Run ComfyUI in the Cloud – The Complete Guide - No Installation Required
Run ComfyUI in the Cloud – The Complete Guide - No Installation Required
Run ComfyUI in the Cloud – The Complete Guide - No Installation Required
ComfyUI is the lego for AI Art and Video generation. It breaks the process into blocks that you can snap together however you want.
Table of Contents
Introduction: What This Guide Covers & Who It’s For
What is ComfyUI?
ComfyUI is a visual programming language for generative AI, built around nodes and "noodles" that connect them. Each node represents a function that transforms inputs into outputs. By chaining nodes together, users create workflows that take inputs like prompts, images, models, and configurations to generate high-quality images and videos.
What makes ComfyUI so useful is its modularity and shareability. A user can spend a week designing a workflow and share it with a teammate, who can tweak inputs, swap out nodes, or refine the process without rebuilding from scratch.
These workflows can also be shared globally, enabling others to generate the same high-quality results in minutes. This level of flexibility and collaboration is unique to node-based systems. Unlike canvas- and prompt-based platforms like Midjourney and Adobe Firefly, which require users to manually redo the entire process each time, ComfyUI allows workflows to be reused, customized, and improved effortlessly - making it a game-changer for AI creativity.
What makes ComfyUI even more powerful is its rapidly growing ecosystem. Thousands of developers are actively building new nodes that integrate the latest models and techniques, unlocking advanced capabilities for generative AI workflows. Nodes can also connect to any API, including closed-source systems like RunwayML, Minimax, and Kling, or even leverage LLMs to automatically refine prompts. With limitless extensibility, ComfyUI is pushing the boundaries of what's possible in AI-powered content creation.
ComfyUI is the lego for AI Art and Video generation. It breaks the process into blocks that you can snap together however you want.
Each block (we call them nodes) handles a specific task: loading your model, processing your prompt, sampling your image, and more.
Launched on Github in Jan 2023, Comfyanonymous is credited as the creator of ComfyUI and a cofounder of Comfy Org. It's garnered massive success, and has changed the way AI Artists experiment and create.
ComfyUI – The Complete Guide to Node-Based Workflows
Who should use ComfyUI?
Both beginners who are looking for step-by-step guidance to advanced users that seek fine-grained control.
ComfyUI might look complex at first, but beginners can absolutely use it. Many beginners have picked up ComfyUI and found that it actually helps them understand AI image and video generation better, since it exposes what’s happening.
At the same time, ComfyUI is geared toward power users and tinkerers – those comfortable with technical tools who want greater control over their creations.
ComfyUI vs. Automatic1111 - Which one to use for AI Image & Video Generation?
| Automatic1111 | ComfyUI | |
|---|---|---|
| Interface - Ease of Use | Very user-friendly; the UI is quite straightforward with most features accessible, straight up as menu settings or buttons. | Steep learning curve and slightly complex UI for beginners. This is a node-graph interface which requires the setup of workflows before generating images/videos. |
| Customization | It has an extensive library of hundreds of plugins/extensions and hundreds of settings and configurations to customize the look and feel as well as advanced features for image and video generation and editing. | Extremely customizable. The overall design is modular. Users can modify or restructure virtually any aspect of the image and video generation. There is a large ecosystem of custom nodes that allows users to leverage the absolute bleeding edge in open source AI. |
| Performance | Good but not the fastest. A1111 is optimized for common use but can be slower and heavier on VRAM compared to other models. Multi-image batch generation is supported, but multi-GPU support is not native. | High performance. ComfyUI is optimized to reuse computations and manage memory smartly. Even on the same hardware, it often generates faster than A1111. Lacks built-in multi-GPU, but can utilize CPU for overflow. |
| Workflow Flexibility | Low to Medium: For standard workflows (txt2img, img2img, inpaint, upscaling), A1111 is very capable with dedicated interfaces. But outside of those, flexibility is limited unless using scripts or automations. | Very High: This is ComfyUI’s core strength. Any workflow you can conceive (as long as you have nodes) can be built. Text-to-image, image-to-image, inpainting, chaining, multi-output workflows, even non-image workflows are possible. |
| Learning Curve | Shallow to Moderate: Initial learning is easy – core functions are obvious. Mastering all features takes time due to the sheer number of options and extensions, but can be learned step by step. | Steep: Requires learning new concepts (nodes, graph logic) and some understanding of the Stable Diffusion, Flux, Hunyuan, and other base models' pipeline. Beginners may need tutorials, but once learned, complex workflows come naturally. |
| Feature Set | Extensive (via extensions): A1111 has a wide range of features including txt2img, img2img, inpainting, outpainting, depth maps, upscaling, face correction, text inversion, LoRA, etc. | Extensive (via custom nodes): Out of the box, ComfyUI supports most generation features like text/image prompts, inpaint, ControlNet, upscale, variations, etc. |
| Ideal User Type | Artists, hobbyists, and general users, including beginners. Great for those who want a powerful tool without needing to "build" the tool themselves. Also suitable for semi-advanced users who want functionality but prefer a GUI over coding. | Tech-savvy creators, tinkerers, power users, researchers. Ideal for users with specific goals that a one-size-fits-all UI can’t satisfy, like researchers testing a new diffusion process or developers integrating Stable Diffusion, Flux, or other pipelines into a larger system. |
Let's Get Started
If you're just starting with AI image generation or you're a seasoned pro looking for more control, you'll find value here.
