Stable Diffusion WebUI vs ComfyUI

Last reviewed Aug 26, 2026 · 608 words

Automatic1111 has more stars — 164,668 to ComfyUI's 129,995 — and less future. The star gap is history: A1111's Stable Diffusion WebUI launched in 2022 and was the interface for the first wave of local image generation, but its releases have slowed to a crawl while ComfyUI ships constantly and picked up support for Flux and video models alongside SD and SDXL. If you're choosing today rather than in 2023, the momentum question is already answered; what's left is whether you can stomach the interface.

Forms versus a node graph

A1111 gives you a Gradio page: prompt box, sliders, tabs for img2img, inpainting, upscaling. You can produce a good image in your first five minutes. ComfyUI gives you a blank canvas of nodes — loader, sampler, VAE decode, wired together — and your first five minutes are spent wondering where the prompt box went. The payoff is that the graph is the pipeline: two-pass workflows, regional conditioning, and multi-model chains that would need an A1111 extension (or be impossible) are just more nodes. Workflows also save as JSON and even embed inside generated PNGs, so reproducing someone else's exact pipeline means dragging their image onto the canvas. A1111's equivalent, PNG-info plus matching extension versions, works until it doesn't.

New models land in ComfyUI first

This is the practical dealbreaker. When a new architecture arrives — Flux was the clearest case — ComfyUI support appears in days because the project is alive and the node system absorbs new model types cleanly. A1111 support arrives late via forks and extensions, or never. The catalogue is polite about it ("infrequent releases lately"); the blunt version is that A1111 is in maintenance mode, and its huge extension ecosystem is aging with it. If your interest is keeping up with open-weight releases as a Midjourney replacement, that alone decides the matchup.

Same GPU, different mileage

Both list 8 GB minimum RAM and both really want a GPU. On identical hardware ComfyUI is the more frugal one — it only executes the parts of the graph that changed and manages VRAM aggressively, which in practice means larger models run on 8-12 GB cards that A1111 pushes into out-of-memory errors. Both are heavy Python installs; both run in Docker or bare metal. Neither belongs exposed to the internet without auth in front.

The honest cost: learning curve

ComfyUI's catalogue con is "steep learning curve" and it's real — expect an evening of tutorials before the graph stops feeling hostile, and expect community workflows that pull in ten custom node packs of varying quality. A1111's cost is the opposite kind: comfort now, dead ends later. Middle grounds exist — InvokeAI puts a polished canvas UI on top of similar internals — but the category has consolidated around ComfyUI as the power tool.

Decision table

What I'd do

Install ComfyUI and commit the one evening it takes to stop fighting the graph; load other people's workflow files and take them apart rather than building from scratch. I'd keep an existing A1111 install around for muscle-memory inpainting sessions if it already works, but I would not set up a new one in 2026 — the ecosystem's energy, the new models, and the VRAM headroom are all on the other side.