Quick Run gemma-4-31B-it-FP8-block

A standalone PowerShell module provides the fastest route to local installation.

Check out the detailed setup guide below to begin.

1-click setup: the app automatically fetches the large weight files.

There is no manual tuning required; the builder deploys the best matching configuration.

📦 Hash-sum → d6cd9a8507c0294441cb1b388ec698f9 | 📌 Updated on 2026-07-08 Verify Processor: next-gen chip for heavy context processing RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: 100 GB for multi-modal model vision components Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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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