How to Run gemma-4-31B-it-FP8-block PC with NPU 5-Minute Setup

For an instant local deployment, running a pre-configured shell script is ideal.

Proceed by following the technical instructions below.

The engine will automatically fetch large dependencies in the background.

The engine benchmarks your hardware to apply the most effective operational mode.

📘 Build Hash: 8a1d24808a6573ed24663ecba22f1926 • 🗓 2026-07-04 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

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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