Learn How to Install and Run Ollama

What is Ollama and Why You Might Want to Use It

Ollama is an open-source software tool that lets you run large language models on your own computer. Large language models are AI systems that can understand and generate human language. Instead of using a service like ChatGPT that runs on someone else's servers, Ollama allows you to run similar models locally, meaning the software and data stay on your machine.

The primary reason people use Ollama is privacy. When you use web-based AI tools, your conversations get sent to external servers. With Ollama, your text stays on your computer. This matters for people working with sensitive information, such as medical professionals, lawyers, or researchers who cannot share their data with third parties.

Another reason is cost. Ollama itself is free, and many of the models it runs are free as well. You do not need to pay subscription fees to OpenAI, Anthropic, or other companies if you use Ollama with open-source models. The trade-off is that you need a computer with enough processing power and storage space.

Ollama supports multiple models of varying sizes. The smallest models might use 3 to 4 gigabytes of memory, while larger ones can use 30 gigabytes or more. Popular models available through Ollama include Llama 2, Mistral, and Neural Chat. Each model has different strengths—some are better at coding, others at writing, and some at general conversation.

Ollama runs on macOS, Windows, and Linux. This wide compatibility means most people can use it regardless of their operating system. The software is actively maintained, with regular updates adding new models and improving performance.

Practical takeaway: Ollama is appropriate if you need privacy, want to avoid subscription costs, or want to experiment with AI models on your own hardware. It is not appropriate if you need the absolute latest model versions or do not have a computer with sufficient resources.

System Requirements and Hardware Considerations

Before installing Ollama, you need to understand whether your computer meets the minimum requirements. The good news is that Ollama can run on modest hardware, but the speed and capability depend heavily on your specific setup.

For CPU-based operation, you need at least 8 gigabytes of RAM for smaller models like Mistral 7B. The more RAM you have, the larger models you can run comfortably. A computer with 16 gigabytes of RAM can handle mid-sized models well. If you have 32 gigabytes or more, you can run larger models without significant slowdowns. CPU processing is much slower than GPU processing, so expect longer wait times for responses.

GPU acceleration dramatically improves performance. If your computer has an NVIDIA graphics card with CUDA support (compute capability 3.5 or higher), Ollama can use the GPU to speed up processing. Many modern NVIDIA cards from the GTX 960 and newer support this. An NVIDIA RTX 3060 or better provides excellent performance. For Apple computers with M1, M2, M3, or M4 chips, the integrated GPU is automatically used and performs very well—these machines are some of the best for running Ollama.

Storage space matters. Small models take 3 to 5 gigabytes of disk space. Medium models take 10 to 15 gigabytes. Large models can exceed 30 gigabytes. You should have at least 50 gigabytes of free space if you plan to experiment with multiple models. Models are stored in a dedicated folder that can be relocated if needed.

Internet connection is required for installation and the first time you run a model, as the software must download the model files. After that, you can use Ollama offline. Internet speed affects how long the initial download takes—a model might take 5 minutes on a fast connection or 30 minutes on slower speeds.

Processor speed also impacts performance. A modern multi-core processor (Intel i5/i7 or AMD Ryzen 5/7 from the last few years) works well. Older processors will function but may be slow. The number of cores helps—a 6-core or 8-core processor processes faster than a 2-core processor.

Practical takeaway: Check your RAM (8GB minimum), storage (50GB recommended), and whether you have an NVIDIA GPU or Apple Silicon before installing. If you have less than 8GB RAM or limited storage, you can still use Ollama, but with smaller models and slower performance.

Installation Steps for Different Operating Systems

Installation differs slightly depending on whether you use Windows, macOS, or Linux. Each process takes less than 10 minutes and involves obtaining the installer and running it.

For macOS: Visit ollama.ai (the official website) and look for the macOS version. Click the button to download the installer file. Once downloaded, open the DMG file in your Downloads folder. Drag the Ollama icon to the Applications folder. This copies the application to your computer. After copying completes, open Applications folder and double-click Ollama to launch it. The application will add itself to your menu bar at the top of the screen. The first launch might take a moment as the system prepares the environment.

For Windows: Visit ollama.ai and select the Windows installer. This downloads an .exe file. Double-click the installer file and follow the prompts. Windows may ask if you want to allow this application to make changes to your device—click yes. The installer will place Ollama in your Program Files folder and create a Start Menu shortcut. After installation completes, you can launch Ollama from your Start Menu or by searching for "Ollama" in Windows Search. On first launch, Windows may briefly show a setup screen.

For Linux: Ollama provides a curl command on their website that you can copy and paste into your terminal. Open a terminal window and paste the command, then press Enter. This command downloads and installs Ollama automatically. You may need to enter your password if prompted. After installation, type "ollama" in the terminal to verify the installation worked. Linux users can also build from source if they prefer, but the curl method is simpler for most people.

GPU Driver Installation: If you have an NVIDIA graphics card, you may need to install NVIDIA CUDA drivers before Ollama can use your GPU. Visit NVIDIA's website and search for CUDA downloads. Select your operating system and follow their instructions. This is only necessary for NVIDIA cards; Apple Silicon and AMD GPUs are handled differently. After installing CUDA drivers, restart your computer before running Ollama.

Verification: After installation, open a terminal (macOS/Linux) or command prompt (Windows) and type "ollama --version" then press Enter. This shows the installed version number, confirming the installation was successful.

Practical takeaway: Installation is straightforward—download the installer for your operating system, run it, and follow the prompts. If you have an NVIDIA GPU, install CUDA drivers first. Verify the installation works by checking the version number in your terminal or command prompt.

Pulling and Running Your First Model

After installing Ollama, the next step is obtaining a model. "Pulling" a model means downloading it from the Ollama repository. The repository contains dozens of open-source models ready to use. Each model has different characteristics, sizes, and capabilities.

To pull your first model, open a terminal (macOS/Linux) or command prompt (Windows) and type "ollama pull llama2" then press Enter. This command downloads the Llama 2 model, which is a good starting point for most users. The download may take several minutes depending on your internet speed—the model is approximately 3.8 gigabytes. You will see a progress indicator showing the download status.

After pulling completes, run the model by typing "ollama run llama2" and pressing Enter. This starts the model and opens an interactive chat interface. You can now type questions or prompts and receive responses. Type your message and press Enter. The model will process your input and generate a response. This first response might take 10-30 seconds depending on your hardware.

Other popular models you can pull include Mistral (type "ollama pull mistral"), Neural Chat (type "ollama pull neural