Fooocus 2026: The Complete Guide to AI Image Generation

Quick navigation: What is Fooocus · Specs · Install · First image · Presets and settings · Prompt weights · Image Prompt modes · Upscale or Variation · LoRAs · Inpainting · Best checkpoints · Cloud and Colab · Fooocus vs alternatives · Troubleshooting · FAQ

Fooocus turned five in 2025 and is still the most accessible Stable Diffusion frontend for creators who want results without the ComfyUI node maze. This guide is the long-form answer to every Fooocus question we get from our community: installation, prompting, presets, Image Prompt modes, LoRAs, inpainting, checkpoints, cloud setups, and how it compares to alternatives in 2026.

If you want to jump to action, the table of contents above links to every section. Otherwise, read top to bottom. Each section adds context the next one builds on, and each one hands off to a dedicated guide when you need the full walkthrough.

What Is Fooocus and Why It Still Matters in 2026

Fooocus is an open-source image-generation interface built on top of Stable Diffusion XL that gives you a Midjourney-like single prompt box on your own hardware. It was created by lllyasviel, the same researcher behind ControlNet and Forge, and it hides samplers, schedulers, and refiner settings behind presets so a beginner gets a good image on the first try. An Advanced checkbox exposes the full controls when you need them.

In 2026, with image models getting larger (FLUX.2, Qwen-Image, SD 3.5 Large), the temptation is to assume Fooocus is obsolete. It is not. Three reasons it remains popular:

1. Zero-config quality. Fooocus ships with smart presets (Quality, Speed, Realistic, Anime). New users get good output on day one without learning prompt engineering or schedulers.
2. Lightweight. It runs on 4-8 GB VRAM. Newer models like FLUX.2 dev need 19+ GB and are unusable for most creators on consumer GPUs.
3. Stable and predictable. The project is in limited long-term support: bug fixes ship, the interface does not change under you, and the SDXL ecosystem of checkpoints and LoRAs it runs is the largest in existence.

One thing to know upfront: the official repository describes Fooocus as being in limited long-term support, bug fixes only, with no current plans to adopt newer model architectures. That is a feature for a creator who wants a tool that keeps working, and a limitation for anyone who needs Flux-class models locally. We cover the alternatives for that case in the comparison section.

If you want photorealism on a 3060 or M-series MacBook without dealing with WebUI extensions or ComfyUI graph debugging, Fooocus is still the right answer. For the hands-on version of this guide, install to first image, read how to use Fooocus.

Quick specs: Stack: SDXL (default) + custom samplers and refiners | Min VRAM: 4 GB (with optimization) | Recommended: 8 GB | License: GPLv3 | OS: Windows / Linux / macOS (Apple Silicon)
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How to Install Fooocus in 2026

The fastest install is the Windows release zip: extract it, run run.bat, and Fooocus installs its own Python environment and downloads the default SDXL models on first launch. The basic install path on other platforms is git clone plus a Python virtual environment, and a few things matter in 2026:

• Use Python 3.10 or 3.11. Python 3.12+ has compatibility issues with some dependencies.
• On macOS Apple Silicon, the install runs through MPS but inference is significantly slower than CUDA. Practical use case: testing or 1-2 generations at a time.
• The default SDXL checkpoint and refiner total roughly 8 GB. Fooocus fetches them automatically on first run, so budget the disk space and the download time rather than hunting for files.

Hardware you need

The official minimums are 4 GB of NVIDIA VRAM and 8 GB of system RAM for RTX 20/30/40-series cards. GTX 10-series cards are listed at 8 GB VRAM, with 6 GB marked as uncertain.

Install by platform

The first launch stalls on purpose while the models download. Watch the terminal and do not close the window. Once the browser tab opens, you are done: the setup is unattended from there.

We have a step-by-step Fooocus installation guide for first-time users. If you are setting up SDXL specifically (not just Fooocus presets), see installing SDXL models in ComfyUI: the model files are interchangeable between the two tools.

Bottom line: 30 minutes of setup, then unattended for years. The friction point is downloading models, not Fooocus itself.

Your First Image: Prompt Anatomy

A working Fooocus prompt has a subject, a few style words, and nothing else, because the preset appends quality terms for you. The four parts of a complete prompt:

Fooocus appends quality boosters automatically when you pick a preset (Quality, Realistic, etc.), so you don't need them in the user prompt. Beginners over-prompt: if a phrase doesn't change anything visually, remove it. A good first prompt:

portrait of a woman in a rain jacket, city street at night, neon reflections, 85mm lens

Leave the negative prompt empty on your first run. Fooocus applies its own prompt expansion (the "Fooocus V2" style, a GPT-2-based expander) so short prompts still produce detailed images. To see exactly what was sent to the model, open log.html in the dated outputs folder: it records the expanded prompt, seed, styles, and every setting for each image, which makes it the easiest way to reproduce a result weeks later.

