
For an instant local deployment, running a pre-configured shell script is ideal.
Please adhere to the deployment steps listed below.
Hands-free setup: the system self-downloads the heavy model files.
During setup, the script automatically determines and applies the best settings.
📘 Build Hash: 56c6c3ff879d846fdc38e1ec864ac41c • 🗓 2026-06-25
- CPU: multi-threading optimized for fast prompt processing
- RAM: required: 16 GB absolute minimum for small models
- Disk Space: free: 80 GB on system drive for scratch space
- Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration
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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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