Using the Windows Package Manager is the quickest way to trigger the setup.

Follow the guidelines below to continue.

The loader auto-caches the model archive (several GBs included).

The configuration wizard runs silently to set up the model for peak performance.

🧾 Hash-sum — fe4e70e0bf13ab1038f6385afbe88073 • 🗓 Updated on: 2026-06-28 Verify Processor: 6-core 3.5 GHz minimum required RAM: enough space for background apps and OS overhead Disk Space:70 GB free space for full FP16 weights storage GPU: high memory bandwidth GPU for next-gen local AI pipeline

The diffusiongemma-26B-A4B-it-NVFP4 model leverages a Gemma-based architecture to deliver high‑fidelity image generation with only 26 billion parameters. Its NVFP4 quantization enables fast inference on consumer‑grade hardware while preserving fine‑grained details. The model excels in multi‑modal prompting, accepting text instructions and producing corresponding visual outputs with impressive coherence. Compared to earlier diffusion models, it achieves a superior balance between speed and quality, making it suitable for real‑time creative workflows. Developers appreciate its seamless integration with the Transformer ecosystem and the built‑in support for conditional generation. Overall, the diffusiongemma-26B-A4B-it-NVFP4 stands out as a versatile tool for both research and production environments.

Parameter Count	26 B
Architecture	Gemma‑based diffusion Transformer
Quantization	NVFP4
Max Input Tokens	1024
Output Resolution	1024×1024

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