPL-3.0 license says nothing about what you may do with the images you generate — that is governed entirely by the license of whichever diffusion model you load. Stable Diffusion 1.5, SD 2.1, and SDXL use the CreativeML Open RAIL-M / RAIL++-M license with no commercial revenue cap; SD 3 and SD 3.5 use the Stability AI Community License, free only under $1,000,000 in annual revenue; Flux.1 schnell is Apache 2.0 (unrestricted), while Flux.1 dev requires a separate commercial license from Black Forest Labs for commercial use. Running any of these models inside ComfyUI does not change or override their license terms.

Self-hosting ComfyUI is free — you pay only for your own hardware and electricity. The software itself, under its GPL-3.0 license, has no subscription, no revenue cap, and no registration requirement for local or offline use.

Comfy Org separately sells Comfy Cloud, a paid hosted-GPU service for readers who do not want to run their own hardware. As of the pricing published on comfy.org, Comfy Cloud offers a free tier with a limited number of GPU runs and no credit card required, then paid monthly subscriptions: Standard at $20/month (4,200 monthly credits, no custom-model imports), Creator at $35/month (7,400 monthly credits, custom-model imports included), Pro at $100/month (21,100 monthly credits, up to one-hour workflow runtime), and Team at $700/month (147,700 monthly credits, shared team access). Annual billing is offered at a discount on each tier. Comfy Cloud runs on hosted Blackwell RTX PRO 6000 GPUs with 96 GB VRAM, and GPU time is billed per second of active processing rather than per generation.

Comfy Cloud is a distinct commercial product from the free, self-hosted, open-source ComfyUI project — you never need it to use ComfyUI on your own GPU, and nothing in the GPL-3.0 license requires paying for it.

ComfyUI and AUTOMATIC1111's Stable Diffusion WebUI both run the same diffusion models on your own GPU and are both free and open-source, but they target different users through a fundamentally different interaction model.

ComfyUI earns its place as the power-user interface for local diffusion-model generation. Its node graph exposes every step of the pipeline — model loading, prompt encoding, sampling, upscaling — as a connectable, inspectable, and reproducible unit, which no tab-based UI can fully match. That transparency is also its main cost: readers who just want to type a prompt and get an image with minimal setup will find AUTOMATIC1111 or Fooocus faster to learn. ComfyUI itself is GPL-3.0 licensed and free to self-host with no revenue cap, and its VRAM needs are set entirely by whichever model you load — Stable Diffusion 1.5 on modest hardware, Flux at full precision on a high-end GPU. Comfy Org's Comfy Cloud is a legitimate option for readers who want the same node-graph workflow without owning a GPU, but it is a separate paid product, not a requirement. For readers who have outgrown a simple text-to-image box and want real pipeline control, ComfyUI is the reasonable next step; readers who have not reached that point yet should start with a simpler UI first.