How to Launch gemma-4-31B-it-FP8-block PC with NPU Step-by-Step

Docker offers the quickest path to setting up this model locally.

Follow the guidelines below to continue.

Next, run the Docker command to spin up the container.

🧩 Hash sum → 85304c8a512d79a5fceb177be1aa8b2c — Update date: 2026-06-26 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: 48 GB needed to prevent memory swapping to disk Disk Space:70 GB free space for full FP16 weights storage GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The **gemma-4-31B-it-FP8-block** model represents a significant advancement in open‑source language models, combining a **31 billion parameters** base with an *in‑struct tuned* configuration optimized for interactive tasks. Built on the latest *Gemma* architecture, it leverages *FP8 block* quantization to deliver high performance while maintaining a relatively small memory footprint. The model supports a **128K token context window**, enabling it to handle long‑form conversations and complex reasoning without truncation. In benchmarks, it outperforms comparable 31B models by over **12%** on reasoning tasks while consuming less than **16 GB** of GPU memory during inference. A concise

summarizing its core specs is provided below for quick reference.

Parameter Count	31 B
Context Length	128K tokens
Precision	FP8 block
Architecture	Gemma (in‑struct tuned)

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