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Z-Image Turbo ComfyUI: Complete Installation Guide For Windows, Linux & macOS

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File Information

FileDetails
ModelZ-Image Turbo
Text EncoderQwen Text Encoder
VAE ModelAE VAE Model
Z-Image Turbo Workflow.json
LicenseOpen Source (Apache Version 2.0)
Github RepositoryGithub/Z-Image

Description

Z-Image is an efficient 6B-parameter image generation foundation model built by Alibaba Tongyi Lab. It is designed for fast inference, bilingual text rendering, photorealistic generation, and high-quality editing.
It uses an advanced Scalable Single-Stream DiT (S3-DiT) architecture, which merges text + semantic tokens + VAE tokens into one unified stream for maximum efficiency.

Screenshots

Features of Z-Image-Turbo + ComfyUI

Feature CategoryDetails
Model Architecture6B-parameter Single-Stream Diffusion Transformer
SpeedSub-second inference on H800 GPUs; 8-step generation
VariantsZ-Image-Turbo, Z-Image-Base, Z-Image-Edit
Text RenderingHighly accurate bilingual (English + Chinese) text rendering
PhotorealismStrong aesthetics and realism in portraits, products & landscapes
Prompt EnhancerIntegrated reasoning assistance for better prompt alignment
Editing PowerEdit mode supports image-to-image, instruction-guided edits
CompatibilityFully compatible with ComfyUI Nightly builds
Plugin SupportWorks with custom ComfyUI nodes & extensions
Low VRAM FriendlyRuns on 16GB GPUs and even 4GB using stable-diffusion.cpp

System Requirements

ComponentMinimumRecommended
GPU8GB VRAM GPU16GB VRAM (RTX 4070/4080 / H800)
CPUAny modern quad coreRyzen 5 / Intel i5 or higher
RAM8GB16GB+
Storage10GB free space20GB+ for models + workflows
OSWindows 10+, macOS 12+, Linux (Ubuntu/Fedora/Arch)Latest OS version
ComfyUI VersionLatest Nightly buildMust update through Manager → Update ComfyUI
Python (if using standalone)3.10+3.10.6 (best compatibility)

How to Install Z-Image-Turbo in ComfyUI??

1. Model Files You Need (for ComfyUI)

Text Encoder

Diffusion Model

VAE

2. Place Files in Correct Folder Structure (IMPORTANT)

Place the files like this:

📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_3_4b.safetensors
│   ├── 📂 diffusion_models/
│   │      └── z_image_turbo_bf16.safetensors
│   └── 📂 vae/
│          └── ae.safetensors

If you put them in the wrong place then workflow won’t load.

3. Before You Start: Update Your ComfyUI

Z-Image requires latest ComfyUI version by following steps below:

  1. Open ComfyUI
  2. Go to Manager
  3. Click Update ComfyUI
  4. Restart ComfyUI

If you skip this step, you may get missing nodes, import errors, or workflow not loading.

4. Load Workflow

  1. Download the Z-image Workflow From the Download Section
  2. Drag The Workflow File in your ComfyUI App
  3. Load the text encoder, diffusion model and vae in the Node
  4. Your Workflow should look like the below image
z image workflow setup

5.Write Your Prompt in the Prompt Node & Adjust the settings as per your requirements, click Run to Start generating images locally

Z image ComfyUI workflow For LowVRAM Devices

if your device has low vRam then you still can use Z-image , just use GGUF version of the original model , all you need to do is to Download the LowVRAM Workflow for your app and follow the instructions given in the workflow, like downloading quantized model, vae etc.

Download Z-Image-Turbo ComfyUI Workflow

Conclusion

Z-Image Turbo stands out as one of the most efficient and high-quality open-source image generation models available today. With its powerful 6B-parameter Single-Stream DiT architecture, bilingual text rendering, sub-second inference speed, and exceptional photorealistic output, it delivers performance that not only rivals but often exceeds many popular models like Stable Diffusion XL, Flux, and Stable Cascade, all while using significantly fewer computation steps.

When combined with ComfyUI, the entire workflow becomes plug-and-play: easy model placement, drag-and-drop workflows, fast GPU acceleration, and broad community support. Whether you’re a creator, researcher, or someone experimenting with AI art, Z-Image Turbo gives you professional-grade output without the complexity or heavy hardware requirements.

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