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Deploy gemma-4-31B-it-FP8-block Using Pinokio Quantized GGUF

Deploy gemma-4-31B-it-FP8-block Using Pinokio Quantized GGUF

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

Please follow the instructions listed below to get started.

The download manager will automatically pull several gigabytes of data.

You don’t need to tweak anything; the installer picks the highest performing setup.

đź’ľ File hash: 96454c9ae143a003dbfeefae15636b84 (Update date: 2026-06-26)



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Storage:100 GB free space for HuggingFace cache folder
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

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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