ComfyUI vs AUTOMATIC1111: Complete Comparison for 2025

The two dominant interfaces for Stable Diffusion are ComfyUI and AUTOMATIC1111 (including its Forge variant). Both are free, open-source, and powerful. But they serve different needs. I've used both extensively, and this comparison reflects real-world experience, not just feature lists.

Quick Answer: ComfyUI is better for advanced users who need workflow flexibility, video generation, and complex multi-model pipelines. AUTOMATIC1111/Forge is better for beginners who want a simpler interface and quick results. In 2025, ComfyUI has become the industry standard for serious creators, while A1111 remains excellent for straightforward image generation.

Quick Comparison Table

Interface Philosophy

ComfyUI: Node-Based Power

ComfyUI represents your generation process as a visual graph. Each node performs one operation: load a model, encode text, sample latents, decode to image. You connect nodes to build custom pipelines.

Advantages:

• See exactly what's happening at each step
• Modify any part of the pipeline
• Create complex workflows impossible in form-based UIs
• Save and share complete workflows

Disadvantages:

• Overwhelming for beginners
• Simple tasks require multiple nodes
• Takes time to understand node relationships

The visual nature of ComfyUI makes complex workflows manageable. You can see the entire generation pipeline, understand dependencies, and modify individual components without breaking the whole system.

AUTOMATIC1111: Form-Based Simplicity

A1111 presents options as form fields: prompt, negative prompt, steps, CFG, sampler. Enter values, click generate. Extensions add tabs for additional features.

Advantages:

• Immediately understandable
• Quick to generate simple images
• Familiar interface pattern
• Less cognitive overhead for basic use

Disadvantages:

• Complex workflows require multiple extensions
• Limited visibility into what's happening
• Harder to create novel pipelines

For straightforward text-to-image generation, A1111's simplicity is actually an advantage. You don't need to understand the underlying pipeline to get results.

Performance Comparison

Generation Speed

In my testing across multiple models and configurations:

SDXL (1024x1024, 30 steps):

• ComfyUI: ~22 seconds
• A1111: ~28 seconds
• Forge: ~24 seconds

Flux (1024x1024, 20 steps):

• ComfyUI: ~18 seconds
• A1111: ~25 seconds (with proper configuration)
• Forge: ~20 seconds

Why ComfyUI is often faster:

• Better graph optimization
• Automatic node caching
• More efficient memory management
• Only computes what's needed

The difference varies by workflow, but ComfyUI typically has a 10-20% speed advantage for equivalent operations.

VRAM Usage

Both have improved significantly, but efficiency varies:

ComfyUI advantages:

• Automatic model offloading
• Aggressive caching of computed tensors
• Better tile-based processing

Forge advantages:

• Optimizations specifically for A1111 workflows
• Improved attention mechanisms
• Better low-VRAM mode

Practical result: Both can run SDXL on 8GB VRAM cards. ComfyUI handles complex workflows on limited VRAM better due to finer control over model loading.

Feature Comparison

Text-to-Image

Both handle basic text-to-image excellently. Differences emerge in advanced use:

ComfyUI:

• Multiple prompt conditioning techniques
• Regional prompting through nodes
• Complex CLIP configurations
• Native attention manipulation

A1111/Forge:

• Simple prompt interface
• Extension-based regional prompting
• BREAK keyword support
• Familiar prompt syntax

Verdict: Equivalent for basic use, ComfyUI for advanced prompt manipulation.

Image-to-Image

ComfyUI:

• Fine control over denoise process
• Multiple img2img techniques through node selection
• Easy to chain multiple img2img passes
• Better for iterative refinement

A1111/Forge:

• Simpler interface for basic img2img
• Inpainting tab is intuitive
• Outpainting extensions available
• Less control but faster to use

Verdict: A1111 faster for simple img2img, ComfyUI better for complex iterative workflows.

