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    Published May 27, 2026by Experimental_dAIver

    The Ultimate Low-VRAM ComfyUI Workflow for Z-Image-Turbo with CacheDiT Turbo Boost⚡

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    workflowresource guidelean workflowlow vramggufcomfyui

    Thought Z-Image-Turbo wasn’t for you because you only have a small graphics card? Think again! 🚀

    With the new ZIT-GGUF-dAIver-v1 workflow, Z-Image-Turbo runs smoothly even on 6 GB VRAM — and with the smaller GGUF variants (Q3/Q4) it can even run on less! Thanks to smart quantization and the built-in CacheDiT Accelerator, you get lightning-fast generations with excellent image quality.


    Why This Workflow Is a Real Game-Changer

    ⚡ CacheDiT – The Speed Boost You Need The integrated CacheDiT_Model_Optimizer accelerates your DiT model by 1.4–1.6× with virtually no quality loss. Just enable it and enjoy significantly faster generation times.

    💾 Extremely Memory-Efficient Thanks to GGUF

    • Main model: z_image_turbo-Q5_K_S.gguf (5.19 GB)

    • Text Encoder: Qwen3-4B.i1-Q5_K_S.gguf (2.82 GB)

    Using smaller quantizations (Q4_K_M, Q3_K_M, etc.) from the official GGUF repository, this workflow runs comfortably on 6 GB or even lower — perfect for laptops and compact GPUs!

    🎨 Two-Stage Upscaling for Professional Results First a 4× detail upscale, followed by a 1× Skin-Contrast refinement. The result: razor-sharp images with beautiful skin texture and fine details.

    🔗 Automatic multiple LoRA Integration Two powerful LoRAs are already included as a sample:

    • Texture_Painterly_2500 (painterly / artistic textures)

    • CrystalShade_Android_Zit (crystal-android ZIT effects)

    Trigger words are automatically detected and added — no extra work required.

    🖼️ Clean & Modern Interface Roughly based on a workflow from @WikkedAI (WikkedZITv4), but equipped with the tricks mentioned above and advanced saving features (SaveImageExtended).


    Download & Installation

    Direct link to the workflow: 👉 Download ZIT-GGUF-dAIver-v1 on Civitai

    Required Custom Nodes (yes, just these, the rest is standard):

    • ComfyUI-GGUF

    • ComfyUI-CacheDiT

    • nd-super-nodes

    • save-image-extended-comfyui

    You’ll find all exact download links and installation paths inside the workflow description.


    Final Thoughts

    Whether you only have 6 GB VRAM or simply want the fastest and most pleasant Z-Image-Turbo experience possible — ZIT-GGUF-dAIver-v1 is probably one of the best low-VRAM workflows available, and easily adoptable to full .safetensor models.

    Fast, beautiful, cleverly designed, and made with attention to detail.

    Give it a try and feel free to let me know how you like the results! ✨