---
language:
- en
tags:
- gguf
- vigyan-ai
- stem
- physics
- calculus
- edge-ai
- on-device
pipeline_tag: text-generation
license: cc-by-nc-4.0
---

# ⚛ Vigyan AI: Sovereign Quantized GGUF Suite [Research Preview]

This repository contains official **GGUF quantizations** of the **Vigyan AI STEM Model Series** engineered for 100% offline, air-gapped on-device deployment across consumer hardware, laptops, and edge devices.

## 📦 Available Checkpoints & Quantizations

| File | Quant Method | Target Hardware | Recommended Context |
| :--- | :--- | :--- | :--- |
| `vigyan-2b-reasoning-q4_k_m.gguf` | Q4_K_M (1.1 GB) | Mobile, WebGPU, 4GB RAM Laptops | 4,096 tokens |
| `vigyan-2b-reasoning-q8_0.gguf` | Q8_0 (1.9 GB) | High-precision on-device 8GB Laptops | 4,096 tokens |

## 🚀 Quickstart via llama.cpp

```bash
llama-cli -m vigyan-2b-reasoning-q8_0.gguf -t 4 --temp 0.2 --repeat-penalty 1.15 -p "<|user|>\nExplain Ohm's Law and RC time constant.\n<|assistant|>\n"
```

## 🔬 Research & Experimental Notice
These checkpoints represent intermediate research iterations developed by **Vigyan AI** to evaluate sovereign neuro-symbolic SLM execution combined with deterministic symbolic solvers (SymPy) and embedded C++ GraphRAG.