ControlNet Integration

ComfyUI:

• Native node support
• Easy to stack multiple ControlNets
• Full control over application timing
• IP-Adapter and ControlNet combination is straightforward

A1111/Forge:

• Extension-based
• Multi-ControlNet tab
• Good interface for single/dual ControlNet
• Less flexible for complex setups

Verdict: Both excellent, ComfyUI better for stacking 3+ control mechanisms.

Video Generation

This is where ComfyUI dominates completely.

ComfyUI:

• Native support for LTX-2, Wan 2.2, AnimateDiff
• Video-specific nodes and workflows
• Frame interpolation, upscaling
• Audio synchronization (LTX-2)

A1111/Forge:

• AnimateDiff extension
• Limited video model support
• No native LTX-2 or Wan support
• Video is an afterthought

Verdict: ComfyUI is the only serious option for AI video generation.

LoRA and Model Management

ComfyUI:

• Load multiple LoRAs with separate nodes
• Precise strength control per LoRA
• Easy to A/B test different LoRA combinations
• Clear visualization of what's applied

A1111/Forge:

• LoRA syntax in prompt
• Stacking through comma separation
• XYZ grid for comparison testing
• Simpler for basic LoRA use

Verdict: A1111 simpler for basic use, ComfyUI better for complex LoRA stacking.

Learning Curve

Getting Started with ComfyUI

Week 1: Understanding nodes and connections. Learning basic workflows for txt2img.

Week 2: ControlNet, img2img, more complex prompting. Understanding model loading.

Week 3-4: Custom workflows, video generation, advanced techniques.

Time to competency: 2-4 weeks for comfortable daily use.

Getting Started with A1111

Day 1: Basic txt2img generation working.

Day 2-3: Extensions installed, ControlNet basics.

Week 1: Comfortable with main features.

Time to competency: 1-2 weeks for comfortable daily use.

The learning curve difference is significant. A1111 is approachable immediately. ComfyUI requires investment before payoff.

Extension Ecosystem

ComfyUI Extensions (Custom Nodes)

Installation: ComfyUI Manager makes this simple.

Popular extensions:

• Impact Pack (face restoration, detailing)
• WAS Node Suite (utilities)
• Efficiency Nodes (workflow optimization)
• Various model-specific nodes

Ecosystem status: Rapidly growing, becoming comprehensive.

A1111 Extensions

Installation: Extensions tab, one-click install.

Popular extensions:

• ControlNet
• ADetailer (face fixing)
• Deforum (animation)
• Multiple UI enhancements

Ecosystem status: Mature, extensive, well-documented.

Verdict: A1111 has more extensions currently, but ComfyUI's ecosystem is catching up rapidly and covers advanced use cases better.

Use Case Recommendations

Choose ComfyUI If:

1. You're doing video generation. LTX-2, Wan 2.2, and future video models live in ComfyUI.

2. You need complex workflows. Multi-model pipelines, conditional generation, iterative refinement.

3. You're creating production content. Batch processing, consistent outputs, repeatable workflows.

4. You want to understand the process. Node-based visualization teaches how generation works.

5. You're building AI influencer content. Character consistency workflows require ComfyUI's flexibility.

Choose A1111/Forge If:

1. You're just starting. The learning curve is much gentler.

2. You need quick simple outputs. Basic txt2img, img2img, inpainting.

3. You prefer form-based interfaces. Some people genuinely prefer traditional UI patterns.

4. You rely on specific A1111 extensions. Some capabilities only exist as A1111 extensions.

5. Time is limited. Getting results in A1111 is faster for simple tasks.

The Forge Factor

Forge is a performance-optimized fork of AUTOMATIC1111. It addresses many of A1111's weaknesses:

• Better VRAM management
• Faster generation
• Improved Flux support
• More modern architecture

Should you use Forge instead of original A1111?

Yes, if you choose the A1111 ecosystem. Forge provides meaningful improvements without changing the interface.

Migration Considerations

From A1111 to ComfyUI

What transfers easily:

• Models (checkpoints, LoRAs, embeddings)
• Prompts (though syntax differs)
• Knowledge of parameters

What doesn't transfer:

• A1111 extensions (need ComfyUI equivalents)
• Workflows (must rebuild in nodes)
• Interface muscle memory

Migration time: Expect 1-2 weeks to rebuild your common workflows in ComfyUI.