Read The Ultimate Guide to Fooocus Image Prompts for the documented prompt syntax, the four Image Prompt modes, and copyable prompt patterns organized by goal.

Performance Presets and the Settings That Matter

Five controls account for almost every difference in Fooocus output, and all of them live behind the Advanced checkbox under the prompt.

Two more live under the Advanced tab. Guidance Scale sets how literally the prompt is followed; the default works for most subjects, and a small increase helps when the image ignores your prompt. Image Sharpness should go up for crisp product shots and down for soft portraits. Change one at a time with a fixed seed so you can see what each does.

Presets explained

The launch presets change the model and styles; the Performance setting changes speed versus detail. They combine freely: a Realistic launch at Speed for drafts, then Quality for the final.

Styles

Styles are curated prompt and negative-prompt bundles under Advanced → Style. They stack, and a few well-chosen ones beat ten. "Fooocus V2" is the entry that enables prompt expansion; unticking it stops the GPT-2 expansion, but any other selected style still adds its own text, so untick those too when you want fully literal control over the prompt.

Mastering Prompt Weights and Style

Once basic prompts work, weights are the next lever, and Fooocus uses the standard SDXL weight syntax so prompts from other Stable Diffusion tools carry over unchanged:

• (keyword) adds emphasis
• (keyword:1.5) sets an explicit weight, here 50 percent stronger
• [keyword] reduces emphasis

Practical example:

portrait of a woman, (cinematic lighting:1.4), (sharp focus:1.2), [oversaturated]

This says: render a portrait, push cinematic lighting strongly, push sharpness moderately, reduce saturation slightly. Weights above roughly 1.5 tend to distort the image, so push one or two terms, not the whole prompt. Fooocus uses the Automatic1111 reweighting algorithm, so weights behave the way A1111 users expect, and embeddings load as (embedding:file_name:1.1).

Two more documented syntax features are worth knowing. Wildcards such as __color__ flower pull a random entry from wildcards/color.txt on each generation, which is the built-in way to batch variations. Negative prompts live under Advanced → Negative Prompt and, with the presets doing the heavy lifting, are for specific exclusions rather than paragraph-length incantations.

Our deeper guide on varying prompt weights with Stable Diffusion walks through advanced patterns including attention ramping and BREAK syntax.

Image Prompt: Reference Images That Steer Generation

Image Prompt is a dedicated input mode (Input Image → Image Prompt) that feeds reference images into generation alongside your text, and it is the feature that most separates Fooocus from a plain prompt box. Fooocus augments IP-Adapter with its own negative embedding, attention modifications, and adaptive weighting, which is why reference images and text work together here instead of the image drowning out the text. Each image slot has a mode under Advanced:

Each slot has two sliders. Weight sets how much the reference contributes relative to the text and other references: raise it when the reference is ignored, lower it when outputs look like clones. Stop At sets how far through generation the reference stays active (0 to 1); lowering it loosens the grip of the reference, and it is the first move when PyraCanny output feels rigid. Fooocus supports multiple image inputs without quality loss, so a common combination is one PyraCanny image for pose plus one ImagePrompt image for style.

The full breakdown of modes, sliders, and prompt patterns is in The Ultimate Guide to Fooocus Image Prompts.

Upscale or Variation, and Describe

The Upscale or Variation tab under Input Image is the fastest way to iterate on a good image without re-rolling the seed. Vary (Subtle) keeps the composition and changes small details, Vary (Strong) reinterprets the image more freely, and the Upscale options enlarge the image while adding detail. The efficient workflow is to generate at the default size, pick the best candidate, then upscale only that one.

The Describe tab does the reverse: upload an image and Fooocus writes a prompt for it, with separate modes for photographs and anime. It is the quickest way to reverse-engineer a look you want to reproduce, and it pairs well with Image Prompt for composition control.

LoRAs in Fooocus

LoRAs (Low-Rank Adaptations) are small fine-tunes, a few hundred megabytes at most, that add a specific style, character, or concept to your base model, and Fooocus supports up to 5 LoRAs simultaneously. They are one of the strongest reasons to run Stable Diffusion locally rather than use a hosted generator.

Common LoRA categories:

• Style LoRAs: anime, oil painting, watercolor
• Character LoRAs: specific people or fictional characters
• Concept LoRAs: specific objects, clothing, poses
• Detail LoRAs: add detail/texture (Detail Tweaker, FaceDetail)

Where to find them: Civitai is the largest catalog; filter for LoRA and SDXL, because Fooocus runs SDXL and its derivatives only. Hugging Face has more permissive-license alternatives.

