Deploying Stable Diffusion WebUI on Nano GPU Service

2026-01-12 By Kelvin 1916 Views nano gpu gpu computing
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This guide walks you through installing and running Stable Diffusion WebUI (AUTOMATIC1111) on a GPU-enabled Linux server, so you can generate images directly from your browser.


Requirements

  • A Linux server with NVIDIA GPU (ensure VRAM matches your model’s requirements)
  • Stable internet connection and sufficient disk space (models may require 10–20GB+)

Step 1: Prepare the system

# apt-get update

# apt install -y wget git python3 python3-venv libgl1 libglib2.0-0

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Step 2: Download WebUI Script

# cd /data

# wget -q https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh

# chmod 700 webui.sh

# sed -i '/SCRIPT_DIR=/a export STABLE_DIFFUSION_REPO="https://github.com/w-e-w/stablediffusion.git"\nexport STABLE_DIFFUSION_XL_REPO="https://github.com/w-e-w/generative-models.git"' webui.sh

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Step 3: Run WebUI

Start the WebUI, binding to 0.0.0.0 so it’s accessible remotely:

# ./webui.sh -f --listen

(Optional: specify a port, default is 7860)

# ./webui.sh -f --listen --xformers

Logs will be stored inside the stable-diffusion-webui folder after first run.

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Step 4: Configure Firewall

Allow external access to port 7860 (or whichever port you chose).

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Step 5: Access the WebUI

Open your browser and visit:

http://your-server-ip:7860

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⚠️ Common Issues

VRAM not enough: Use a smaller model (e.g., SD 1.5) or try optimized forks (e.g., xformers)

Dependency errors: Ensure Python 3.10+ and NVIDIA drivers are installed properly

Exposed to internet: Secure with password, HTTPS, or run behind reverse proxy (nginx)

Missing models: Place model .ckpt or .safetensors in /data/stable-diffusion-webui/models/Stable-diffusion


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