Z-Image-Turbo - Image Generator - ComfyUI & One Click Windows Installer

Z-Image-Turbo is a compact 6B-parameter image model that delivers fast, high-quality results with very few sampling steps, making it ideal for local generation on modest GPUs while still matching or beating much larger models in realism and text rendering. This post shares a plug-and-play ComfyUI workflow plus a one-click Windows installer that handles all dependencies, so you can go from download to generating 1024x1024 images in under a minute without any manual setup.

Free workflow on Civitai: civitai.com

Included in the Installer Package

It automatically sets up:

• ComfyUI and the necessary custom nodes

• Sage Attention 2

• Flash Attention 2

• Triton for Windows

• PyTorch: 2.8.0+cu128

Preloaded Models

• z_image_turbo-Q5_K_M.gguf model — Hugging Face

• Qwen3-4B-UD-Q5_K_XL.gguf text encoder — Hugging Face

• z_image_turbo_vae.safetensors VAE model — Hugging Face

• 2xLexicaRRDBNet_Sharp.pth upscale model — Hugging Face

Speed

Generate 1024 x 1024 images in less than 1 minute (9 steps) on an RTX 4050 6 GB VRAM GPU using the Q5_K_M GGUF model. The workflow automatically scales with your system, providing faster generation and higher resolution on GPUs like the RTX 4090 or higher-memory setups.

System Requirements

• Nvidia RTX 30XX, 40XX, or 50XX series GPU (FP16 support required; GTX 10XX/20XX not tested)

• CUDA-compatible GPU with a minimum of 4 GB VRAM (more recommended)

• Windows OS

• At least 15 GB free storage

Usage Notes

• You can utilize either the Z-Image-Turbo GGUF models or the standard Z-Image-Turbo diffusion models in the workflow.

• Enable or disable workflow sections using the levers in the Fast Groups Bypasser node on the left side of the workflow.

• Be sure to disable Text to Image nodes if you want to use Image to Image and vice versa.

• Enter your detailed descriptive text prompt for the scene you want to generate.

• For best results, enhance your prompt with an LLM.