Folder, selection, and weights

1. Drop the .safetensors file into models/loras inside your Fooocus installation (not models/checkpoints, or it appears in the wrong dropdown).
2. Tick Advanced, open the Model tab, and pick the LoRA in one of the five slots. Use "Refresh All Files" if a new file is not listed.
3. Set a weight. No <lora:name:0.8> prompt syntax is needed; that belongs to Automatic1111. If the LoRA has a trigger word, include it in the prompt.

Stacking

All selected LoRAs apply together, and combined weight is what usually wrecks an image rather than any single LoRA. Keep the total across active LoRAs near 1.0 to 1.5: one style LoRA at 0.8 plus one character LoRA at 0.6 behaves predictably, while four LoRAs at 1.0 each produce a muddy result no matter how good each is alone. Add them one at a time so a bad result can be attributed to a cause.

Step-by-step, including why a LoRA seems to do nothing: How to Add and Use LoRAs in Fooocus for Stable Diffusion.

Bottom line: Start with a single LoRA at weight 0.6-0.8. Stack only when each LoRA pulls a different dimension (style + detail, not style + style).

Inpainting Workflow

Inpainting lets you regenerate a specific region of an image, fixing a hand, replacing a background, or removing an object, and in Fooocus the Method dropdown is the setting that most often decides whether the result works. Fooocus's inpainting got significantly stronger after 2.4.

The Fooocus inpainting workflow:

1. Generate or upload an image
2. Tick Input Image and open the Inpaint or Outpaint tab
3. Paint a mask over the region to regenerate
4. Choose the Method: Improve Detail, Modify Content, or Remove Object
5. Write a prompt describing what should be inside the mask (Remove Object ignores it)
6. Hit Generate

If you mask a region, describe something new, and get back a subtly cleaner version of the original, you are on Improve Detail and want Modify Content.

Denoise strength and mask size

Inpaint Denoising Strength, behind Developer Debug Mode in the Inpainting tab, controls how much of the original pixels survive:

Common gotcha: if your mask is too small, the model has too little context. If too large, it regenerates content you wanted to keep. The sweet spot is roughly 30% larger than the visible defect, and Mask Erode or Dilate adjusts it numerically after painting. Outpainting works from the same tab: tick one or more directions (Left, Right, Top, Bottom) and describe the scene continuation rather than the subject.

Full tutorial: Fooocus Inpainting Tutorial covers Respective Field, engine versions, Disable Initial Latent, mixing Image Prompt with inpaint, the multi-pass workflow, and seam fixes.

Best Checkpoints to Load

For photorealism in Fooocus, use Juggernaut XL or RealVisXL; for anime, AAM XL AnimeMix; and if you do not want to choose, the run_realistic.bat and run_anime.bat launch presets download a strong default for you. Any SDXL checkpoint works, and the files are interchangeable with ComfyUI.

To load a custom model, download the .safetensors file from Civitai or Hugging Face, drop it into Fooocus/models/checkpoints/, then pick it under Advanced → Model. Fooocus's defaults (sampler, refiner, styles) are tuned to just work, so you rarely need to touch anything else. Match the checkpoint to the job: inpainting and upscaling use whatever checkpoint is selected, so a realistic photo edited with an anime checkpoint will show the mismatch.

Our full picks with prompt-style notes: Best Fooocus Models and Checkpoints and, for the wider SDXL landscape including Illustrious and Pony families, Best SDXL Models in 2026.

Cloud and Colab Options

Most creators eventually hit hardware limits, particularly on M-series Macs or older NVIDIA cards, and there are three cloud paths in 2026:

• Google Colab: the free tier got tighter, but Colab Pro ($10/mo) gives reliable T4 access. The official notebook runs Fooocus in your browser: fooocus_colab.ipynb. Free sessions are limited, so save outputs regularly, and LoRAs have to be fetched into the session's models/loras each time because that storage does not persist.
• RunPod: ~$0.30/hr for an RTX 4090, billed per second. Best for sporadic heavy work.
• Replicate / Modal / Fal: managed inference. You don't run Fooocus, you call an API.

If you have a working local setup but need occasional throughput bursts, RunPod is usually the cheapest option. Replicate-style API services are better when you want to integrate Fooocus into a product, not a creative workflow.

Fooocus vs Alternatives

Fooocus is the right choice when you want good SDXL images with the least setup and no node graphs; ComfyUI wins once you need multi-stage pipelines or the newest model families. The 2026 landscape:

Fooocus vs ComfyUI vs Automatic1111 vs Forge

For the deeper teardown, read Fooocus vs ComfyUI vs Automatic1111. If Fooocus feels too restrictive, the ComfyUI 2026 complete guide is where to start, and our AI image generators comparison covers the hosted tools if you would rather not run anything locally. On the model question itself, SDXL vs Flux in 2026 lays out what you give up and gain by staying on SDXL.

Bottom line: Fooocus stays in the top 3 in 2026 for users who want quality without complexity. ComfyUI wins on custom workflows. FLUX-native tools win on raw quality if you have the VRAM.

