How to Launch gemma-4-31B-it-FP8-block on AMD/Nvidia GPU

To get this model running locally in no time, utilize the built-in WSL tools.

Refer to the instructions below to proceed.

The installer auto-downloads and deploys the entire model pack.

During setup, the script automatically determines and applies the best settings.

🔒 Hash checksum: bea27f176a5a53da88d83b9ab03ebb4b • 📆 Last updated: 2026-06-26 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space:70 GB free space for full FP16 weights storage GPU: high memory bandwidth GPU for next-gen local AI pipeline

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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