How to Run diffusiongemma-26B-A4B-it-NVFP4 Locally via Ollama 2 with Native FP4 No-Code Guide

The fastest method for installing this model locally is by using Docker.

Refer to the instructions below to proceed.

After that, launch the environment using docker-compose.

📊 File Hash: c78bc3c54c47104e48672c83c1cfa1d7 — Last update: 2026-06-23 Verify CPU: multi-threading optimized for fast prompt processing RAM: minimum 16 GB for stable 8B model loading Disk Space: 80 GB NVMe SSD required for fast model weights loading GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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.

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