Stable Diffusion WebUI vs ComfyUI: Compared
Quick Verdict
For beginners and casual image generation, Stable Diffusion WebUI (specifically the Forge fork) is easier to use — it has a straightforward form-based interface. For advanced users who want full control over their image generation pipeline, ComfyUI’s node-based workflow system is more powerful and flexible. ComfyUI is also significantly more memory-efficient.
Overview
These are the two dominant interfaces for running Stable Diffusion and other image generation models locally. Neither is a model itself — they’re frontends that let you use models like SDXL, Flux, and SD3.
Stable Diffusion WebUI (Forge) — AGPL-3.0 license, 161k stars (original A1111) + 12k stars (Forge fork). Originally created by AUTOMATIC1111, now most actively developed as “Forge” by lllyasviel. Form-based Gradio UI. Latest: Forge actively maintained (February 2026).
ComfyUI — GPL-3.0 license, 104k GitHub stars. Created by comfyanonymous. Node/graph-based workflow interface. Weekly releases. Extremely active development (February 2026).
A note on forks: The original AUTOMATIC1111 WebUI is still maintained but development has slowed. Forge is the recommended fork — it adds better memory management, Flux model support, and a modernized Gradio 4 interface while maintaining compatibility with existing A1111 extensions. This article compares Forge (as the active A1111 successor) vs ComfyUI.
Feature Comparison
| Feature | SD WebUI (Forge) | ComfyUI |
|---|---|---|
| Interface style | Form-based (Gradio) | Node/graph-based |
| Learning curve | Low (fill form, click generate) | Medium-high (build workflow) |
| txt2img | Yes | Yes |
| img2img | Yes | Yes |
| Inpainting | Yes | Yes |
| Outpainting | Yes | Yes |
| ControlNet | Yes (built-in integration) | Yes (via nodes) |
| LoRA support | Yes | Yes |
| Embeddings | Yes | Yes |
| Upscaling | Yes (ESRGAN, SwinIR, etc.) | Yes |
| Batch processing | Yes | Yes |
| Prompt weighting | Yes | Yes |
| SDXL support | Yes | Yes |
| Flux support | Yes (Forge adds this) | Yes |
| SD3 support | Partial | Yes |
| Video generation | Limited | Yes (AnimateDiff, etc.) |
| Audio generation | No | Yes |
| Workflow saving/sharing | No (only settings) | Yes (shareable .json workflows) |
| Workflow marketplace | No | Yes (comfyui.org, OpenArt) |
| Extension/plugin system | Yes (A1111 extensions) | Yes (custom nodes) |
| API | Yes | Yes |
| Queue system | Basic | Async queue (only re-runs changed nodes) |
| Memory management | Good (Forge improved) | Excellent (1 GB VRAM minimum) |
| Default port | 7860 | 8188 |
| NVIDIA GPU | Yes (CUDA) | Yes (CUDA) |
| AMD GPU | Yes (limited) | Yes (ROCm) |
| Intel GPU | Yes (CPU mode) | Yes (XPU) |
| Apple Silicon | Yes | Yes (Metal) |
| CPU-only | Yes | Yes |
| Docker support | Community images | Community images |
| License | AGPL-3.0 | GPL-3.0 |
Installation Complexity
Neither has official Docker images — both are typically installed from source with Python virtual environments. Community Docker images exist but aren’t officially maintained.
SD WebUI (Forge):
git clone https://github.com/lllyasviel/stable-diffusion-webui-forge
cd stable-diffusion-webui-forge
# Windows:
webui.bat
# Linux:
./webui.shThe startup script automatically creates a venv, downloads dependencies, and launches. Place model files in models/Stable-diffusion/. First run downloads required components (~5 GB).
ComfyUI:
# Option 1: comfy-cli (recommended)
pip install comfy-cli
comfy install
# Option 2: Manual
git clone https://github.com/comfyanonymous/ComfyUI
cd ComfyUI
pip install -r requirements.txt
python main.pyPlace models in models/checkpoints/. ComfyUI also has a portable Windows build that requires no installation.
Both require a GPU for reasonable performance. CPU-only mode works but is extremely slow (minutes per image vs seconds).
Minimum hardware:
- NVIDIA GPU with 4+ GB VRAM (6-8 GB recommended for SDXL/Flux)
- 16 GB system RAM
- 20+ GB disk space (models are 2-7 GB each)
- ComfyUI can work with as little as 1 GB VRAM by offloading to system RAM (slower but functional)
Performance and Resource Usage
ComfyUI is significantly more memory-efficient. Its smart memory management automatically offloads models between GPU and system RAM. It can generate SDXL images on 4 GB VRAM GPUs that would fail in WebUI. The async queue system also means it only re-processes changed parts of a workflow — editing a prompt doesn’t re-load the model.
SD WebUI (Forge) improved memory management substantially over the original A1111, but ComfyUI still wins here. Forge handles Flux models well with BitsAndBytes quantization (NF4, GGUF), reducing an 11 GB model to ~4 GB.
For the same hardware, ComfyUI will generally be able to generate larger images and use larger models.
Community and Support
SD WebUI: The combined A1111 + Forge community is massive — 161k + 12k stars. The original A1111 extension ecosystem has thousands of extensions. Forge maintains compatibility with most of them. Enormous amount of tutorials, guides, and YouTube content available.
ComfyUI: 104k stars with explosive growth. The workflow-sharing ecosystem is unique — people share complex pipelines as portable .json files. ComfyUI Manager makes installing custom nodes trivial. Growing ecosystem of tutorials, though still smaller than A1111’s.
Both have very active communities. A1111/Forge has more legacy content; ComfyUI’s community is growing faster.
Use Cases
Choose SD WebUI (Forge) If…
- You’re new to AI image generation
- You want a simple form: type prompt, click generate
- You want the easiest path to generating images
- You have a large collection of A1111 extensions you rely on
- You prefer a traditional UI over node-based workflows
- You want ControlNet integrated into a clean interface
Choose ComfyUI If…
- You want full control over the image generation pipeline
- You need maximum memory efficiency (limited VRAM)
- You want to create and share reproducible workflows
- You work with video generation (AnimateDiff)
- You want to experiment with cutting-edge models quickly
- You want async queuing and incremental re-processing
- You enjoy building visual node graphs
Final Verdict
ComfyUI is the more powerful and efficient choice. Its node-based system is intimidating at first, but it gives you control that form-based interfaces simply can’t match. The ability to save, share, and modify workflows as JSON files makes complex pipelines portable and reproducible. Memory efficiency means it runs better on the same hardware.
SD WebUI (Forge) is the easier choice for quick image generation. If you just want to type a prompt and get an image, Forge delivers with less friction. The form-based interface is intuitive for anyone. It’s the better entry point for AI image generation.
If you’re getting started: try Forge first, move to ComfyUI when you want more control. If you’re serious about AI image generation as a workflow: go straight to ComfyUI.
Related
Get self-hosting tips in your inbox
New guides, comparisons, and setup tutorials — delivered weekly. No spam.