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    Z-Image — Easy Text-To-Image Workflow | ComfyUI - v1.0 — Primary Release
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    Z-Image – Easy Text-to-Image Workflow (With optional LoRA support)

    This workflow is built to be clean, simple, and extremely easy to use while still giving you everything you need for high-quality Z-Image generations. The layout is organized so clearly that you can see the entire process at a glance — prompt → settings → generate. No clutter, no wandering around the canvas.

    It also includes an optional LoRA loader for character consistency or style variations, along with a built-in 1K and 2K aspect-ratio reference sheet so you can quickly type in the exact resolution you want without hunting for numbers.

    Z-Image is optimized for resolutions up to 2K. Anything higher tends to soften, so the workflow includes a full list of recommended 2K and 1K sizes for easy copy-over.

    On an RTX 4090 (24GB VRAM), it performs extremely fast:
    1K images: typically under 30 seconds
    2K images: usually under 1 minute

    If you want a clean, no-nonsense Z-Image setup that has everything laid out clearly and compactly, this workflow keeps generation simple, predictable, and fast.



    Workflow Requirements

    1. zImage_turbo.safetensors
      Save to: ComfyUI\models\diffusion_models

    2. zImage_vae.safetensors
      Save to: ComfyUI\models\vae

    3. zImage_textEncoder.safetensors
      Save to: ComfyUI\models\text_encoders

    Download link:
    https://huggingface.co/Comfy-Org/z_image_turbo/tree/main/split_files

    Note:
    If ComfyUI shows missing nodes, open the ComfyUI Manager and click “Install Missing Custom Nodes.”

     

     

    Description

    Version 1.0 – Primary Release

    • Fully cleaned and organized Z-Image text-to-image workflow

    • Extremely easy-to-read layout with clear left-to-right flow

    • Added 1K and 2K aspect-ratio reference sheets directly in the workflow

    • Includes optional LoRA loader for character consistency or style control

    • Optimized sampler + settings for fast runtime

    • Includes complete model loader stack (UNET, VAE, CLIP) with folder placement instructions

    • Clean, stable, beginner-friendly starting point for Z-Image generation