--- license: apache-2.0 language: - en base_model: - Tongyi-MAI/Z-Image-Turbo library_name: gguf pipeline_tag: text-generation tags: - text-generation - prompt-engineering - image-generation - z-image - z-image-turbo - qwen3 - gguf - text-encoder - comfyui - lm-studio - conversational --- # Z-Image-Engineer V6 GGUF **Follow me on X [@BennyDaBall_OG](https://x.com/BennyDaBall_OG) !** GGUF quantized release for [Z-Image-Engineer V6](https://huggingface.co/BennyDaBall/Z-Image-Engineer-V6). The main repo contains the merged HF safetensors. This repo contains the quant ladder for the [ComfyUI-Z-Engineer](https://github.com/BennyDaBall930/ComfyUI-Z-Engineer) node, LM Studio, ComfyUI `CLIPLoaderGGUF`, llama.cpp-style loaders, and local prompt-enhancement workflows.  --- ## What is this? **Z-Image-Engineer V6** is a SMART DoRA fine-tuned 4B Qwen text encoder from `Tongyi-MAI/Z-Image-Turbo`. Use these GGUF files when you want: - ComfyUI Z-Image text-encoder replacement and in-ComfyUI prompt enhancement through [ComfyUI-Z-Engineer](https://github.com/BennyDaBall930/ComfyUI-Z-Engineer) (no external server needed) - LM Studio prompt enhancement - ComfyUI text-encoder loading through plain `CLIPLoaderGGUF` - smaller local files than the merged HF safetensors - the same V6 prompt style and conditioning behavior in a quantized format --- ## Quantization Ladder | Filename | Size | Target Use Case | |---|---:|---| | `Z-Image-Engineer-V6-F16.gguf` | 7.498 GiB | Full precision reference. | | `Z-Image-Engineer-V6-Q8_0.gguf` | 3.986 GiB | Near-lossless; used for local A/B testing. | | `Z-Image-Engineer-V6-Q6_K.gguf` | 3.079 GiB | High-fidelity balanced footprint. | | `Z-Image-Engineer-V6-Q5_K_M.gguf` | 2.697 GiB | Daily-driver performance-to-size ratio. | | `Z-Image-Engineer-V6-Q4_K_M.gguf` | 2.331 GiB | Reliable 4-bit standard. | | `Z-Image-Engineer-V6-Q3_K_M.gguf` | 1.933 GiB | Lightweight option for tighter setups. | | `Z-Image-Engineer-V6-MXFP4.gguf` | 2.101 GiB | Alternative compact quantization. | Full recursive validation hashes are in `HASHES.sha256`. --- ## Quick Start ### LM Studio Download a GGUF quant, load it, and prompt it directly: ```text Enhance this image prompt for Z-Image Turbo: a unicorn ``` The comparison examples were generated from direct LM Studio user requests like this, with no separate system prompt. `V6_SYSTEM_PROMPT.md` is included only as an optional preset for people who want a stricter prompt-only chat setup. ### ComfyUI (recommended: ComfyUI-Z-Engineer) 1. Install the [ComfyUI-Z-Engineer](https://github.com/BennyDaBall930/ComfyUI-Z-Engineer) custom node (v2.0+). 2. Place a GGUF file into `ComfyUI/models/text_encoders/`. 3. Add **Z-Engineer CLIP Loader (GGUF)** and pick the quant - use the `clip` output where the stock Z-Image Qwen text encoder would normally go. 4. Optional: add **Z-Engineer Prompt Enhancer (Local)** with the same `clip` to rewrite seed prompts in-process, previewed on the node. No LM Studio or external server required. A ready-made workflow ships with the node repo: `example_workflows/z_image_turbo_z_engineer.json`. With [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) installed the quant stays quantized in VRAM. Alternative without the node: add a plain `CLIPLoaderGGUF` node (ComfyUI-GGUF), set model type to `lumina2`, and use it as the text encoder only. Verified image settings: ```text UNET: z_image_turbo_bf16.safetensors VAE: ae.safetensors Text Encoder: Z-Image-Engineer-V6-Q8_0.gguf Resolution: 1024x1024 Steps: 8 CFG: 1.0 Sampler: res_multistep Scheduler: simple Shift: 3.0 ``` --- ## SMART DoRA V6 was trained with BennyDaBall's SMART DoRA system: - **DoRA** for direction/magnitude-separated adapter updates. - **Entropic regularization** for less repetition and broader output variety. - **Holographic regularization** for cleaner depth-wise feature structure. - **Topological regularization** for more coherent latent trajectories. - **Manifold regularization** for stable weight behavior during refinement. The final V6 build used master-corpus SMART DoRA training, retention pressure, SceneClean SFT32 style restoration, AntiRepeat Binary24 refinement, and a 25% style-restoration / 75% anti-repeat DoRA blend. --- ## Related Repos - Main merged HF release: [BennyDaBall/Z-Image-Engineer-V6](https://huggingface.co/BennyDaBall/Z-Image-Engineer-V6) - ComfyUI custom node (GGUF + shard loaders, local prompt enhancer with preview): [ComfyUI-Z-Engineer](https://github.com/BennyDaBall930/ComfyUI-Z-Engineer) --- ## Acknowledgements - **Tongyi-MAI** for the Z-Image Turbo ecosystem. - **Qwen** for the adaptable text encoder backbone. - The open-source maintainers behind **LM Studio**, **ComfyUI**, **llama.cpp**, **PEFT**, and **Transformers**. **Built & trained locally with care by BennyDaBall.** **Follow me on X [@BennyDaBall_OG](https://x.com/BennyDaBall_OG) !**
