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

The fastest method for installing this model locally is by using Docker.

Use the instructions provided below to complete the setup.

Be patient as the system self-retrieves massive model weights dynamically.

The smart installation system will instantly find the perfect configuration.

🛠 Hash code: 2ad648587c6f79a1e90655c19b7a9463 — Last modification: 2026-07-02 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: 32 GB or higher for smooth 32k context lengths Disk Space:70 GB free space for full FP16 weights storage GPU: modern architecture (Ada Lovelace / Ampere minimum)

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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