Ollama

Ollama is an open-source server application that allows users to run and manage large language models locally. It provides a streamlined environment for deploying open models on macOS, Windows, and Linux desktops, as well as via Docker containers. The software functions as a backend that handles model orchestration and inference, enabling users to interact with AI models through a command line interface or integrated applications.

Typical use cases include local chat interactions, integrating AI into development workflows, and building custom agents. The application supports a wide variety of open models, including Llama, Gemma, Mistral, and Qwen. It is designed to operate as a local service that can be accessed by other software via a standardized interface, ensuring that model weights and data remain on the local machine.

Key features

• Local execution of large language models on desktop operating systems
• REST API for running and managing models programmatically
• Official libraries for Python and JavaScript integration
• Support for multiple open model families including Llama 3 and Gemma 4
• Docker image availability for containerized deployment
• Command line interface for model launching and chatting
• Integration capabilities with external AI agents and coding tools
• Backend support powered by the llama.cpp project

The architecture relies on the llama.cpp project for model inference. It is intended for developers and AI enthusiasts who require local control over their models for privacy, security, or offline development purposes. Because it exposes a REST API, it serves as a foundation for a vast ecosystem of community-built chat interfaces, IDE extensions, and RAG frameworks. It integrates with various SDKs across multiple programming languages, including Go, Rust, Java, and Swift, allowing it to be embedded into diverse software stacks.

Beyond simple chat, the software supports specialized integrations for coding assistants and personal AI agents. It can be connected to tools like Claude Code, OpenCode, and various RAG engines to process local documents. This flexibility allows users to build complex AI pipelines while maintaining the compute on their own hardware.

Ollama positions itself as a local compute platform and AI gateway for managing open-source generative AI models.