Quick Run gemma-4-31B-it-FP8-block Windows 11 with Native FP4

The most rapid route to a local installation of this model is through Docker.

Simply follow the directions outlined below.

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

The installer will automatically analyze your hardware and select the optimal configuration for your system.

🛠 Hash code: a6ff23e03962b561f07b3158c85386e5 — Last modification: 2026-06-25 Verify Processor: 6-core 3.5 GHz minimum required RAM: 48 GB needed to prevent memory swapping to disk Storage:100 GB free space for HuggingFace cache folder 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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