Quick Run gemma-4-31B-it-FP8-block on Copilot+ PC Quantized GGUF Step-by-Step

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

Refer to the instructions below to proceed.

Everything happens automatically, including the heavy cloud asset download.

You don’t need to tweak anything; the installer picks the highest performing setup.

🧾 Hash-sum — bf8a3230ab81822355cb2bee3b23f244 • 🗓 Updated on: 2026-06-27 Verify Processor: high single-core performance needed for token latency RAM: minimum 16 GB for stable 8B model loading Disk Space: 100 GB for multi-modal model vision components Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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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