Who Should Use Fooocus

You should try Fooocus if:

• You have a 6-12 GB VRAM GPU (or M-series Mac for testing)
• You want SDXL-quality output without learning ComfyUI
• You generate < 100 images/week and don't need fine-grained control
• You care more about "good prompt → good image" than custom pipelines

You should skip Fooocus if:

• You need controlled multi-stage workflows (use ComfyUI)
• You need FLUX.2 / Qwen-Image quality (use cloud or 24+ GB GPU)
• You want a commercial-license enterprise tool (use Stability's hosted API)

Troubleshooting

Most Fooocus problems come down to VRAM, an unticked checkbox, or a preset mismatch, and the table below covers the ones we see most.

Frequently Asked Questions

Is Fooocus still being maintained in 2026?

Yes, in limited long-term support. The official repository states that Fooocus receives bug fixes but has no current plans to adopt newer model architectures. It remains a reliable way to run SDXL-class generation locally, but new features are not where the project is heading.

Can Fooocus run on a Mac?

Yes, on Apple Silicon (M1 / M2 / M3 / M4). It uses MPS for inference, and each image takes several times longer than on a mid-range NVIDIA card. Practical for testing and small batches, slow for batch work. CPU-only Macs are not recommended.

How much VRAM do I need for Fooocus?

Minimum 4 GB with optimization flags. Recommended 8 GB. With 12 GB+ you can run SDXL refiner stages comfortably and stack 3+ LoRAs.

Does Fooocus support FLUX or SD 3.5?

The default Fooocus install does not. The base codebase is SDXL-targeted, and the project has no current plans to add newer architectures. Community forks experiment with FLUX support but are not production-ready as of 2026; ComfyUI is the practical route to those models.

Is Fooocus free for commercial use?

The Fooocus codebase is GPLv3. Models are licensed separately: SDXL base is OpenRAIL-M (commercial use allowed with restrictions). Always check the license of the specific model file you load.

Why are my Fooocus images blurry / low-quality?

Three common causes:

1. Wrong preset for the subject (use "Realistic" for photos, "Quality" for art)
2. Underweight prompt: add (detailed:1.3) or use a Detail LoRA
3. Resolution mismatch: SDXL is trained at 1024x1024; deviating significantly reduces quality

Can I use Fooocus to inpaint an existing photo?

Yes. Tick Input Image, open the Inpaint or Outpaint tab, paint the mask, choose Improve Detail, Modify Content, or Remove Object, and set denoise strength to 0.5-0.7 for detail work or 0.8-1.0 for new content. See our Fooocus inpainting tutorial.

Where do I find good prompts to copy?

Civitai's Images section shows full prompts on every uploaded image. Filter by SDXL and the style you want. Our Ultimate Guide to Fooocus Image Prompts has copyable prompt patterns by goal, and the PromptZone prompt directory has tested prompts across image and text models.

What is the easiest way to install Fooocus?

On Windows, download the release zip from GitHub, extract it, and double-click run.bat. It installs its own Python environment and downloads the default models on first launch, so there is nothing else to configure.

Where are my generated images saved?

In the outputs folder inside your Fooocus directory, organized by date, alongside a log.html file that records the prompt, expanded prompt, seed, and settings for every image.

How many LoRAs can I use at once in Fooocus?

Five. Keep the combined weight near 1.0 to 1.5 rather than filling every slot at full strength, and add them one at a time so you can tell which one caused a change.

What is the difference between PyraCanny and CPDS?

Both control structure from a reference image. PyraCanny extracts multi-resolution edges and is precise, best for exact poses. CPDS extracts looser structure with a fast preprocessor that needs no separate model download. Start with CPDS for speed, switch to PyraCanny when you need exactness.

Which checkpoint should I use in Fooocus for realistic photos?

Juggernaut XL is the default recommendation for photorealism, with RealVisXL as a close second that is often better for product shots. Launching run_realistic.bat gives you a strong realistic default without downloading anything by hand.

The Short Take

Fooocus is the right Stable Diffusion frontend in 2026 for most creators. It is fast to install, forgiving of beginner mistakes, and produces output competitive with much heavier setups. ComfyUI overtakes it once you need pipeline control or Flux-class models. FLUX overtakes it once you have 24 GB+ VRAM. Until then, Fooocus is the path of least resistance from "I want a good image" to "I have a good image."

If this guide helped, the deeper reads are linked above. If something is missing, a specific workflow, a Mac-only quirk, a niche LoRA stack, the most-asked questions usually become updates here.

Last reviewed and updated: September 2026.

Related guides on PromptZone

• Fooocus Presets Explained: Default, Anime, Realistic, SAI & LCM

Free tools for this

• AI Image Prompt Generator: Free Prompt Builder
• Negative Prompt Generator for Stable Diffusion