ComfyUI: Running quantized Z-Image GGUF for low VRAM

AI Search·Dec 2025

Demo summary

The creator demonstrates how to use a compressed GGUF version of Z-Image in ComfyUI to generate images on hardware with as little as 4GB of VRAM.

Step-by-step

Drag and drop the JSON workflow file onto the ComfyUI interface
Download a GGUF model file and save it to the 'models/unet' directory
Download a matching quantized text encoder and save it to the 'models/text_encoders' directory
Open the Manager, search for 'ComfyUI GGUF' in the Custom Nodes Manager, and install or update it
Restart ComfyUI
Select the downloaded GGUF model and text encoder in their respective nodes
Enter your positive prompt and set the image width and height
Click Run to generate the image

Options

Choose between various quantization levels (e.g., Q4 medium) based on file size and VRAM
Generate high-resolution images up to 6 megapixels

Watch out for

GGUF nodes will appear red if the custom node extension is not installed or updated
The quantized text encoder should match the quantization level of the model (e.g., Q4 medium for both)

Tips

Update the GGUF custom node to the latest version even if you already have it installed
Z-Image typically does not require a negative prompt
Keep resolution at 1024x1024 for faster generation during testing

Highlights

“Very impressive considering this is a super compressed and quantized version. So in a nutshell, that is how you can use Z image turbo even if you have like 4 GB of VRAM.”

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