This repository contains the GGUF quantized weights for the
z-image-turbo model, optimized to run in environments with limited VRAM resources (though still demanding) using
ComfyUI.
The goal of this upload is to enable the execution of this pipeline by leveraging the efficiency of the GGUF format for both the UNET and the Text Encoder (Qwen).
Feel free to download and use just the workflow (json) in the models tab and versions!
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UNET: models/unet/z_image_turbo-Q8_0.gguf
- Q8 quantized version of the main diffusion model.
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Text Encoder: models/text_encoders/Qwen3-4B-UD-Q5_K_XL.gguf
- Qwen3 4B LLM quantized in Q5, used for prompt processing.
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VAE: models/vae/ae.safetensors
- Standard Variational Autoencoder for decoding the image.
-
Feel free to download and use just the workflow!
To use these models, you will need custom Nodes that support GGUF loading (such as City96's ComfyUI-GGUF or similar).
Even with GGUF quantization, the model requires considerable hardware due to the size of the text encoder and the UNET.
Model Information
Check out the original model card Z-Image Turbo for detailed information about the model.
