The current landscape of artificial intelligence interactions includes cloud-based tools like ChatGPT and Copilot, but some users, especially developers, prefer running large language models (LLMs) locally. Ollama provides a solution for this preference. To run LLMs effectively, hardware requirements include a GPU, with larger models needing more computational power. For example, Google's Gemma 3 has a 1 billion parameter model requiring 2.3GB of VRAM and a 4 billion parameter version needing over 9GB. Meta's Llama 3.2 has similar requirements. A modern PC with at least 8GB of RAM and a dedicated GPU can utilize Ollama.
To install Ollama on Windows 11, users download the installer from the official website or GitHub and follow the installation process. Once installed, it operates in the background, indicated by an icon in the taskbar, and can be accessed via localhost:11434 in a web browser. Ollama primarily uses a command-line interface (CLI), requiring users to use PowerShell or WSL. Key commands include "ollama pull" to install LLMs and "ollama run" to execute them. For instance, to install the 1 billion parameter Google Gemma 3 LLM, users would enter "ollama pull gemma3:1b". Running the models opens a chatbot interface for user interaction, and exiting can be done by typing "/bye". Setting up Ollama is user-friendly and requires minimal technical expertise.