The fastest way to get this model running locally is via Docker.

Review and follow the instructions below.

1-click setup: the app automatically fetches the large weight files.

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

📊 File Hash: 594bbf321e1f0d0238c7d2ea77801b88 — Last update: 2026-06-22 Verify CPU: multi-threading optimized for fast prompt processing RAM: required: 16 GB absolute minimum for small models Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: 12 GB VRAM minimum required for basic quantization

The **gemma-4-31B-it-GGUF** model represents a significant advancement in open‑source language models, combining a 31‑billion parameter architecture with instruction‑following capabilities. Built on the Gemma family, it leverages optimized GGUF quantization to deliver fast inference while maintaining high accuracy on a wide range of tasks. The model excels in multilingual understanding, code generation, and reasoning, making it suitable for both research and production environments. Its lightweight footprint enables deployment on consumer hardware without sacrificing performance, thanks to efficient memory usage and streamlined token processing. Below is a quick comparison of key specifications that highlight its competitive edge:

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