Skip to content
buildbay.
Ollama logo

Ollama

ollama · Developer platforms

GitHub stars

181,984
—Collecting 30d data

Stats updated

181,806 stars on Sep 27 to 181,984 stars on Oct 1, up 178.5 measured star snapshots

What is Ollama?

Ollama packages model management and inference into a straightforward local runtime. A single command can pull and run a model, while the automatically served API gives developers a consistent way to use the same models from scripts, applications, editors, and self-hosted AI interfaces.

Ollama is an open-source runtime for downloading, running, and building with AI models on macOS, Windows, and Linux. It provides a model library, a command-line interface, a local HTTP API, official Python and JavaScript libraries, and optional access to larger cloud-hosted models through the same tooling.

Core capabilities

  • Runs chat, coding, reasoning, vision, and embedding models locally on macOS, Windows, and Linux.
  • Exposes a local HTTP API plus official Python and JavaScript libraries for application development.
  • Supports model customization, tool calling, structured outputs, embeddings, and OpenAI-compatible integrations.

A model library and runtime for everyday machines

Ollama handles model downloads, storage, execution, and updates behind a compact command-line workflow. Its library includes models for conversation, coding, reasoning, vision, and embeddings, with native applications and hardware acceleration available across supported desktop and Linux environments.

  • macOS
  • Windows
  • Linux
  • local inference

A consistent API for building with models

The runtime serves an HTTP API by default and has official Python and JavaScript clients. Applications can generate text, chat with message history, create embeddings, accept images with multimodal models, call tools, and constrain responses with JSON schemas; an OpenAI-compatible endpoint helps existing integrations connect with fewer changes.

  • REST API
  • Python
  • JavaScript
  • OpenAI compatibility

Where it fits

Use cases

  1. 01

    Private local AI on a personal computer

    Download and run supported models on a Mac, Windows PC, or Linux machine, keeping prompts and inference close to the applications and data that use them.

  2. 02

    An API backend for AI applications

    Use the local REST API or official Python and JavaScript libraries to add chat, generation, embeddings, vision, structured responses, and tool calls to an application.

  3. 03

    Custom and specialized model workflows

    Create repeatable model configurations with Modelfiles, choose models for coding or reasoning, and connect existing software through Ollama or OpenAI-compatible endpoints.