We'll walk through everything from basic setups to advanced techniques, helping you build confidence with each step.
Installation & Setup
Download ComfyUI for Windows/Mac here:
For installation instructions and download files, go here:
ComfyUI Keyboard Shortcuts
| Keybind | Explanation |
|---|---|
Ctrl + Enter | Queue up current graph for generation |
Ctrl + Shift + Enter | Queue up current graph as first for generation |
Ctrl + Alt + Enter | Cancel current generation |
Ctrl + Z/Ctrl + Y | Undo/Redo |
Ctrl + S | Save workflow |
Ctrl + O | Load workflow |
Ctrl + A | Select all nodes |
Alt + C | Collapse/uncollapse selected nodes |
Ctrl + M | Mute/unmute selected nodes |
Ctrl + B | Bypass selected nodes (acts like the node was removed from the graph and the wires reconnected through) |
Delete/Backspace | Delete selected nodes |
Ctrl + Backspace | Delete the current graph |
Space | Move the canvas around when held and moving the cursor |
Ctrl/Shift + Click | Add clicked node to selection |
Ctrl + C/Ctrl + V | Copy and paste selected nodes (without maintaining connections to outputs of unselected nodes) |
Ctrl + C/Ctrl + Shift + V | Copy and paste selected nodes (maintaining connections from outputs of unselected nodes to inputs of pasted nodes) |
Shift + Drag | Move multiple selected nodes at the same time |
Ctrl + D | Load default graph |
Alt + + | Canvas Zoom in |
Alt + - | Canvas Zoom out |
Ctrl + Shift + LMB + Vertical drag | Canvas Zoom in/out |
P | Pin/Unpin selected nodes |
Ctrl + G | Group selected nodes |
Q | Toggle visibility of the queue |
H | Toggle visibility of history |
R | Refresh graph |
F | Show/Hide menu |
. | Fit view to selection (Whole graph when nothing is selected) |
| Double-Click LMB | Open node quick search palette |
Shift + Drag | Move multiple wires at once |
Ctrl + Alt + LMB | Disconnect all wires from clicked slot |
Skip Installation with ThinkDiffusion cloud
ThinkDiffusion lets you spin up virtual machines loaded with your choice of open-source apps. Run models from anywhere—Hugging Face, Civitai, or your own—and install custom nodes for ComfyUI. Your virtual machine works just like a personal computer.
The best part? Pick hardware that fits your needs, from 16GB to 48GB VRAM (with an 80GB option coming soon).
Plus, ThinkDiffusion updates apps quickly and maintains multiple versions to keep your workflow running smoothly.
Common Installation Issues
- Missing dependencies or errors during install (how to fix Python/PyTorch issues).
- “CUDA not available” – ensuring correct GPU drivers or using CPU mode if no CUDA.
- Permission errors on Mac/Linux – how to fix with correct permissions or using sudo appropriately.
- Empty browser page or server not launching – checking for firewall or port conflicts, and verifying you opened the correct local URL.
Torch not compiled with CUDA enabled: error
This error means the PyTorch you installed isn’t using your GPU properly. It often happens if you accidentally installed the CPU-only version of torch. To fix it, uninstall the torch package and then reinstall the correct GPU version.
