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Amazing Z-Image Workflow

76

997

29

Type

Workflows

Stats

870

0

Reviews

Published

Dec 4, 2025

Base Model

ZImageTurbo

Hash

AutoV2
EE7BAA370C

A Z-Image-Turbo workflow, which I developed while experimenting with the model, it extends ComfyUI's base workflow functionality with additional features.

Features

  • Style Selector: Choose from fourteen customizable image styles for experimentation.

  • Sampler Selector: Easily pick between the two optimal samplers.

  • Workflows for both checkpoint formats (GGUF / Safetensors).

  • Custom sigma values subjectively adjusted.

  • Generated images are saved in the "ZImage" folder, organized by date.

  • Includes a trick to enable automatic CivitAI prompt detection.

Predefined Styles in This Version

Workflow Overview

The zip contains two workflow files:

1. "amazing_zimage-GGUF.json": Recommended for GPUs with 12GB or less.

2. "amazing_zimage-SAFETENSORS.json": Based directly on the ComfyUI example.

You'll often come across discussions about the best file format for ComfyUI. Based on my experience, GGUF quantized models offer a better balance between compactness and maintaining good prompt response compared to SafeTensors versions. However, it's also true that ComfyUI has internal speed enhancements that work more effectively with SafeTensors, which might lead you to prefer larger SafeTensors files. The reality is that this depends on several factors: your ComfyUI version, PyTorch setup, CUDA configuration, GPU type, and available VRAM and RAM. To help you out, I've included links below to various checkpoint versions so you can determine what works best for your specific system.

Required Checkpoints Files

For amazing_zimage-GGUF.json

For amazing_zimage-SAFETENSORS.json

Based directly on the official ComfyUI example,

Required Custom Nodes

The workflows require the following custom nodes:
(which can be installed via ComfyUI-Manager or downloaded from their repositories)

License

This project is licensed under the Unlicense license.

More info: https://github.com/martin-rizzo/AmazingZImageWorkflow