AUTOMATIC1111 vs Forge
Forge is not a cloud service. It’s a fork of the same Stable Diffusion Web UI you already know—local install, open source, runs on your GPU. If someone told you otherwise, ignore them. Here’s the real split.
Feature Comparison
| Feature | Forge | AUTOMATIC1111 |
|---|---|---|
| Runs Locally | Yes | Yes |
| Open Source | Yes | Yes |
| NSFW Allowed | Yes | Yes |
| Type | Local / Offline | Local / Offline |
Quick Verdict — March 2026
Default pick: Forge if you want the A1111-style tabs with a newer inference stack tuned for harder SDXL-style runs. Stay on stock AUTOMATIC1111 only when you must have an extension or workflow that doesn’t play nice with Forge.
Pick Forge for speed and memory behavior on typical SDXL setups. Pick AUTOMATIC1111 for maximum extension compatibility and “it worked in my old video” reproducibility.
Side-by-side spec table
| AUTOMATIC1111 | Forge | |
|---|---|---|
| What it is | Original stable-diffusion-webui |
Fork: stable-diffusion-webui-forge — same Gradio idea, different backend work |
| Runs locally | Yes | Yes |
| Open source | Yes | Yes |
| UI | Tabs, prompts, extensions | Same layout DNA — muscle memory transfers |
| Extensions | Huge catalog | Most carry over; not 100% — test your must-haves |
| VRAM / SDXL | Fine with tuning; people push --medvram flags |
Designed around better SDXL-era behavior in practice for many users |
| Best for | Legacy workflows, rare extensions, tutorial matching | Day-to-day txt2img/img2img when you want the fork’s optimizations |
Where AUTOMATIC1111 wins
- Extension coverage: If your favorite extension is A1111-only, stock A1111 is the safe harbor.
- Tutorial matching: Old guides reference exact A1111 builds—seeds and details may not port 1:1 to any fork.
- “It still works”: When you don’t want to touch a working install, you don’t owe anyone an upgrade.
Where Forge wins
- Backend focus: Memory and speed work where SDXL actually hurts—that’s the point of the fork.
- Same habits: You’re not learning Comfy overnight. Prompt → generate stays familiar.
- Project claims: Forge’s own notes (see project discussions) describe meaningful SDXL gains on common VRAM tiers—verify on your GPU, but the intent is clear.
Setup compared
AUTOMATIC1111: Clone AUTOMATIC1111/stable-diffusion-webui, run the launcher, fight Python once, win forever (until the next dependency bump).
Forge: Clone lllyasviel/stable-diffusion-webui-forge instead—same dance, different repo. Point at your existing model folders with flags or symlinks so you don’t duplicate terabytes.
Hardware & performance
- Neither fixes a bad GPU. Both eat VRAM for breakfast if you pick the wrong resolution.
- Forge: Expect better headroom on SDXL-class work for many setups—not magic, just a different engine.
- Don’t trust random “75% faster” blog headlines. Benchmark your card with the same model and steps.
- Migrations bite: If your seed matches but the image doesn’t, you didn’t “fail”—engines differ. Lock sampler, scheduler, VAE, and prompts before you panic.
Who should use what
| AUTOMATIC1111 if you… | Forge if you… |
|---|---|
| Need one weird extension that breaks on the fork | Want SDXL-class runs without babysitting VRAM as hard |
| Replicate old screenshots from A1111 tutorials | Want A1111 muscle memory with a faster fork |
| Refuse to reinstall anything that works | Are OK re-testing extensions after a move |
Want zero install drama? LocalForge AI is another path—Forge-style stack without you herding dependencies.
About Forge
Performance-optimized fork of AUTOMATIC1111 with better VRAM handling. Runs models on 8GB cards that crash in A1111.
Full Forge profile →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 →