Complete Guide: ComfyUI WAN 2.2 on RunPod

Shahtab Mohtasin — Sun, 05 Oct 2025 20:33:53 +0000

ComfyUI WAN 2.5 Serverless Setup Guide (RunPod)

This tutorial covers the setup of ComfyUI WAN 2.5 on RunPod, including network storage, model downloads, JupyterLab configuration, and workflow testing.

1. Create Required Accounts

RunPod – for GPU pods and serverless functions. Sign up with referral link (Deposit $10 to potentially receive a $5–$500 credit bonus)

2. Fund Your RunPod Account

Ensure you have at least $10 in your RunPod account to spin up GPU pods.

3. Create Network Storage

Navigate to Network Volumes in RunPod.
Create a volume of at least 40 GB for persistent storage.

4. Deploy a Pod with GPU

Click Deploy Pod from the dashboard.
Select GPU (e.g., RTX A5000).
Choose template: ComfyUI Manager – Permanent Disk – torch 2.4
Attach the network volume you created.

5. Launch the Environment

Wait for pod installation.
Open Jupyter Notebook via Connect.
Run the terminal command:

./run_gpu.sh

6. Select Template

Choose the WAN 2.2 Text to Video template for ComfyUI setup.

7. Install Necessary Models

Download and install all required WAN 2.2 models for video generation.

a. High Noise Model

curl -L -o /workspace/ComfyUI/models/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors \
"https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors"

b. Low Noise Model

curl -L -o /workspace/ComfyUI/models/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors \
"https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors"

c. High Noise LoRA

curl -L -o /workspace/ComfyUI/models/loras/wan2.2_t2v_lightx2v_4steps_lora_v1.1_high_noise.safetensors \
"https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/loras/wan2.2_t2v_lightx2v_4steps_lora_v1.1_high_noise.safetensors"

d. Low Noise LoRA

curl -L -o /workspace/ComfyUI/models/loras/wan2.2_t2v_lightx2v_4steps_lora_v1.1_low_noise.safetensors \
"https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/loras/wan2.2_t2v_lightx2v_4steps_lora_v1.1_low_noise.safetensors"

e. VAE Model

curl -L -o /workspace/ComfyUI/models/vae/wan_2.1_vae.safetensors \
"https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors"

f. Text Encoder

curl -L -o /workspace/ComfyUI/models/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors \
"https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors"

8. Test the Workflow

Ensure all model names match the downloaded files.
Open ComfyUI and verify the workflow.
Run the workflow to confirm there are no errors.

9. Move the Models Folder

Move the models folder to a higher-level directory for easier access:

mv /workspace/ComfyUI/models /workspace/

10. Clean Up Workspace

Remove the ComfyUI workspace folder to save space, keeping only the models:

rm -rf /workspace/ComfyUI

Tip: This ensures only the necessary models remain for serverless usage.

11. Terminate the Pod

Terminate the GPU pod to save costs.
Your files will remain intact in Network Storage, ready for serverless deployment.

12. Upload to Private GitHub Repository

Create a private GitHub repo.
Upload the following:

WAN serverless folder
Dockerfile
Snapshot
1. Avoid tracking large model files unless necessary.

13. Deploy as Serverless Endpoint

Connect the GitHub repo to RunPod.
Add your HuggingFace token for model access.

14. Configure Endpoint Settings

Attach the network storage.
Add environment variables:

COMFY_POLLING_MAX_RETRIES=2000
COMFY_POLLING_INTERVAL_MS=500

15. Save and Wait

Save the configuration.
Wait for the deployment to complete before testing.

16. Testing the Endpoint

Method 1: Postman

Set Postman variables to match your serverless API endpoint.
Update input keys and output paths according to the deployed workflow.

Method 2: Custom Web App

Update .env with the correct API URL and tokens.
Ensure environment variables match the endpoint settings.

Notes & Best Practices

If ComfyUI is modified, update Postman requests and web app code accordingly.
Verify that model paths, API keys, and workflow names match your deployed setup.
Regularly check endpoint status and update models if needed.
Use network storage for persistent data between serverless invocations.
For web apps, update .env variables such as:

COMFY_API_URL
HF_TOKEN
STORAGE_PATH

✅ End of ComfyUI WAN 2.5 Serverless Setup Guide

ComfyUI with RunPod: Pod Deployment + Serverless API Setup (free app template and resources)

Shahtab Mohtasin — Thu, 14 Aug 2025 20:07:08 +0000

Learn How to Deploy ComfyUI on RunPod

Use Markdown to write and format posts.
This guide shows how to deploy ComfyUI on RunPod using both pod and serverless setups.
It covers API access, model setup, testing, and includes a free app template to help you build your project.

Video Guide: https://youtu.be/fPcK5FjB0CU?si=XWNmPopLUsp9YM3Q

PART 1: RunPod Pods Setup with ComfyUI – Step-by-Step Guide

This guide provides step-by-step instructions for setting up and using RunPod Pods with ComfyUI.

It covers:

Creating required accounts
Deploying a GPU pod
Installing models
Testing the system

1. Create Required Accounts

RunPod – for GPU pods and serverless functions:
https://runpod.io?ref=ckrxhc11
Signing up and depositing \$10 may grant a one-time bonus credit \$5–\$500.
HuggingFace – for accessing and downloading AI models:
https://huggingface.co/
Civitai – for downloading community models:
https://civitai.com/

2. Fund Your RunPod Account

Ensure \$10+ in your RunPod account to spin up GPU pods.
Referral link (bonus eligible): https://runpod.io?ref=ckrxhc11

3. Create Network Storage

Go to Network Volumes in RunPod.
Create a new volume with at least 40 GB.
This provides persistent storage between pod sessions.

4. Deploy a Pod with GPU

Click Deploy Pod on the RunPod dashboard.
Select a GPU (e.g., RTX A5000 for better performance).
Under Templates, choose: ComfyUI Manager – Permanent Disk – torch 2.4
Attach your network volume during setup.

5. Launch the Environment

………………
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For full free written guide: https://aikitty.cc/comfyui-course

Forem: Shahtab Mohtasin

Complete Guide: ComfyUI WAN 2.2 on RunPod

ComfyUI WAN 2.5 Serverless Setup Guide (RunPod)

1. Create Required Accounts

2. Fund Your RunPod Account

3. Create Network Storage

4. Deploy a Pod with GPU

5. Launch the Environment

6. Select Template

7. Install Necessary Models

a. High Noise Model

b. Low Noise Model

c. High Noise LoRA

d. Low Noise LoRA

e. VAE Model

f. Text Encoder

8. Test the Workflow

9. Move the Models Folder

10. Clean Up Workspace

11. Terminate the Pod

12. Upload to Private GitHub Repository

13. Deploy as Serverless Endpoint

14. Configure Endpoint Settings

15. Save and Wait

16. Testing the Endpoint

Method 1: Postman

Method 2: Custom Web App

Notes & Best Practices

ComfyUI with RunPod: Pod Deployment + Serverless API Setup (free app template and resources)

PART 1: RunPod Pods Setup with ComfyUI – Step-by-Step Guide

1. Create Required Accounts

2. Fund Your RunPod Account

3. Create Network Storage

4. Deploy a Pod with GPU

5. Launch the Environment