Z-Image

How to Run Z-Image in Forge UI: Complete Setup Guide for 2026

Dec 31, 2025

How to Run Z-Image in Forge UI: Complete Setup Guide for 2025

Running Z-Image locally gives you full control over AI image generation without relying on cloud services. This guide walks you through setting up Z-Image in Forge UI, specifically using Forge Neo—the most compatible version for this powerful 6-billion-parameter model.

10

What is Z-Image and Why Use Forge UI?

Z-Image is Alibaba's latest text-to-image model that delivers impressive results in just 8 steps. Released in late 2024, it competes directly with models like FLUX while requiring less computational power. The Turbo variant is optimized for speed, making it ideal for local installations.

Forge UI, particularly the Neo branch, provides native support for Z-Image's diffusion transformer architecture. Unlike the original Stable Diffusion WebUI, Forge Neo includes built-in optimizations for modern models like Z-Image, Flux, and Wan 2.2.

System Requirements

Before starting, verify your system meets these requirements:

  • GPU: NVIDIA graphics card with at least 6GB VRAM (12GB+ recommended)
  • RAM: 16GB system memory minimum
  • Storage: 40GB free space for models and dependencies
  • OS: Windows 10/11, Linux, or macOS (NVIDIA GPUs only)
  • Python: 3.10 or 3.11 (automatically installed by Forge)

Users report that Z-Image runs on cards as old as the GTX 1070, though generation times will be slower on older hardware. A 12GB card like the RTX 3060 generates images in approximately 6 seconds.

Step 1: Install Forge Neo

Forge Neo is a community-maintained fork that continues development of the original Forge WebUI with support for cutting-edge models.

Windows Installation

  1. Open Command Prompt or PowerShell

  2. Navigate to your desired installation directory:

    cd C:\AI

  3. Clone the Forge Neo repository:

    git clone https://github.com/Haoming02/sd-webui-forge-classic sd-webui-forge-neo --branch neo

  4. Launch the WebUI:

    cd sd-webui-forge-neo
webui-user.bat

The first launch will download Python, PyTorch, and other dependencies automatically. This process takes 10-20 minutes depending on your internet connection.

Linux Installation

git clone https://github.com/Haoming02/sd-webui-forge-classic sd-webui-forge-neo --branch neo
cd sd-webui-forge-neo
./webui.sh

Step 2: Download Z-Image Model Files

Z-Image Turbo is available in two precision formats:

  • BF16 (32.9GB): Full precision, best quality
  • FP8 (16.5GB): Reduced precision, lower VRAM usage

Download from Hugging Face

Visit the official model repository:

Download the .safetensors file. For most users, the FP8 version provides excellent results while using half the VRAM.

Place the Model File

  1. Navigate to your Forge Neo installation folder
  2. Open models/Stable-diffusion/
  3. Copy the downloaded .safetensors file here

The file structure should look like:

sd-webui-forge-neo/
└── models/
    └── Stable-diffusion/
        └── z_image_turbo_bf16.safetensors

Step 3: Configure Forge Neo for Z-Image

After placing the model file, restart Forge Neo if it's already running. The interface will automatically detect the new model.

Select the Z-Image Model

  1. Open your browser to http://localhost:7860
  2. At the top of the interface, locate the Checkpoint dropdown
  3. Select z_image_turbo_bf16 (or your FP8 version)
  4. Wait for the model to load (first load takes 30-60 seconds)

Z-Image works differently from traditional Stable Diffusion models. Use these settings for optimal results:

  • Sampling Steps: 8 (the model is optimized for this)
  • CFG Scale: 3.5-4.5 (higher values may oversaturate)
  • Sampler: Euler or DPM++ 2M
  • Resolution: Start with 1024x1024, supports up to 2048x2048

The model reloads each time you modify your prompt. This is normal behavior for diffusion transformer models and ensures consistent results.

Step 4: Generate Your First Image

Let's create a test image to verify everything works correctly.

Basic Prompt Example

Enter this prompt in the text box:

A serene mountain landscape at sunset, snow-capped peaks reflecting golden light, pine forest in foreground, photorealistic, 8k quality

Negative Prompt (optional):

blurry, low quality, distorted, watermark

Click Generate and wait 5-15 seconds depending on your GPU.

Understanding Z-Image's Strengths

Z-Image excels at:

  • Photorealistic scenes: Landscapes, portraits, architecture
  • Prompt adherence: Follows complex instructions accurately
  • Speed: 8-step generation is significantly faster than 20-30 step models
  • Detail preservation: Maintains fine details even at high resolutions

Step 5: Advanced Configuration

Memory Optimization

If you encounter VRAM errors, add these launch arguments to webui-user.bat:

set COMMANDLINE_ARGS=--medvram --opt-split-attention

For cards with 6-8GB VRAM, use:

set COMMANDLINE_ARGS=--lowvram --opt-split-attention

Batch Generation

To generate multiple images at once:

  1. Increase Batch Count (generates sequentially)
  2. Or increase Batch Size (generates simultaneously, uses more VRAM)

For a 12GB card, batch size of 2-3 works well.

Troubleshooting Common Issues

Model Not Appearing in Dropdown

Solution: Verify the file is in models/Stable-diffusion/ and has a .safetensors extension. Restart Forge Neo completely.

"Out of Memory" Errors

Solution:

  • Switch to the FP8 model version
  • Add --medvram or --lowvram launch arguments
  • Reduce resolution to 768x768
  • Close other GPU-intensive applications

Slow Generation Times

Solution:

  • Ensure you're using exactly 8 sampling steps
  • Update your GPU drivers
  • Check that CUDA is properly installed (run nvidia-smi in terminal)

Images Look Oversaturated

Solution: Reduce CFG Scale to 3.0-3.5. Z-Image is sensitive to high guidance values.

Comparing Local vs Cloud Solutions

Running Z-Image locally offers several advantages:

Local Installation Benefits:

  • No usage limits or credits
  • Complete privacy—images never leave your computer
  • Customizable settings and workflows
  • No internet dependency after setup

When to Consider Cloud Services:

  • Limited hardware (less than 6GB VRAM)
  • Occasional use doesn't justify setup time
  • Need for mobile access

For users who want to experiment without local setup, platforms like zimage.run provide instant access to Z-Image through a web interface. This can be useful for testing prompts before committing to a local installation, or for generating images on devices without compatible GPUs.

Next Steps and Resources

Once you have Z-Image running, explore these advanced features:

Image-to-Image Generation

Forge Neo supports img2img with Z-Image:

  1. Switch to the img2img tab
  2. Upload a reference image
  3. Adjust Denoising Strength (0.3-0.7 for modifications)
  4. Generate variations

ControlNet Integration

Install ControlNet extensions for precise control over composition, pose, and style. Z-Image works with standard ControlNet models.

Community Resources

Conclusion

Setting up Z-Image in Forge Neo gives you a powerful, fast AI image generator running entirely on your local machine. The 8-step generation process makes it one of the quickest models available, while the 6-billion-parameter architecture ensures high-quality results.

The initial setup takes about an hour including downloads, but once configured, you have unlimited image generation capability. Whether you're creating art, prototyping designs, or exploring AI capabilities, local installation provides the flexibility and privacy that cloud services cannot match.

For those who prefer immediate access without setup, remember that web-based options like zimage.run offer a convenient alternative to test the model's capabilities before committing to a local installation.

Zimage.run Team