Ollama is a local runtime for running Large Language Models (LLMs) on your own machine. It lets developers use AI models without cloud APIs, internet access, or external services.
What Ollama Is Used For
- Running LLMs locally
- Experimenting with prompts and models
- Building local AI-powered developer tools
- Learning how LLMs behave without cloud dependencies
System Requirements
- macOS, Linux, or Windows
- At least 8 GB RAM (16 GB recommended)
- Terminal / command line access
Download and Install Ollama
macOS
Download and install using Homebrew:
brew install ollama
Or download the installer from the official website.
Linux
Install using the official install script:
curl -fsSL https://ollama.com/install.sh | sh
Windows
Download the Windows installer from the official Ollama website and follow the setup steps. Once installed, Ollama runs as a background service.
Verify Installation
After installation, verify that Ollama is working:
ollama --version
Running Your First Model
Ollama automatically downloads models the first time you run them.
ollama run llama3
This command:
- Downloads the model (if not already present)
- Starts an interactive chat session
Type your prompt and press Enter. Use Ctrl + D or /bye to exit.
Basic Ollama Commands
List Installed Models
ollama list
Download a Model (Without Running)
ollama pull llama3
Run a Model with a One-Off Prompt
ollama run llama3 "Explain Java records in simple terms"
Remove a Model
ollama rm llama3
Where Models Are Stored
Ollama stores models locally on your machine. Once downloaded, models can be reused offline without re-downloading.
Why Developers Use Ollama
- No API keys or usage limits
- Full control over data and prompts
- Works offline
- Ideal for local development and experimentation
Ollama Models
Please visit ollama library page for a complete list of supported models (Llama, Phi, Qwen, etc.).
Summary
Ollama is the easiest way to start running LLMs locally. With a single command, developers can download and interact with modern language models directly from the terminal, making it a great entry point for local AI development.
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