ComfyUI interface not showing up / cannot connect
If you started ComfyUI and nothing opened, or you can’t see the UI, first check the console for the address. By default it should be at 127.0.0.1:8188. Make sure you’re trying to access it from the same machine (ComfyUI by default binds to localhost, so if you’re on a different PC or device on the network, it won’t load). If needed, open a browser on the machine running ComfyUI and go to the URL (http://localhost:8188). If you still get connection refused, ComfyUI might not have started correctly – check for errors in the terminal where you ran main.py or the .bat file.
No models found / model list is empty
If ComfyUI launches but you can’t select any model in the Load Checkpoint node, it means it didn’t detect your Stable Diffusion model file.
Double-check that you placed your model in the correct folder (ComfyUI/models/checkpoints).
If you have another open source UI installed like Automatic1111, you can also configure ComfyUI to use those model directories instead of duplicating files.
Understanding ComfyUI’s Node-Based Workflow System
ComfyUI is a node-based interface for Stable Diffusion. Instead of using sliders and buttons like Automatic1111, you build visual workflows using nodes—modular blocks that perform specific tasks like loading a model, processing a prompt, or generating an image.
Visual Workflow vs. Traditional UI
Most UIs are form-based—you type a prompt, adjust a few sliders, and hit "Generate." The software takes care of the behind-the-scenes processing. ComfyUI, on the other hand, exposes every part of that process as a node.
Think of it like this:
- Traditional UIs = "Type, click, and wait." The process is preset, and you tweak what the UI allows.
- ComfyUI = "Build it your way." You assemble your own AI pipeline using nodes, connecting them like a flowchart.
This means you can rearrange, modify, or add extra steps in the image generation process—something other UIs don’t let you do.
Want to run multiple samplers side by side? Or mix two models in one workflow? You can. This flexibility is what makes ComfyUI so powerful.
Key Concepts: How Workflows Work in ComfyUI
A ComfyUI workflow is a graph of nodes, where:
- Nodes = Building blocks of an image generation process.
- Edges (Connections) = The wires that pass data from one node to another.
- Inputs & Outputs = Each node has specific inputs (what it needs to work) and outputs (what it produces).
Core Nodes Overview (The Essential Pieces)
A ComfyUI workflow typically includes a handful of must-have nodes that every generation process needs. Let’s break them down:
Checkpoint Loader
📌 Loads the AI Model. This is where you pick the Stable Diffusion model (like SD1.5, SDXL, or a fine-tuned custom model) or other models like Flux or Hunyuan, etc.
- Your choice of model affects style and quality.
- Different models = Different art styles or subject capabilities.
- Think of this as the "brain" of the AI—it contains all the knowledge needed to generate images.
🔗 Connects to: Sampler (it needs a model to generate images).
🚨Common Pitfall: No models listed? Make sure your models are in the right folder (ComfyUI/models/checkpoints). If they still don’t show up, restart ComfyUI.
CLIP Text Encoder
📌 The AI doesn’t "read" text like we do—it needs it converted into embeddings (numeric representations of words). This is what the CLIP Text Encoder does.
- Positive Prompt Encoder: Tells the AI what to create.
- Negative Prompt Encoder: Tells the AI what not to include (e.g., "blurry," "low quality," "bad anatomy").
🔗 Connects to: Sampler (it needs prompts to guide the image).
🚨 Common Pitfall: If your prompt isn’t affecting the image much, try increasing CFG Scale in the Sampler node. If the image looks "muddy," your model might have poor prompt adherence.
KSampler
📌 This is the core of image generation—it transforms noise into a meaningful image by following your prompt. Different samplers interpret and refine images differently, affecting speed, sharpness, and creativity.
Controls:
- Sampler Type (Euler, DDIM, DPM++, etc.) – Different algorithms that process the image differently.
- Euler a – Fast and good for quick previews, but may lack fine detail.
- DPM++ 2M Karras – High-quality and smooth details, recommended for final outputs.
- DDIM – Faster but can sometimes produce softer, less-defined images.
- UniPC – A good balance between speed and detail. - Steps – How many refinement passes it takes (higher = more detail, but slower).
- Fewer steps (e.g., 20-30) = Faster, but may lack precision.
- More steps (e.g., 50-70) = More refined images, but diminishing returns beyond ~50. - CFG Scale (Classifier-Free Guidance): Determines how strictly the AI follows your prompt. (higher = more adherence, but less creativity).
- Low (3-5) = More creative freedom, but sometimes off-prompt.
- Medium (7-10) = Balanced—faithful to the prompt but still creative.
