Comfy logo

Comfy

Open-source AI workflow platform that gives creators detailed control over image and video generation, including local models.

Alternative to: Higgsfield
Comfy app screenshot

Short description

ComfyUI works very differently from Higgsfield. Instead of giving you a simple creative studio, it lets you build your own AI workflows using connected nodes.

Features

  • Node workflows: Connect different AI models and processing steps to build custom generation pipelines.

  • Local generation: Run models on your own computer instead of sending everything to a cloud service.

  • 60,000+ community nodes: Add functionality created by the community.

  • Model support: Run models such as Wan, FLUX, Kling, Seedance and others.

  • Camera control: Build workflows with detailed control over generated shots.

  • Reproducibility: Save workflows and recreate results later.

  • Custom models: Use LoRAs, checkpoints and other custom model components.

Pricing

  • Free: Open source

  • Local: Run locally using your own hardware

  • Comfy Cloud: Hosted options available

  • Model licensing: Varies by model

Integrations

  • MCP: Connect ComfyUI with AI agents.

  • API: Run ComfyUI workflows programmatically.

  • CLI: Control workflows from the command line.

  • Plugins: Extend ComfyUI with community-built functionality.

Platforms

  • Desktop (Win/Mac/Linux)
  • Comfy Cloud
  • Enterprise
❤️

What users love about Comfy

  • Open Source: Gives creators complete access to the underlying workflow system.

  • Local Generation: Lets users generate content without sending it to a hosted platform.

  • Privacy: Keeps sensitive assets and generations on local hardware.

  • Community: Large community creates models, nodes and ready-made workflows.

  • Workflow Control: Gives advanced users granular control over each generation step.

  • Reproducibility: Saved workflows make it easier to recreate successful results.

😕

What users complain about Comfy

  • Learning Curve: Difficult for beginners.

  • GPU Costs: GPU hardware can be expensive.

  • Setup: Setup and maintenance take time.

  • Compatibility: Model and node compatibility can become complicated.