Setup gemma-4-31B-it-FP8-block PC with NPU Easy Build

Deploying this model locally is quickest when done via Docker.

Follow the sequence of steps detailed below.

The system automatically triggers a cloud download for all heavy weights.

The setup file includes an intelligent feature that instantly optimizes all configurations for your hardware profile.

🧩 Hash sum → 28bb36262a13a6998725f382eb84fe14 — Update date: 2026-06-22 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: enough space for background apps and OS overhead Disk: high-speed SSD 120 GB to cache model layers GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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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