For the fastest local setup of this model, enabling Windows Features is best.
Refer to the instructions below to proceed.
The loader auto-caches the model archive (several GBs included).
The program scans your VRAM and RAM to seamlessly apply optimal configurations.
🗂 Hash: 062cbf9b7a359e8e6dc1eb82a3dc6d04 • Last Updated: 2026-06-24
- Processor: next-gen chip for heavy context processing
- RAM: high-speed DDR5 memory preferred for CPU offloading
- Storage: extra room for future model updates and datasets
- Graphics: CUDA Compute Capability 8.0+ required for flash-attention
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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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