Ollama: Run Large Language Models Locally on Your Laptop

Ollama is an open-source platform launched in 2023 that makes it easy to run large language models (LLMs) like Llama, Gemma, and Mistral directly on your laptop, prioritizing privacy, speed, and cost-free AI experimentation. By September 2025, Ollama has grown into a go-to tool for developers and enthusiasts, offering a vast model library and a new desktop app for macOS and Windows, with Linux support via CLI. Here’s a concise rundown on what Ollama is and how to use it to run LLMs on Linux, Windows, or macOS [ollama.com].

What is Ollama?

Ollama is a lightweight, open-source framework designed to simplify downloading, running, and customizing LLMs on local hardware without cloud dependency. It supports over 1,000 models, including Llama 3.2, Gemma 3, and DeepSeek-V3.1, for tasks like coding, chatbots, or data analysis. Key features include:

• Privacy: All processing stays on your device, keeping data secure.
• Customization: Create custom models using a Modelfile to tweak prompts or parameters.
• Compatibility: Runs on macOS, Windows, Linux, and Docker, with minimal setup.
• Ecosystem: Integrates with tools like LangChain and supports multimodal models and embeddings for apps.

Ollama’s 2025 updates include a desktop app for easier access, vigilant mode for secure operations, and improved GPU memory management, making it ideal for both hobbyists and pros.

How to Use Ollama to Run LLMs on Your Laptop

Step 1: Check System Requirements

• Hardware: 8GB RAM for 7B models (e.g., Llama 3), 16GB for 13B, 32GB for 70B. GPU recommended but not required.
• OS: macOS 10.15+, Windows 10/11, or Linux (Ubuntu 20.04+).
• Storage: Models range from 4GB to 50GB+, ensure space.

Step 2: Install Ollama

• macOS: Download the desktop app at ollama.com or use CLI via curl -fsSL https://ollama.com/install.sh | sh.
• Windows: Install via the desktop app or WSL2 for CLI.
• Linux: Run the install script or use Docker (docker pull ollama/ollama).

Step 3: Run a Model

• App: Browse and pull models like Llama 3, then start chatting or analyzing files.
• CLI: ollama run llama3 to download and launch.

Step 4: Customize and Use

• Write a Modelfile (e.g., FROM llama3) to make your own variant.
• Use for code, research, file analysis, or app integration (port 11434).

Step 5: Explore Advanced Features

• Multimodal vision-language models (e.g., llava).
• LAN mode (ollama serve --lan).
• Regular updates via ollama update.

Why It Matters

Ollama empowers anyone to run LLMs locally, bypassing costly cloud APIs while keeping data private. With its 2025 desktop app and growing ecosystem, it’s a budget-friendly alternative to cloud-based AI platforms.

Final Thoughts

Ollama shows how powerful LLMs can live on your laptop without a subscription or cloud lock-in. From students tinkering with code to developers building apps, it’s a privacy-first, cost-free gateway to AI experimentation. Want to try? Download Ollama at ollama.com and run ollama run llama3 to get started.