gemma-4-31B-it-FP8-block Uncensored Edition

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gemma-4-31B-it-FP8-block Uncensored Edition

Deploying locally takes the least amount of time when executed through native OS tools.

Check out the detailed setup guide below to begin.

The engine will automatically fetch large dependencies in the background.

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

🔧 Digest: 3db254ee3f4c8aa8bb3a545db80b85a9 • 🕒 Updated: 2026-06-28
  • Processor: high single-core performance needed for token latency
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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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