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@@ -14,6 +14,8 @@ tags:
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  - qwen-image-2512
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  - flux
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  - flux.1-dev
 
 
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  - quantized
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  - int8
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  - convrot
@@ -23,13 +25,13 @@ pipeline_tag: image-to-image
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  # ControlNet Models (ConvRot INT8)
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- 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**).
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  ---
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  ## 🌟 Model Overview
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- This repository hosts high-quality **ConvRot INT8** quantized weights for all-in-one ControlNet Union and dedicated ControlNet models. By applying orthogonal Hadamard rotation prior to per-channel INT8 quantization, these models effectively eliminate activation outlier distortion and drastically reduce VRAM and disk footprint while preserving precise structural control fidelity:
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  - **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.
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  - **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.
@@ -37,13 +39,17 @@ This repository hosts high-quality **ConvRot INT8** quantized weights for all-in
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  - **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.
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  - **Qwen-Image-2512-Fun-Controlnet-Union-2602**: Multi-condition ControlNet Union model (5 layer blocks) for the **Qwen-Image-2512** architecture.
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  - **Qwen-Image-ControlNet-Inpainting**: Dedicated inpainting and editing ControlNet model for the **Qwen-Image** architecture.
 
 
 
 
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  - **FLUX.1-dev-ControlNet-Union-Pro-2.0**: Next-generation unified 7-in-1 ControlNet for the **FLUX.1-dev** architecture by **Shakker Labs**.
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  ---
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  ## 📦 Available Models
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- | Filename | Base Architecture | Base Model | Supported Conditions | Quantization | File Size | License |
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  | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
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  | `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 |
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  | `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 |
@@ -52,13 +58,16 @@ This repository hosts high-quality **ConvRot INT8** quantized weights for all-in
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  | `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 |
53
  | `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 |
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  | `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 |
 
 
 
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  | `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 |
56
 
57
  ---
58
 
59
  ## 🛠️ Key Features
60
 
61
- - **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.
62
  - **ConvRot INT8 Precision**: Leverages orthogonal Hadamard rotations to redistribute channel-wise outlier spikes uniformly across dimensions, preventing quantization error buildup in deep control layers.
63
  - **VRAM & Storage Optimization**: Slashes VRAM consumption and disk footprint by ~50% compared to unquantized FP16 checkpoints, allowing seamless multi-ControlNet workflows on consumer GPUs.
64
 
@@ -90,6 +99,7 @@ Place the downloaded `.safetensors` files into your ComfyUI `models/controlnet/`
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  - **SDXL ControlNet Union:** [xinsir/controlnet-union-sdxl-1.0](https://huggingface.co/xinsir/controlnet-union-sdxl-1.0) by **xinsir**
91
  - **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)
92
  - **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)
 
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  - **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)
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  - **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)
95
 
 
14
  - qwen-image-2512
15
  - flux
16
  - flux.1-dev
17
+ - diffsynth
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+ - diffsynth-studio
19
  - quantized
20
  - int8
21
  - convrot
 
25
 
26
  # ControlNet Models (ConvRot INT8)
27
 
28
+ High-fidelity **ConvRot INT8** quantized weights for multi-condition and dedicated ControlNet models across diverse generative architectures (**Illustrious-XL / SDXL**, **SDXL 1.0**, **Z-Image-Turbo**, **Qwen-Image / Qwen-Image-2512**, and **FLUX.1-dev**).
29
 
30
  ---
31
 
32
  ## 🌟 Model Overview
33
 
34
+ This repository hosts high-quality **ConvRot INT8** quantized weights for all-in-one ControlNet Union and dedicated condition-specific ControlNet models. By applying orthogonal Hadamard rotation prior to per-channel INT8 quantization, these models effectively eliminate activation outlier distortion and drastically reduce VRAM and disk footprint while preserving precise structural control fidelity:
35
 
36
  - **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.
37
  - **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.
 
39
  - **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.
40
  - **Qwen-Image-2512-Fun-Controlnet-Union-2602**: Multi-condition ControlNet Union model (5 layer blocks) for the **Qwen-Image-2512** architecture.
41
  - **Qwen-Image-ControlNet-Inpainting**: Dedicated inpainting and editing ControlNet model for the **Qwen-Image** architecture.
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+ - **Qwen-Image DiffSynth ControlNet Suite**: Dedicated single-condition ControlNet models for the **Qwen-Image** architecture developed by **DiffSynth-Studio**:
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+ - **`qwen_image_canny_diffsynth_controlnet_convrot_int8`**: High-precision Canny edge structural control.
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+ - **`qwen_image_depth_diffsynth_controlnet_convrot_int8`**: Geometric spatial depth guidance.
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+ - **`qwen_image_inpaint_diffsynth_controlnet_convrot_int8`**: Masked inpainting and localized semantic replacement.
46
  - **FLUX.1-dev-ControlNet-Union-Pro-2.0**: Next-generation unified 7-in-1 ControlNet for the **FLUX.1-dev** architecture by **Shakker Labs**.
47
 
48
  ---
49
 
50
  ## 📦 Available Models
51
 
52
+ | Filename | Base Architecture | Base Model / Author | Supported Conditions | Quantization | File Size | License |
53
  | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
54
  | `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 |
55
  | `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 |
 
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  | `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 |
59
  | `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 |
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  | `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 |
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+ | `qwen_image_canny_diffsynth_controlnet_convrot_int8.safetensors` | Qwen-Image | [modelscope/DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) | Canny Edge Detection & Structural Guidance | ConvRot INT8 | ~1.14 GB | Apache-2.0 |
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+ | `qwen_image_depth_diffsynth_controlnet_convrot_int8.safetensors` | Qwen-Image | [modelscope/DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) | Geometric Depth Map Guidance | ConvRot INT8 | ~1.14 GB | Apache-2.0 |
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+ | `qwen_image_inpaint_diffsynth_controlnet_convrot_int8.safetensors` | Qwen-Image | [modelscope/DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) | Masked Inpainting & Localized Editing | ConvRot INT8 | ~1.14 GB | Apache-2.0 |
64
  | `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 |
65
 
66
  ---
67
 
68
  ## 🛠️ Key Features
69
 
70
+ - **All-in-One & Dedicated Condition Control**: Unified multi-condition architectures alongside specialized single-condition models (Canny, Depth, Tile, Inpainting) for fine-grained workflow flexibility.
71
  - **ConvRot INT8 Precision**: Leverages orthogonal Hadamard rotations to redistribute channel-wise outlier spikes uniformly across dimensions, preventing quantization error buildup in deep control layers.
72
  - **VRAM & Storage Optimization**: Slashes VRAM consumption and disk footprint by ~50% compared to unquantized FP16 checkpoints, allowing seamless multi-ControlNet workflows on consumer GPUs.
73
 
 
99
  - **SDXL ControlNet Union:** [xinsir/controlnet-union-sdxl-1.0](https://huggingface.co/xinsir/controlnet-union-sdxl-1.0) by **xinsir**
100
  - **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)
101
  - **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)
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+ - **Qwen-Image DiffSynth ControlNet Models:** [modelscope/DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) by **ModelScope / Alibaba Group** (Apache-2.0)
103
  - **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)
104
  - **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)
105