Guides by Editorial Team

Self-host Stable Diffusion locally (replace Midjourney/Runway)

Run Stable Diffusion on your own GPU for private, cheaper image generation without subscriptions.

Updated August 31, 2026

Stable Diffusion is the easiest way to generate images with text prompts, but the web services cost money, lock your data, and can change overnight. This guide shows you how to run a ready-made Stable Diffusion web UI on your own machine so you can generate images privately, pay once (or not at all), and keep full control over your workflow.

What you’ll get

  • A local web UI you can run on a laptop or desktop GPU
  • Support for Stable Diffusion 1.5 (low VRAM) and SDXL (high quality)
  • Offline image generation without uploading prompts or art to a cloud service
  • A path to batch rendering, scripts, or hooking into local tools (VS Code, Obsidian, Blender)

What you need

Hardware

  • GPU with 6–8GB VRAM: Stable Diffusion 1.5 (512×512) runs on 6–8GB, but will be slow. A 10–16GB card (RTX 4070/4080) is much smoother.
  • GPU with 12+ GB VRAM: Needed for SDXL 1.0 at 1024×1024. Without it, use Stable Diffusion 1.5 or run 512×512.
  • Disk space: Plan for 10–20GB for models + output.

Software

  • A recent Linux distro (Ubuntu 22.04+ recommended) or Windows 10/11.
  • Python 3.10.6 on Windows (the AUTOMATIC1111 repo pins this exact build for torch compatibility; on Linux the wrapper auto-installs 3.11 via the deadsnakes PPA or your distro’s package). For InvokeAI’s current installer the Launcher ships its own Python.
  • A browser to access the local web UI.

Step 1: Pick a web UI (Automatic1111 is the easiest start)

The most popular local option is the AUTOMATIC1111 Stable Diffusion Web UI. It wraps the model, tokenizer, and GPU runtime into a single web interface. The repo is still active (last push 2026-03-02, AGPL-3.0) and the launch script accepts the same --xformers, --medvram, and --lowvram flags it always has.

Install using the official script (Linux)

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

The script will clone the repo into stable-diffusion-webui/, set up a venv, install PyTorch and the listed requirements, and launch the UI. To enable xformers for faster sampling, edit webui-user.sh in that directory and add --xformers to COMMANDLINE_ARGS before re-running.

Install on Windows

Install Python 3.10.6 (newer 3.11/3.12 builds break torch for this project), then clone and run:

git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
cd stable-diffusion-webui
.\webui-user.bat

Edit webui-user.bat to add --xformers to COMMANDLINE_ARGS if your GPU supports it.

When the server starts, it will print a local URL (e.g., http://127.0.0.1:7860). Open it in your browser.

Step 2: Download a model checkpoint

Stable Diffusion doesn’t include weights by default. The web UI will create a models/Stable-diffusion folder; drop the .ckpt or .safetensors file there.

  • Stable Diffusion 1.5 (CompVis) - works on most consumer GPUs.
  • Stable Diffusion XL 1.0 - higher fidelity, requires 12+ GB VRAM.

Download the model from Hugging Face (requires a free account and accepting the license):

Step 3: Configure for your GPU

In the web UI, click Settings → Stable Diffusion → Stable Diffusion checkpoint and select the model you placed in models/Stable-diffusion.

Low VRAM tips

  • Use --medvram or --lowvram flags when starting launch.py:
    • python launch.py --medvram (best balance for 8GB)
    • python launch.py --lowvram (for 6GB or less)
  • Use half-precision (float16) to save VRAM.
  • Lower the image size (512×512 or 640×640) to avoid out-of-memory errors.

Step 4: Generate images (replace Midjourney)

  1. Open the web UI in your browser.
  2. Set the prompt, width/height, and sampling method.
  3. Click Generate.

The interface lets you batch prompts, use templates, and save results locally. You can also export to a local folder and write scripts to automate rendering.

Optional: Use InvokeAI for a polished “app-like” experience

If you want a more opinionated install that manages models and provides a cleaner UI, try InvokeAI. The current README points users at the InvokeAI Launcher installer rather than the older pip install + invokeai --web workflow, so download the latest Launcher from the InvokeAI releases page and run it. The Launcher handles model management, the bundled UI, and updates.

What This Means

Running Stable Diffusion locally gives you:

  • Privacy: Prompts and images never leave your machine.
  • Cost control: One-time compute (your GPU) instead of monthly subscription fees.
  • Resilience: You won’t lose access if a service changes pricing, adds watermarking, or shuts down.

The downside is you need a capable GPU and some maintenance (updates, model downloads). But for frequent creators, it can save hundreds of dollars per year.

What You Can Do

  • Try the same prompt in Midjourney or Runway and compare output quality and speed.
  • Keep your model files on an encrypted disk if you’re concerned about theft.
  • Use a tool like rclone or rsync to back up generated images automatically.
  • Experiment with different samplers (Euler, DPM++ 2M Karras) to see which fits your style.