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README.md

@@ -8,6 +8,8 @@ tags:
 - sdxl
 - stable-diffusion-xl
 - illustrious-xl
+- z-image
+- z-image-turbo
 - qwen-image
 - qwen-image-2512
 - flux
@@ -21,7 +23,7 @@ pipeline_tag: image-to-image
 
 # ControlNet Models (ConvRot INT8)
 
-High-fidelity **ConvRot INT8** quantized weights for multi-condition ControlNet models across diverse generative architectures (**Illustrious-XL / SDXL**, **SDXL 1.0**, **Qwen-Image**, and **FLUX.1-dev**).
+High-fidelity **ConvRot INT8** quantized weights for multi-condition ControlNet models across diverse generative architectures (**Illustrious-XL / SDXL**, **SDXL 1.0**, **Z-Image-Turbo**, **Qwen-Image**, and **FLUX.1-dev**).
 
 ---
 
@@ -31,6 +33,8 @@ This repository hosts high-quality **ConvRot INT8** quantized weights for all-in
 
 - **CN-anytest4_illustrious2 (Variants A & B)**: Multi-purpose all-in-one Anytest v4 ControlNet models fine-tuned for **Illustrious-XL / SDXL** by **2vXpSwA7**, offering high-precision anime and illustration structure guiding.
 - **controlnet-union-pro-max-sdxl-1.0**: The comprehensive all-in-one ControlNet Union model for **SDXL 1.0** by **xinsir**, supporting 10+ control conditions in a single compact file.
+- **Z-Image-Turbo-Fun-Controlnet-Union-2.1-lite-2601-8steps**: Multi-condition ControlNet Union model (lite 6-block architecture, 8-step distilled) for the **Z-Image-Turbo** architecture by **alibaba-pai**, providing lightweight and fast structure control (Canny, Depth, Pose, Color, etc.).
+- **Z-Image-Turbo-Fun-Controlnet-Tile-2.1-lite-2601-8steps**: Dedicated high-resolution Tile and upscaling ControlNet model (lite architecture, 8-step distilled) for the **Z-Image-Turbo** architecture by **alibaba-pai**, optimized for super-resolution detail enhancement.
 - **Qwen-Image-2512-Fun-Controlnet-Union-2602**: Multi-condition ControlNet Union model (5 layer blocks) for the **Qwen-Image-2512** architecture.
 - **Qwen-Image-ControlNet-Inpainting**: Dedicated inpainting and editing ControlNet model for the **Qwen-Image** architecture.
 - **FLUX.1-dev-ControlNet-Union-Pro-2.0**: Next-generation unified 7-in-1 ControlNet for the **FLUX.1-dev** architecture by **Shakker Labs**.
@@ -44,6 +48,8 @@ This repository hosts high-quality **ConvRot INT8** quantized weights for all-in
 | `CN-anytest4_illustrious2_A_convrot_int8.safetensors` | Illustrious-XL / SDXL | [2vXpSwA7/iroiro-lora (Anytest v4 Variant A)](https://huggingface.co/2vXpSwA7/iroiro-lora) | Multi-condition (Canny, Lineart, Depth, Pose, Structure) | ConvRot INT8 | ~1.40 GB | Fair AI / OpenRAIL++-M |
 | `CN-anytest4_illustrious2_B_convrot_int8.safetensors` | Illustrious-XL / SDXL | [2vXpSwA7/iroiro-lora (Anytest v4 Variant B)](https://huggingface.co/2vXpSwA7/iroiro-lora) | Multi-condition (Canny, Lineart, Depth, Pose, Structure) | ConvRot INT8 | ~1.40 GB | Fair AI / OpenRAIL++-M |
 | `controlnet-union-pro-max-sdxl-1.0_convrot_int8.safetensors` | SDXL 1.0 | [xinsir/controlnet-union-sdxl-1.0](https://huggingface.co/xinsir/controlnet-union-sdxl-1.0) | OpenPose, Depth, Canny, Lineart, Anime Lineart, Scribble, Soft Edge, Normal, Segment, Tile, Inpaint | ConvRot INT8 | ~1.40 GB | OpenRAIL++-M / Apache-2.0 |
+| `Z-Image-Turbo-Fun-Controlnet-Union-2.1-lite-2601-8steps_convrot_int8.safetensors` | Z-Image-Turbo | [alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1](https://huggingface.co/alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1) | Multi-condition (Canny, Depth, Pose, Color, Scribble, Inpaint) | ConvRot INT8 | ~1.01 GB | Apache-2.0 |
+| `Z-Image-Turbo-Fun-Controlnet-Tile-2.1-lite-2601-8steps_convrot_int8.safetensors` | Z-Image-Turbo | [alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1](https://huggingface.co/alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1) | Tile, Super-Resolution, Detail Enhancing | ConvRot INT8 | ~1.01 GB | Apache-2.0 |
 | `Qwen-Image-2512-Fun-Controlnet-Union-2602_convrot_int8.safetensors` | Qwen-Image-2512 | [alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union) | Canny, HED, Depth, Pose, MLSD, Scribble, Gray, Inpaint | ConvRot INT8 | ~1.76 GB | Apache-2.0 |
 | `Qwen-Image-ControlNet-Inpainting_convrot_int8.safetensors` | Qwen-Image | [alibaba-pai/Qwen-Image-ControlNet-Inpainting](https://huggingface.co/alibaba-pai/Qwen-Image-ControlNet-Inpainting) | Inpainting, Image Editing | ConvRot INT8 | ~2.12 GB | Apache-2.0 |
 | `FLUX.1-dev-ControlNet-Union-Pro-2.0_convrot_int8.safetensors` | FLUX.1-dev | [Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0) | Canny, Depth, Pose, Blur, Gray, Soft Edge, Low Quality | ConvRot INT8 | ~2.14 GB | Other / Non-Commercial |
@@ -54,7 +60,7 @@ This repository hosts high-quality **ConvRot INT8** quantized weights for all-in
 
