How to Setup gemma-4-31B-it-FP8-block with 1M Context Step-by-Step

The fastest way to get this model running locally is via Optional Features.

Follow the sequence of steps detailed below.

The setup auto-streams the model assets (expect a multi-GB download).

The automated script takes care of everything, tailoring the setup to your specs.

🛠 Hash code: bef0392765abd2e324a6ddd81fd171c7 — Last modification: 2026-06-28 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: enough space for background apps and OS overhead Disk Space:70 GB free space for full FP16 weights storage Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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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