RuinedFooocus vs Forge - Which Local UI Fits You in 2026?
RuinedFooocus and Stable Diffusion WebUI Forge both sit in the “run heavy image models on your own GPU” camp, but they are not the same product wearing different skins. RuinedFooocus is a Fooocus-heritage UI aimed at people who want a simplified front end while still reaching into newer model families the original Fooocus line did not prioritize. Forge is a Gradio WebUI fork in the Automatic1111 lineage, tuned for memory behavior and modern checkpoints, with a huge pile of extensions and scripts that grew up around that ecosystem. This page compares them the way a tinkerer would: install paths, where each UI breaks, what “uncensored locally” actually means technically, and which stack earns disk space if you only keep one. We cite the public GitHub homes - Runew0lf/RuinedFooocus and lllyasviel/stable-diffusion-webui-forge - so you can verify release assets yourself instead of trusting repack sites.
The Quick Answer
Key Takeaway - 2026
- RuinedFooocus: Pick this when you want a Fooocus-like prompt-and-go loop, automatic encoder downloads for some supported stacks, and community extras like merge tooling - at the cost of tracking a fork that may lag upstream Fooocus polish on certain quality-of-life features.
- Forge: Pick this when you want the Gradio WebUI pattern (tabs, extensions, scripts) with maintainers focused on performance and newer model paths - plan on reading the README’s CUDA + PyTorch package matrix before you grab a one-click archive.
- Or use LocalForge AI as a packaged option if you want Forge-class behavior without hand-assembling Python - listed last, next to DIY GitHub installs.
“Uncensored” here means local control: you choose weights and prompts; there is no remote classifier in the default loop. You still owe clean licensing and ethical use.
Comparison table
| Topic | RuinedFooocus | Forge |
|---|---|---|
| Lineage | Fooocus-style simplified UI (fork) | Automatic1111-style Gradio WebUI (fork) |
| Typical Windows path | Extract release, run run.bat per project wiki |
Extract one-click build or git clone per README |
| Extension universe | Smaller, fork-specific | Large A1111/Forge extension compatibility story |
| Learning curve | Lower if you want fewer tabs | Medium if you want every knob |
| Best when | You like minimal UI + bundled conveniences | You like scriptability + classic WebUI muscle memory |
Verify disk and VRAM guidance on the wiki or README you are using today - hardware advice from last year goes stale fast.
What RuinedFooocus actually is
RuinedFooocus lives on GitHub under Runew0lf/RuinedFooocus. Install docs on the project wiki describe extracting a packaged release and launching with run.bat on Windows, with notes about model folders and optional pre-seeding checkpoints to skip first-run downloads. The pitch is familiar to Fooocus refugees: fewer exposed settings, quicker iteration for people who do not want a node graph.
Tradeoffs show up in maintenance. Forks can be brilliant and still miss specific upstream niceties - automatic masking, certain enhancer flows, or bleeding-edge UI polish - depending on release timing. Treat forum screenshots as hints, not contracts.
What Forge actually is
Forge’s home is lllyasviel/stable-diffusion-webui-forge. The README advertises one-click bundles pairing specific CUDA and PyTorch builds; picking the wrong archive for your driver stack is a classic thirty-minute detour. Once running, you get the tabbed WebUI world: checkpoints, LoRAs, extensions, and community scripts.
Forge is the fork we point readers to when “Automatic1111 vs modern memory behavior” debates appear. Your card still sets the ceiling - 8 GB versus 12 GB versus 24 GB is the difference between comfortable SDXL-class work and constantly quantizing - but the UI layer matters for how often you fight defaults.
VRAM and model families (no fake numbers)
We are not publishing download counts or “official” VRAM tables that change weekly. Instead:
- Read the model card for the exact checkpoint you chose (SDXL, SD1.5, Flux-class, etc.).
- Start at a conservative resolution and raise it in 64-pixel steps until VRAM errors return.
- Enable med/low VRAM flags in Gradio stacks when the README documents them; do not treat flags as shameful - treat them as tools.
RuinedFooocus’s wiki mentions broad storage and RAM expectations; Forge’s issue threads discuss edge cases with specific GPUs. Use those primary sources.
Workflow fit: one image vs one hundred
If your day is “type prompt, iterate ten times, done,” RuinedFooocus’s simplified surface can feel faster than a tab farm you have not customized yet. If your day is “batch 200 variations with XYZ grids and scripted post,” Forge’s ecosystem is hard to beat.
Safety, privacy, and legality (short and blunt)
Local tools improve privacy versus cloud APIs because pixels do not leave your box by default. They do not grant immunity from law, consent norms, or platform policies on other sites. Generate privately, store responsibly, and keep minors and non-consensual content out of your pipeline - full stop.
Migration ideas
Many users keep both a minimal UI and a WebUI fork. Point them at different model folders or symlink with care. Never symlink until you understand default paths on disk - bad links produce silent “wrong VAE” bugs.
Troubleshooting you should expect anyway
Black outputs usually mean a VAE or precision mismatch - not “the UI is cursed.” Swap to a baked VAE build of the checkpoint or explicitly load the matching VAE file the model card names. Slow first launch is normal while Torch kernels compile; give the first run 10 to 20 minutes on a fresh install before you declare defeat. Antivirus false positives hit Python-based stacks constantly; if run.bat or webui-user.bat vanishes or gets quarantined, fix exclusions before reinstalling for the third time. Driver mismatches show up as cryptic CUDA errors; align your NVIDIA driver with the CUDA flavor advertised on the Forge archive you chose.
When neither UI is the answer
If you need reproducible graphs you can email as JSON, ComfyUI wins regardless of this comparison. If you want the absolute shallowest on-ramp with almost no tabs, stock Fooocus (not the fork) can still be the right call - this page only covers RuinedFooocus versus Forge. If you want cloud convenience, stop reading local guides; the tradeoffs reverse.
Folder layout mental model
Think in three buckets: checkpoints, small adapters (LoRA / embeddings), and VAE. If you copy files at random depth, the UI will start - but your outputs will look like wet cardboard. Forge follows WebUI conventions under models/ with recognizable subfolders; RuinedFooocus documents its own checkpoint paths on the wiki. When in doubt, search the repo for the string models in the README for the version you downloaded, not a random YouTube from 2024.
Extension economics
Forge inherits the extension habit: you can automate crops, send outputs to external editors, or chain ControlNet stacks without writing nodes - but each plugin is another failure point on updates. RuinedFooocus keeps the surface smaller, which means fewer moving parts and fewer midnight Git pulls, but also fewer one-click macros. If you love tinkering, Forge’s ecosystem pays rent. If you hate breaking changes, keep RuinedFooocus lean and resist feature creep. Keep a tiny written list of must-have plugins so updates do not blindside you during upgrades.
Who should use what
- Choose RuinedFooocus if you want Fooocus-like simplicity and the fork’s feature set matches the models you care about this month.
- Choose Forge if you want the Gradio extension world, scriptability, and maintainers focused on WebUI-class performance work.
- Choose LocalForge AI if you want Forge-style stacks without assembling CUDA choices yourself - one packaged path among several.
Release hygiene (both camps)
Before you declare a regression, diff your webui-user.bat / launch flags against a clean stock file from the same tag. Forks ship opinionated defaults; a stray --xformers toggle or an old venv folder can masquerade as a UI bug for hours.