gemma-4-31B-it-FP8-block Using Pinokio Local Guide

par | Juin 30, 2026 | Loaders | 0 commentaires

gemma-4-31B-it-FP8-block Using Pinokio Local Guide

For the fastest local setup of this model, enabling Windows Features is best.

Use the instructions provided below to complete the setup.

The process automatically pulls down gigabytes of critical model assets.

The initial setup handles the heavy lifting, fine-tuning the environment for your device.

🔐 Hash sum: fac6a2b50d0d7f59268b0a93f732247b | 📅 Last update: 2026-06-29
  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Storage: extra room for future model updates and datasets
  • 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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