How to Run ComfyUI on RunPod

What You'll Need

• A RunPod account (free to sign up)
• A payment method (credit/debit card or PayPal)
• Basic familiarity with ComfyUI (helpful but not required)

Method 1: One-Click Template (Recommended)

This is the fastest way. RunPod has a community template with ComfyUI pre-installed.

Step 1: Sign Up

Create a RunPod account at runpod.io. Add a payment method to your account.

Step 2: Deploy the Template

1. Log in to RunPod and go to "Pods"
2. Click "Deploy"
3. Under "Community Cloud", search for "ComfyUI"
4. Select the most popular ComfyUI template (usually the one with the most runs)
5. Choose a GPU: RTX 4090 for best performance, A4000 for budget
6. Set disk size to at least 50GB (models take space)
7. Click "Deploy"

Step 3: Access ComfyUI

Once the pod is running (usually under 2 minutes):

1. Click "Connect" on your pod
2. Click the "ComfyUI" HTTP port (usually port 8188)
3. ComfyUI opens in your browser. Start generating.

Step 4: Stop When Done

Click "Stop" on your pod when you're finished. You stop paying immediately.

Method 2: Manual Setup

If you want full control or need custom nodes:

Step 1: Deploy a Base Pod

1. Go to "Pods" → "Deploy"
2. Select "PyTorch" template or a bare Ubuntu image
3. Choose your GPU
4. Deploy and connect via JupyterLab or SSH

Step 2: Install ComfyUI

git clone https://github.com/comfyanonymous/ComfyUI
cd ComfyUI
pip install -r requirements.txt

Step 3: Download Models

Place models in the appropriate folders:

• Checkpoints: ComfyUI/models/checkpoints/
• VAE: ComfyUI/models/vae/
• LoRAs: ComfyUI/models/loras/
• ControlNet: ComfyUI/models/controlnet/

Step 4: Launch ComfyUI

python main.py --listen 0.0.0.0 --port 8188

Then connect via the exposed port in RunPod's interface.

Tips for Cost Efficiency

• Use persistent network storage. Store models on a network volume so you don't re-download them for every pod.
• Stop pods when idle. You're billed by the second while the pod runs.
• Start with A4000 or RTX 3090. Upgrade to 4090 or A100 only if you actually need the speed.
• Use serverless for APIs. If you're serving an API, use RunPod Serverless instead of keeping a pod running.

Common Issues

• "CUDA out of memory": Use a GPU with more VRAM, enable tiled VAE, or reduce image resolution.
• "Model not found": Check that models are in the correct subfolder. ComfyUI is strict about paths.
• "Port not accessible": Make sure you're using RunPod's "Connect" button, not trying to access localhost.