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! ✨