AUTOMATIC1111 vs ComfyUI
AUTOMATIC1111 and ComfyUI both run Stable Diffusion locally - they’re not “cloud vs local,” they’re form UI vs node graph. This page breaks down the real workflow differences so you pick the one you’ll actually keep using.
Feature Comparison
| Feature | AUTOMATIC1111 | ComfyUI |
|---|---|---|
| Runs Locally | Yes | Yes |
| Open Source | Yes | Yes |
| NSFW Allowed | Yes | Yes |
| Type | Local / Offline | Local / Offline |
Quick Verdict - March 2026
Pick AUTOMATIC1111 if you want a tabbed web UI, the biggest extension catalog, and the shortest path from install → prompt → image. Pick ComfyUI if you want a node graph you can save as JSON, reuse forever, and extend with custom nodes when new models and techniques land.
One line: AUTOMATIC1111 = fast iteration inside one app screen. ComfyUI = reproducible pipelines you can share like code.
Side-by-side spec table
| AUTOMATIC1111 (SD Web UI) | ComfyUI | |
|---|---|---|
| UI type | Classic web UI: tabs, fields, sliders | Node graph in the browser: wires between ops |
| Setup (typical) | Clone repo → webui-user.bat / webui.sh (or community installers) |
Portable build, manual venv, or Desktop beta - pick what matches your OS |
| VRAM | Depends on model + resolution; --medvram / --lowvram are first-line mitigations on tight GPUs |
Depends on model + how many nodes stay resident; big graphs cost more VRAM |
| Model support | SD 1.5 / SDXL / community checkpoints + LoRAs via the usual folders | Same model families; often where new techniques show up as nodes first |
| Best for | Prompt → generate → inpaint loops; extension-heavy workflows | Saved workflows, batch logic, multi-stage and video-style pipelines |
Where AUTOMATIC1111 wins
- Extension ecosystem: Huge library of one-click extensions - ControlNet, extra samplers, tooling - wired into the same UI you already learned.
- Familiar controls: Prompt, negative prompt, steps, CFG, sampler - same vocabulary as most tutorials online.
- Fast “tweak and regenerate”: Change a slider, hit generate - no rearranging a graph unless you want to.
- Inpainting / img2img loop: Strong fit when you’re refining one canvas without rebuilding a node network each time.
Where ComfyUI wins
- Workflow is a file: Export/import JSON, stash versions in git, share exact pipelines - your graph is the recipe.
- Composable pipelines: Branching, reroutes, and reusable subgraphs beat “one giant screen of settings” when the process gets long.
- Custom nodes: New techniques often land as node packs; you add what you need instead of waiting for a single monolithic release.
- Automation-friendly: Queue behavior and headless patterns fit “run this graph on 500 inputs” better than clicking through tabs.
Setup compared
AUTOMATIC1111: Install Python/Git (versions per project docs), clone stable-diffusion-webui, run the launcher script, let dependencies pull on first boot, drop checkpoints into the models folder. It’s the path most walkthroughs assume - expect troubleshooting GPU drivers and VRAM flags at least once on a new machine.
ComfyUI: Install route varies (portable vs venv). You’ll pick a startup script, point model folders, then learn the canvas - the first hour is graph topology, not prompts. ComfyUI Manager (community) is widely used for custom nodes - treat updates like any dependency stack: update when you need a fix, not randomly mid-project.
Hardware & performance
- Both care more about which checkpoint and resolution you pick than about the brand name of the UI.
- AUTOMATIC1111: Official troubleshooting docs reference low-VRAM modes (
--medvram,--lowvram) when you’re on smaller GPUs; SDXL-class models at high res is where people hit OOM first - plan headroom. - ComfyUI: Heavy graphs (multiple models, ControlNets, upscalers) stack memory pressure - watch VRAM as you add nodes, not just at the checkpoint loader.
- Speed claims vary by GPU, driver, and sampler - if someone quotes a single “% faster,” it’s usually a cherry-picked run. Benchmark your card with your workflow if it matters.
Who should use what
| AUTOMATIC1111 if you… | ComfyUI if you… |
|---|---|
| Want the shortest path to “prompt in, image out” with minimal graph thinking | Want saved workflows you can version, diff, and hand to teammates |
| Rely on extensions and community scripts inside one UI | Want node packs and custom ops when new models drop |
| Prefer tutorials that use tab vocabulary (txt2img, img2img, extras) | Prefer wiring loaders, samplers, and VAE decode explicitly |
| Mostly edit one image at a time in a tight loop | Run multi-step or repeatable pipelines (batch, video-style graphs, complex post) |
How to run it without the rabbit hole: install Forge or ComfyUI yourself, or use LocalForge AI if you want a pre-wired local stack with less manual setup.
About AUTOMATIC1111
The original Stable Diffusion web UI with 145k+ GitHub stars. Full-featured image generation frontend with extensions, LoRA support, and img2img.
Full AUTOMATIC1111 profile →About ComfyUI
Node-based Stable Diffusion frontend for power users. Visual workflow editor with full pipeline control and native Flux support.
Full ComfyUI profile →