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The purpose of this workflow is to mix ZIT's excellent prompt tracking and high image quality with illustrious- SDXL's vast AGC character resources.
Laufzeitprofil
Quellenbeschreibung
nunchaku-Z-image_to_SDXL
The purpose of this workflow is to mix ZIT's excellent prompt tracking and high image quality with illustrious- SDXL's vast AGC character resources.
In other words, characters that ZIT has not yet learned can be expressed using illustrious-SDXL's learned resources without using Lora.
It combines nunchaku-Z-image-turbo and SDXL for extremely fast generation speeds .
This is how I use it, but it's up to you to use it in your own way.
SVDQ Nunchaku-Z Image Turbo with SDXL Workflow
Very faster generation speed compared to Z-image-Turbo to SDXL (workflow)
KI-generierter Kommentar
KI-generierte Erklärung auf Grundlage von Quellen- und Konfigurationsdetails. Vorschläge sind klar gekennzeichnet.
Use nunchaku-Z-image_to_SDXL to generate images from prompt text by combining ZIT's prompt tracking and high image quality with Illustrious-SDXL character resources; it uses nunchaku-z-image-turbo or Z-Image Turbo with an Illustrious checkpoint.
The workflow encodes text, creates and samples a latent image, decodes it with a VAE, combines images, creates row-based grids, and saves animated WEBP files.
Inputs include prompt text, an empty latent image, checkpoint and text-encoder files, a VAE, and a LoRA.
Outputs include decoded images, combined images, row-based image grids, and animated WEBP files.
Use ComfyUI 0.6 or higher with Nunchaku 1.1.0 and ComfyUI-nunchaku 1.1.0.
Place nunchaku-z-image-turbo in diffusion_models, an Illustrious checkpoint in checkpoints, and the DMD2 Speed LoRA in loras.
The workflow uses the node packs ComfyUI-nunchaku, comfyui-easy-use, and images-grid-comfy-plugin.
Model files identified for the workflow include ae.safetensors, Luc_meqemeqe.safetensors, svdq-fp4_r128-z-image-turbo.safetensors, qwen_3_4b.safetensors, and dmd2_sdxl_4step_lora_fp16.safetensors.
For the Z-Image component, choose nunchaku-z-image-turbo or Z-Image Turbo - Quantized for low VRAM.
Vorschlag · nicht geprüft
For the SDXL component, select an Illustrious checkpoint; the description names Luc_meqemeqe - v1.0 as a merge model.
Vorschlag · nicht geprüft
The setup names dmd2_sdxl_4step_lora_fp16 or dmd2_sdxl_4step_lora_fp32 for the DMD2 Speed LoRA.
Before running, verify that qwen_3_4b.safetensors, Luc_meqemeqe.safetensors, and svdq-fp4_r128-z-image-turbo.safetensors are the files your setup expects.
Vorschlag · nicht geprüft
Make sure the official Nunchaku Z-Image Turbo workflow works before using this workflow.
Vorschlag · nicht geprüft
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Quellen
1 QuelleQuellenauszüge
1 AuszugSource context: 311 downloads · Type Workflows · Base model ZImageTurbo
Requirements
ComfyUI ver. 0.6 or higher
Install or Updated to Nunchaku version 1.1.0
Install or Updated to ComfyUI-nunchaku version 1.1.0
Models
nunchaku-z-image-turbo or Z-Image Turbo - Quantized for low VRAM
Illustrious Model
Civitai | Share your models Illustrious Checkpoint
also recommend my merge model
Luc_meqemeqe - v1.0 | Illustrious Checkpoint
DMD2 Speed LoRA
dmd2_sdxl_4step_lora_fp16 or dmd2_sdxl_4step_lora_fp32
Here is a great explanation by Simplesmente
Thank you very much, Simplesmente!
This official workflow must work before it can be used.
I use ComfyUI 0.6.0 from Stability Matrix
Install ComfyUI anew
Pytroch 2.9.1+cu130 (December 30, 2025)
Install ComfyUI-nunchaku with Manager and restart
Nunchaku Installer
add Preview as Text
connection
mode: Select update node and run
Follow the text press "R"
verson : 1.1.0
mode : install
Then RUN
Success! Installed
Restart ComfyUI
Download this workflow and drag and drop it.
raw.githubusercontent.com/nunchaku-tech/ComfyUI-nunchaku/refs/heads/main/example_workflows/nunchaku-z-image-turbo.json
This dialog box will appear, so download each model to the designated folder.
Download nunchaku-z-image-turbo to " diffusion_models " folder
(.\StabilityMatrix\Data\Packages\ComfyUI\models)
nunchaku-tech/nunchaku-z-image-turbo at main
RTX50xx is fp4, RTX40xx, 30xx is int4
I have an RTX5060Ti 16GB so I chose fp4_r128
Download the model and place it in the designated folder. Press "R" to update the model.
"RUN"
Similarly, drag and drop this workflow "nunchaku-Z-image_to_SDXL.json"
Missing nodes are installed from the Manager's Missing Custom Nodes
restart
Checkpoints folder contains the Illustrious Checkpoints of your choice.
DMD2 Speed LoRA to the loras folder
dmd2_sdxl_4step_lora_fp16 or dmd2_sdxl_4step_lora_fp32
Download the model and place it in the designated folder. Press "R" to update the model.
"RUN"
If you want to use Lora with nunchaku-z-image-turbo,
Install the following custom node:
Geschätzter VRAM Bedarf
Schätzung nicht verfügbar
376 MB über 1 von 5 Modell-Dateien. Gesamtmodell-Dateien + 25% Ladeaufwand + 2 GB Ausführungs-Puffer, aufgerundet.
Anforderungen
8 AnforderungenVAE · Unknown
LoRA · 376 MB · SAFETENSOR · Unknown
Luc_meqemeqe.safetensors
Nicht aufgelöstCheckpoint · Unknown
svdq-fp4_r128-z-image-turbo.safetensors
Nicht aufgelöstCheckpoint · Unknown
Knotenpaket · Registry
Knotenpaket · Registry
Knotenpaket · Registry