- High (12-15) = Follows the prompt strictly but may result in repetitive or unnatural outputs. - Seed – Determines randomness (fixed seed = reproducible results, random = new outputs each time).
🔗 Connects to: VAE Decoder (to convert latent data into an actual image).
🚨 Common Pitfall: If your image looks too rigid or unnatural, lower CFG Scale for more variety. If it’s too abstract, increase CFG Scale to make it follow the prompt more closely. 📌 This is where the magic happens. The sampler gradually refines an image from noise into something coherent.
VAE Decoder
📌 Stable Diffusion doesn’t directly create images—it works in a special compressed format called latent space. The VAE Decoder converts that latent image into something visible.
- If your images look blurry or washed out, try using a better VAE model (some models come with an improved VAE).
- Works like a translator, converting AI data into pixels.
🔗 Connects to: Image Preview or Save Node.
🚨 Common Pitfall: If your output image is weirdly blurry, check if you’re using the right VAE model.
Image Save/Preview
📌 This is the last step—it displays and/or saves the final image.
- Preview Node: Lets you see the image inside ComfyUI.
- Save Node: Exports the image as a file on your computer.
🔗 Connects to: VAE Decoder (because it needs the processed image).
🚨 Common Pitfall: If your image is being saved but not displayed, check if you added a Preview Node!
How These Nodes Work Together (Basic Text-to-Image Pipeline)
Here’s the typical ComfyUI workflow for generating an image:
- Checkpoint Loader → Loads your Stable Diffusion model (e.g., SDXL).
- Text Prompt Encoder → Converts text prompts into a format the AI understands.
- KSampler → Runs the diffusion process to generate an image in latent space.
- VAE Decoder → Converts the latent image into an actual viewable image.
- Image Preview / Save Node → Displays or saves the final result.
In traditional UIs, this entire process is hidden. ComfyUI lets you see and modify every step.
Autocinemograph in ComfyUI
Read more on workflows
Creating Your First Image
Generate your first image with Flux and ComfyUI
Simple 5-step process:
1. Sign up on ThinkDiffusion (we offer free trial)
2. Launch ComfyUI machine
3. Download the workflow from the tutorial below.
4. Once machine is launched, simply drag the workflow onto the ComfyUI user interface
5. Add your input files, adjust prompt & settings, and click generate 💥
Try another one - Here's a collection of 10 cool ComfyUI workflows
Advanced Workflows & Creative Applications
ControlNet in ComfyUI
ControlNet are a series of Stable Diffusion models that lets you have precise control over image compositions using pose, sketch, reference, and many others.
Flux controlnet in ComfyUI
Flux Controlnet model
Recently XLab, InstantX, Shakker Labs and MistoAI have released ControlNets for Flux. XLab's collection supports 3 models for now: Canny, Depth and HED. Each ControlNet is trained on 1024x1024 resolution and works optimally for this resolution.
With Flux, you can create impressive images from text prompts, descriptions or other inputs such as images. It also works well with ComfyUI, a powerful and straightforward workspace. Both experts and newbies, who may not have a technical background, can use it.
ControlNet is a tool for controlling the precise composition of AI images. Using its model, you can provide an additional control image to condition and control your image generation. It can generate detailed photos, illustrations and assets or change existing images.
Learn more about ControlNet with our resources:
Flux Controlnet workflow in ComfyUI
Sketch to Image with Controlnet in ComfyUI
ComfyUI Controlnet workflow
LoRA Models in ComfyUI
Stable Diffusion models are fine-tuned using Low-Rank Adaptation (LoRA), a unique training technique. It offers a solution that is particularly useful in the field of artificial intelligence art production by mainly addressing the issues of balancing the size of model files and training power.
With LoRAs, users can make model customizations without putting a heavy strain on local storage resources.
Artists, designers, and enthusiasts may find the LoRA models to be compelling since they provide a diverse range of opportunities for creative expression. They are also quite simple to use with ComfyUI, which is the nicest part about them.
Our team has created a bunch of tutorials on both using and training your own LoRAs. Check them out here:
ComfyUI LoRA
HyperSD and Blender in ComfyUI
What is Hyper Stable Diffusion?
ByteDance has demonstrated its dedication to both speed and innovation with the introduction of Hyper-SD. It is designed to speed up generation time significantly. With increased speed, it also ensures that images are sharper, more detailed and visually appealing.
