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Quick Start

Deploy ComfyUI Studio on RunPod and open the web UI in under 5 minutes.

Step 1: Deploy on RunPod

Click the deploy button or go to RunPod Deploy.

Select a GPU. Any NVIDIA GPU from V100 to B200 works. Recommended:

Use Case Recommended GPU VRAM
Video generation (WAN 2.2, HunyuanVideo) A100 80GB, H100, B200 80+ GB
Image generation (Flux, SDXL) RTX 4090, A6000, L40S 24-48 GB
Budget / experimentation RTX 3090, A5000 24 GB

Step 2: Set Environment Variables

Before launching the pod, set these environment variables in the RunPod template:

Variable Required Value
API_KEY Yes Choose a strong password. This is your login to the web UI.
CIVITAI_API_KEY Recommended Your CivitAI API token. Without this, you cannot download models from CivitAI or fetch model metadata. Get it from civitai.com/user/account → API Keys.
HF_TOKEN Recommended Your HuggingFace access token. Without this, you cannot download gated models (Flux, WAN, Hunyuan, etc.). Get it from huggingface.co/settings/tokens → New token → Read access.

API_KEY is required

The default API_KEY is changeme. You must set your own strong password. Anyone with this password has full access to your pod through the web UI.

Step 3: Launch and Wait

Launch the pod. The first boot takes 2-5 minutes because:

  1. The bootstrap script clones the application from GitHub
  2. ComfyUI is copied from the Docker image to the persistent volume
  3. Both services start (ComfyUI on 8188, Studio on 8000)

You can watch the boot progress in the RunPod container logs. Look for:

=== ComfyUI Studio — starting ===
[0/3] First boot — bootstrapping application...
[bootstrap] Cloning repo...
[bootstrap] Copied backend
[bootstrap] Copied frontend
[bootstrap] Bootstrap complete — app v12.3.0
[1/3] ComfyUI already present — skipping
[2/3] Starting ComfyUI on port 8188...
      ComfyUI ready after 10 seconds.
[3/3] Starting Studio backend on port 8000...
=== Services started ===

Step 4: Open the Web UI

Once the services are running, open:

https://<POD_ID>-8000.proxy.runpod.net

Replace <POD_ID> with your pod's ID (shown in the RunPod dashboard).

You'll see a login page. Enter the API_KEY you set in step 2.

Step 5: You're In

After login, you'll see the dashboard with:

  • Component versions and update status
  • GPU/CPU/RAM/disk telemetry
  • Quick stats (models, workflows, nodes)

From here:

  • Go to Models to download AI models
  • Go to Workflows to see available generation pipelines
  • Go to Run to execute a workflow

Next Steps