How to Launch gemma-4-31B-it-FP8-block Windows 11 One-Click Setup 2026/2027 Tutorial

Deploying this model locally is quickest when done via Docker.

Use the instructions provided below to complete the setup.

Then, run the specified Docker command to start the environment.

🧾 Hash-sum — abcf5faa23c9fe210b63580ef2d8cb82 • 🗓 Updated on: 2026-06-27 Verify Processor: next-gen chip for heavy context processing RAM: 48 GB needed to prevent memory swapping to disk Disk: high-speed SSD 120 GB to cache model layers GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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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