---
language:
  - cs
  - sk
  - en
  - de
license: apache-2.0
base_model: EuroLLM-9B
quantization: Q8_0
tags:
  - gguf
  - llama.cpp
  - offline
  - local-ai
  - multilingual
  - cli-runtime
  - ai-runtime
pipeline_tag: text-generation
library_name: llama.cpp
---

# Offline AI 2.2 – EuroLLM-9B-Q8_0 (GGUF)

Offline AI 2.2 is a fully local AI runtime environment built around digital sovereignty, privacy, and system autonomy.

No cloud.  
No telemetry.  
No tracking.  
No external dependencies.  

Everything runs locally via **llama.cpp**.

---

## 🖥️ CLI Preview

Below is the Offline AI runtime interface:

![Offline AI CLI Help Menu](cli_help_menu.png)

Offline AI is no longer just a model launcher.

It is a **local AI runtime environment** designed to manage and operate language models fully offline with a structured command interface.

Core capabilities include:

- CLI runtime environment  
- Model lifecycle management  
- Profile-based workspace system  
- Snapshot conversation archiving  
- Runtime diagnostics and monitoring  
- Administrative control layer  

The architecture is designed as a foundation for **multi-model local AI systems**.

---

## 🧠 RUNTIME ARCHITECTURE

Offline AI uses a layered architecture:

User (CLI)
↓
Python Runtime
↓
C++ Inference Engine (llama.cpp)
↓
GGUF Language Model


The Python runtime acts as the **control layer**, responsible for:

- command handling  
- model orchestration  
- workspace profiles  
- snapshots and notes  
- system diagnostics  
- administrative operations  

The inference backend is a lightweight C++ wrapper around **llama.cpp** with real-time token streaming.

---

## 🔧 TECHNICAL INFORMATION

Base model: EuroLLM-9B  
Quantization: Q8_0 (GGUF)  
Format: llama.cpp compatible  
Inference engine: llama.cpp  
Offline AI Version: 2.2  
Recommended RAM: 16 GB  
Platforms: macOS, Windows, Linux  

This repository distributes a **quantized GGUF Q8_0 variant** of the EuroLLM-9B model optimized for efficient local inference.

The original model weights are **not modified and not fine-tuned** as part of this project.

---

## 🚀 WHAT'S NEW IN 2.2

- Structured CLI runtime environment  
- Model lifecycle management system  
- Model alias system  
- Workspace profiles and isolation  
- Snapshot conversation archiving  
- Runtime diagnostics and monitoring  
- Administrative control mode  
- Improved modular runtime architecture  

Offline AI 2.2 evolves the project from a simple model launcher into a **local AI runtime platform** prepared for managing multiple specialized AI models.

---

## 🔐 PROJECT PHILOSOPHY

Offline AI demonstrates that modern AI systems can operate fully offline.

The project explores the idea that:

- AI does not require cloud infrastructure  
- Open models can run independently on personal hardware  
- AI tools can respect user privacy  
- Local-first computing is a viable architecture  

Offline AI promotes:

- Digital sovereignty  
- Transparent system design  
- Offline experimentation  
- User-controlled AI environments  

---

## 📄 MODEL ORIGIN & LICENSE

Model: EuroLLM-9B  
Original authors: EuroLLM Project consortium  
Funded by: European Union research initiatives  
Base model license: Apache License 2.0  

Quantized distribution: GGUF Q8_0  
Runtime engine: llama.cpp (MIT License)  
Offline AI runtime interface: © David Káninský  

All components are used in compliance with their respective licenses.

---

## ⚠️ DISCLAIMER

This project is an educational and experimental implementation.

It is not a commercial AI service and does not replace professional advice.  
Outputs are not intended for legal, medical, financial, or critical decision-making use.

Use beyond personal, research, or educational purposes is at your own responsibility.

---

## 🌍 PROJECT

Website: https://OfflineAI.online  
Domains: .cz / .sk / .de  

Offline AI Runtime  
Author: David Káninský