 - **All-in-One Multi-Condition Control**: Unified architectures enabling single or blended conditioning inputs (Pose, Depth, Lineart, Canny, Tile, Inpainting, etc.) without switching heavy checkpoints during workflow execution.
 - **ConvRot INT8 Precision**: Leverages orthogonal Hadamard rotations to redistribute channel-wise outlier spikes uniformly across dimensions, preventing quantization error buildup in deep control layers.
-- **VRAM & Storage Optimization**: Slashes VRAM consumption and disk footprint by ~50% to 70% compared to unquantized FP16 checkpoints, allowing seamless multi-ControlNet workflows on consumer GPUs.
+- **VRAM & Storage Optimization**: Slashes VRAM consumption and disk footprint by ~50% compared to unquantized FP16 checkpoints, allowing seamless multi-ControlNet workflows on consumer GPUs.
 
 ---
 
@@ -82,6 +88,7 @@ Place the downloaded `.safetensors` files into your ComfyUI `models/controlnet/`
 ### Base Models & Research
 - **Illustrious Anytest ControlNet:** [2vXpSwA7/iroiro-lora](https://huggingface.co/2vXpSwA7/iroiro-lora) by **2vXpSwA7**
 - **SDXL ControlNet Union:** [xinsir/controlnet-union-sdxl-1.0](https://huggingface.co/xinsir/controlnet-union-sdxl-1.0) by **xinsir**
+- **Z-Image-Turbo ControlNet Models:** [alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1](https://huggingface.co/alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1) & [aigc-apps/VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun) (Apache-2.0)
 - **Qwen-Image ControlNet Models:** [alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union), [alibaba-pai/Qwen-Image-ControlNet-Inpainting](https://huggingface.co/alibaba-pai/Qwen-Image-ControlNet-Inpainting) & [aigc-apps/VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun) (Apache-2.0)
 - **FLUX.1-dev ControlNet Union Pro 2.0:** [Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0) & [InstantX Team](https://huggingface.co/InstantX) (FLUX.1-dev Non-Commercial License)
 - **Base Architectures:** [Illustrious-XL](https://civitai.red/models/675574/illustrious-xl), [Stability AI SDXL 1.0](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) & [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev)