JusteLeo/Nunchaku-Zimage-Win-Wheels

Nunchaku Prebuilt Wheels for Z-image (Windows)

This repository provides the missing pre-compiled binaries (.whl) for the Nunchaku library, specifically optimized for Windows x64 environments where official wheels are unavailable.

🚀 What's New in v1.2.0

• —Cache-DiT: Support for the new inference optimization.
• —Z-Image Turbo Optimizations: Performance gains via layer fusion (QKV/Norm/Rotary).
• —RTX 2000 Series Support: Native compatibility for Turing GPUs.
• —Improved Compatibility: Updated for the latest diffusers versions.

🛠 GPU & CUDA Support

⚠️ Hardware Compatibility Note

⚙️ Compilation Details

To ensure maximum stability and performance, the v1.2.0 wheels were compiled using CUDA Toolkit 12.9 for the following environments:

• —PyTorch 2.7.0 +cu128
• —PyTorch 2.8.0 +cu128

Compatibility Matrix (Windows Only)

Build Methodology

Built in 2025 with:

• —OS: Windows 11 x64
• —Compiler: MSVC (Visual Studio 2022)
• —CUDA Toolkit: v12.9

Local Build Command (Reference)

set CUDA_HOME=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.9
set CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.9
set DISTUTILS_USE_SDK=1

uv pip install torch==2.8.0 torchvision --index-url https://download.pytorch.org/whl/cu128
uv pip install numpy ninja setuptools packaging wheel
uv build --wheel --no-build-isolation

Installation

1. 1.Download the .whl file matching your environment from the Files tab.
2. 2.Install via pip:

# Example for Python 3.12 and v1.2.0
pip install nunchaku-1.2.0+torch2.8-cp312-cp312-win_amd64.whl

1. 1.Verify:

import nunchaku
print("Nunchaku v1.2.0 (Z-image) successfully loaded.")

Disclaimer

This is an unofficial community repository providing missing Windows wheels. For original source code and official updates, please visit the Nunchaku-tech GitHub.