Offline AI GitHub Projects

10 GitHub projects that let you run AI completely offline on your own computer for free.

📌1. Ollama

Run Llama, Mistral, Gemma, and 50+ models locally.

Key Features:
One command to install.
Ideal for developers seeking raw control.

📌2. LM Studio

A beautiful desktop app that downloads and runs any open model with zero code.

Key Features:
Best for non-technical users.

📌3. Jan

Open-source ChatGPT alternative that runs 100% offline.

Key Features:
Chat interface.
Model manager.
Built-in API server.

📌4. GPT4All

Designed for complete beginners.

Key Features:
Download the app, pick a model, and start chatting.
No setup knowledge required.

📌5. AnythingLLM

Turns your local AI into a full knowledge base.

Key Features:
Chat with your own PDFs, docs, and notes.
Operates with zero cloud dependency.

📌6. LocalAI

Drop-in replacement for the OpenAI API.

Key Features:
All your existing tools keep working, just pointed at your own machine.

📌7. MSty

Privacy-first AI desktop app.

Key Features:
Multi-model chat and document support.
Ensures data never leaves your machine.

📌8. Open WebUI

Browser-based ChatGPT-style interface that connects to Ollama.

Key Features:
Familiar interface.
Runs completely offline.

📌9. llamafile

Single executable file that runs a full AI model.

Key Features:
Download one file.
Double-click to start.

📌10. Koboldcpp

Long-context AI inference that runs on old hardware.

Key Features:
Conversations stay on your machine.
Your data never leaves.
Zero cost to operate.

📌Flowchart

START
↷
SELECT TOOL
↷
INSTALL LOCALLY
↷
CONFIGURE MODEL
↷
RUN OFFLINE AI
↷
UTILIZE AI OUTPUT

📌🛠 Real-Time Story: Building Your Offline AI Workspace

Imagine Sarah, a freelance writer, who often needs quick AI assistance for brainstorming ideas and summarizing research papers. She’s concerned about privacy and prefers tools that don’t rely on cloud services.

Step 1: Sarah downloads LM Studio because it’s beginner-friendly and requires no coding knowledge.
Step 2: She installs AnythingLLM to organize her PDFs and notes into a searchable knowledge base.
Step 3: For longer writing projects, Sarah uses Koboldcpp to generate context-aware suggestions on her older laptop.
Step 4: With her offline AI setup, Sarah works efficiently, knowing her data stays secure and her tools are free to use.

By combining these tools, Sarah builds a robust offline AI workspace tailored to her needs.