From ComfyUI to A1111

Rarely done. People who learn ComfyUI typically prefer its flexibility. The main reason to use A1111 after knowing ComfyUI is for specific extensions.

Real-World Workflow Comparison

Simple Portrait Generation

A1111 approach:

1. Enter prompt
2. Set parameters
3. Generate
4. Maybe use ADetailer

ComfyUI approach:

1. Load checkpoint node
2. CLIP encode prompt
3. Empty latent
4. KSampler
5. Decode
6. Save

Verdict: A1111 is simpler for this common task.

Character Consistency Across Images

A1111 approach:

1. Generate initial image
2. Use as reference with ControlNet
3. Manual iteration
4. Inconsistent results

ComfyUI approach:

1. IP-Adapter + Face ID workflow
2. Load reference image
3. Generate with consistency
4. Easy to batch multiple poses

Verdict: ComfyUI is significantly better for this professional use case.

Video Generation from Image

A1111 approach:

• Install AnimateDiff extension
• Limited results
• No modern video models

ComfyUI approach:

• Load LTX-2 or Wan 2.2
• Connect img2vid workflow
• Professional quality output
• Full control over motion

Verdict: ComfyUI is the only option for serious video work.

Community and Support

ComfyUI

• Active Discord community
• Regular updates
• Strong developer ecosystem
• Growing documentation

A1111

• Massive Reddit community
• Extensive documentation
• Years of troubleshooting posts
• Mature knowledge base

Verdict: A1111 has more beginner resources, ComfyUI has better advanced support.

Future Direction

Where ComfyUI is Heading

• Video generation focus: The future of AI generation is video, and ComfyUI leads here.
• Professional adoption: Studios and agencies are standardizing on ComfyUI.
• New model support: New models are released with ComfyUI nodes first.

Where A1111 is Heading

• Maintenance mode: Updates slower than historically.
• Forge as successor: Many consider Forge the future of this ecosystem.
• Stable but not leading: Reliable for current use, unclear for future features.

Frequently Asked Questions

Can I use both?

Yes. Many professionals use ComfyUI for complex work and A1111 for quick tests. They share model files.

Which has better Flux support?

ComfyUI has native, excellent Flux support. A1111/Forge requires configuration but works.

Is ComfyUI really harder?

Yes, initially. But the learning investment pays off for anyone doing serious work.

Should beginners start with A1111 then move to ComfyUI?

Reasonable approach, but you can also start with ComfyUI using pre-built workflows.

Which is more stable?

A1111 has fewer updates and breaking changes. ComfyUI updates frequently but rarely breaks existing workflows.

Can I convert A1111 workflows to ComfyUI?

Not directly. You rebuild workflows using equivalent nodes.

Which uses less disk space?

Similar when configured equivalently. Both need model files.

Is one more "professional"?

ComfyUI is increasingly the professional standard, especially for production work.

Will A1111 be deprecated?

Unlikely. It remains useful and has a large user base. Forge ensures the ecosystem continues.

Which should I learn for AI influencer creation?

ComfyUI. Character consistency and video generation require its capabilities.

Wrapping Up

Both tools are excellent for their intended purposes:

ComfyUI is the power tool. It requires learning but rewards that investment with unmatched flexibility. For video generation, complex workflows, and production work, it's the clear choice.

AUTOMATIC1111/Forge is the accessible tool. It gets you generating quickly with minimal learning. For simple image generation and users who prefer traditional interfaces, it remains excellent.

My recommendation for most users in 2025: Learn ComfyUI. The AI generation landscape is moving toward video and complex multi-model workflows. ComfyUI positions you for where the technology is going, not just where it's been.

For getting started with ComfyUI, see our ComfyUI beginner guide. For video generation specifically, check the LTX-2 guide.

If you want to skip local setup entirely, Apatero.com offers powerful generation without installing anything.