HyperSD and Blender in ComfyUI
The image below is a comparison between Hyper SD and SDXL Lightning using 1 step. Tests show that Hyper-SD has better quality and works faster than earlier models such as SDXL-Lightning.
Blender is renowned for its capabilities in creating 3D models and images. With Blender, you can create detailed characters, elaborate scenes and stunning effects for movies, video games and digital art. The software is supported by a passionate community that shares tips, tutorials and plugins to help each other improve their skills.
ComfyUI can connect to Blender with the custom node MixLab. This seamless integration ensures consistent and reliable results, which are essential for any professional projects.
Hyper SD with Blender
Consistent Character Creation in ComfyUI
Follow our step-by-step tutorial to build consistent characters for your storylines:
Consistent Character Creation in ComfyUI
Outpainting in ComfyUI
What is Outpainting?
Outpainting allows for the creation of any desired image beyond the original boundaries of a given picture. That is, you can enlarge photographs beyond their original boundaries using the capabilities of artificial intelligence.
Outpainting in ComfyUI
Troubleshooting & FAQs
Why am I getting blank or black images?
Causes: Typically due to a missing connection or component in the workflow. If the VAE Decoder isn’t connected or the model isn’t loaded correctly, you might not see a proper image.
Solution: Ensure all essential nodes (model, text encoder, sampler, VAE) are properly connected. Verify your prompt isn’t empty and that a valid checkpoint is loaded.
"CUDA out of memory" errors
Causes: Your GPU ran out of VRAM (common with high resolution, large batch sizes, or large models like SDXL on a smaller GPU). Also, video workflows cause this.
Solutions: Reduce image size/steps, use batch size 1, or enable low VRAM mode. If using SDXL, try the base model alone without the refiner or use CPU for the refiner stage. Clearing cached data in ComfyUI may also help. And for large model files, finding distilled or quantized versions that take up less GPU memory also helps. Or you can use the quantised version of models such as gguf which are better optimized for cpu and gpu. Learn more at https://learn.thinkdiffusion.com/introduction-to-flux-ai-quick-guide/#model-quantization
ComfyUI not launching / web page not showing
Causes: Missing dependencies or the local server failing to start.
Fix: Run ComfyUI from a terminal to check errors. Install missing Python packages or update PyTorch. Manually navigate to http://localhost:8188 and check for firewall blocks. There can be 'n' number of reasons such as-
- Port already occupied
- Dependencies Conflict
- Cuda runtime issue
Error messages in nodes (red outline)
Causes: A red outline node is due to missing custom nodes.
Fix: Confirm the model file exists in the correct folder and is named correctly. Update or remove any outdated custom nodes. Install any missing custom nodes through ComfyUI-Manager. After installing make sure to restart and reload your ComfyUI-session
How to update ComfyUI safely?
Guide: First use git fetch and then use git pull in the ComfyUI folder to update if installed via Git. And make sure you are not using any additional command line arguments such as --cpu as it will only trigger cpu.
Precautions: Back up workflows and custom nodes. After updating, test a simple workflow first. Check ComfyUI release notes or Discord for breaking changes.
Can I use ComfyUI with an AMD GPU?
Answer: As of now, ComfyUI is primarily designed for Nvidia GPUs using CUDA. AMD users might try using ROCm (if supported) or run on CPU, but performance will be slower.
Where are my images saved?
Answer: By default, images are saved in the output folder inside the ComfyUI directory. If you used an Image Save node with a custom location, check that path instead.
How do I import someone else’s workflow?
Answer: The most convenient way to import is to drag the file over the ComfyUI interface. Or you could use ComfyUI’s Load feature: place the .json workflow file in the workflows folder, or use the UI’s load function to open it. Ensure you have any required custom nodes for that workflow.
Step-by-Step Tutorials for ComfyUI Workflows
ComfyUI Face Detailer
Motion Brush ComfyUI workflow
Autocinemagraph comfyUI step-by-step tutorial
Community & Expanding Your Skills
ComfyUI Community Resources
- ComfyUI GitHub Discussions
It's the official GitHub discussion board where users report issues, and request for more features. It's also great for staying up to date with new releases. Pretty active of course. - r/ComfyUI on Reddit
We love this Reddit community where users engage and share workflow examples, guides, troubleshooting tips, and more. - ThinkDiffusion Discord
Our active community where users ask questions, share their creations, and insights. We also post detailed tutorials regularly here.
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