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2026 年 7 月 9 日

gemma-4-31B-it-FP8-block on Copilot+ PC Offline Setup

gemma-4-31B-it-FP8-block on Copilot+ PC Offline Setup

If you need a near-instant local setup, just fetch files via a basic curl request.

Carefully read and apply the steps described below.

The process automatically pulls down gigabytes of critical model assets.

The initial setup handles the heavy lifting, fine-tuning the environment for your device.

📤 Release Hash: 12c8f8fd084fe697ff1c68d9413de7ef • 📅 Date: 2026-07-03



  • Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
  • RAM: enough space for background apps and OS overhead
  • Disk: high-speed SSD 120 GB to cache model layers
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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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