ComfyUI
Build reusable image-generation graphs with explicit model and node dependencies.
- Starting price
- Free local node software
- Free access
- Free GPL-3.0 application
- Billing unit
- Hardware and optional API usage
- Platform
- Windows, Linux and Apple Silicon Mac
- Verified
- 20 Oct 2026
Overview
What you provide
- Load a workflow with the required models and supply prompts, images or conditioning inputs.
What you get
- ComfyUI executes connected model nodes to generate or transform images with reusable workflow definitions.
Choosing this tool
ComfyUI fits repeatable image pipelines where you need to expose model loading, conditioning and sampling as connected nodes. Invoke puts more emphasis on canvas editing; DiffusionBee reduces setup for a Mac user. Choose a graph only when its control is worth maintaining models and extensions.
A decision worked through
A saved graph can describe a 20-image run, but it is not a cost quotation. A fully local graph uses your hardware; substituting one paid API node changes the budget even if the graph file and image count look almost identical.
ComfyUI alternatives for this task
For ComfyUI, compare Invoke, DiffusionBee. Match the input, delivery format and operating responsibilities before comparing price.
| Product | Price / unit | Free allowance | Input → output | Key limit |
|---|---|---|---|---|
| ComfyUIRead profileOfficial source ↗ | GPL-3.0 runtime: free | Local generations use own hardware | Node graphs become image outputs. | Custom nodes require review. |
| InvokeRead profileOfficial source ↗ | Apache-2.0 self-hosted: free | No software generation allowance | Canvas edits become revised images. | API-only models add provider costs. |
| DiffusionBeeRead profileOfficial source ↗ | AGPL-3.0 GUI: free | No cloud-image quota in local mode | Prompts/masks become edited pictures. | Mac and model compatibility required. |
Setup & workflow
- Install a supported desktop or portable build using the official instructions.
- Place the required weights in the documented model folders and inspect the graph.
- Run a small example before increasing resolution or batch size.
Requirements & installation
- For manual installation follow the backend-specific PyTorch instructions, install requirements.txt, and launch python main.py after placing the required weights.
Limits & review
- Model checkpoints and extensions are not automatically supplied by a workflow file. Device support varies across CUDA, ROCm, XPU and Apple backends; an extension can execute code or contact an external service.
Your part
- Inspect imported nodes and verify the output and provenance before reusing a shared workflow.
Sources & verification4
This profile is based on official sources, not a hands-on product test.
Vendor descriptions and demos document advertised features. Editorial guidance is based on these sources.
- Official installation and device backendsgithub.com
- ComfyUI official referencegithub.com
- Invoke official referencegithub.com
- DiffusionBee official referencegithub.com
