Ollama

Ollama is an open-source tool that lets developers and individuals run large language models (LLMs) directly on their own hardware — macOS, Windows, or Linux — with a single install command. Built primarily in Go and released under the MIT License, it backs its local inference engine with llama.cpp and exposes a REST API and CLI for integrating models into applications. An optional cloud tier extends local usage to datacenter-grade hardware when larger or faster models are needed.

What It Is

Ollama is a local inference runtime that downloads, manages, and serves open models through a unified interface. It sits between the raw model weights and the applications or agents that consume them, handling model lifecycle (pull, run, delete), serving a local HTTP API compatible with many LLM frameworks, and optionally routing requests to Ollama's own cloud infrastructure. The core platform is open source (MIT), while the cloud layer is a hosted commercial service layered on top.

Open-Source Architecture

The GitHub repository (ollama/ollama) is written in Go and uses llama.cpp as its primary inference backend. As of the latest release (v0.24.0, published May 14 2026), the project has accumulated over 171,000 GitHub stars and more than 16,000 forks, making it one of the most-starred local LLM projects on GitHub. The MIT license allows unrestricted use, modification, and redistribution. Models are defined via a Modelfile format, and the REST API follows a straightforward chat/generate pattern compatible with many existing LLM SDKs.

Supported Models and Integrations

Ollama's model library includes Gemma 3, DeepSeek, Qwen, Mistral, Llama 3, GLM, MiniMax, Kimi-K2.5, gpt-oss, and many others. The GitHub README lists over 40,000 community integrations spanning:

• Chat interfaces: Open WebUI, LibreChat, Lobe Chat, AnythingLLM, and others
• Code editors: VS Code (via Continue, Cline, AI Toolkit), Emacs, Sublime Text, Qt Creator
• Frameworks and agents: LangChain, LlamaIndex, Spring AI, crewAI, AutoGPT, Semantic Kernel, Firebase Genkit, Haystack
• Languages: Python, JavaScript, Ruby, Rust, Go, Java, .NET, Swift, PHP, Dart, Elixir, R, Julia, C++
• Coding agents: Claude Code, Codex, Copilot CLI, OpenCode, OpenClaw, Droid
• RAG engines: RAGFlow, R2R, LlamaIndex, and others
• Observability: Langfuse, OpenLIT, MLflow Tracing, Opik, Lunary

The ollama launch command can directly start integrations like OpenClaw, Claude Code, or Codex against a locally running model.

Local-First, Cloud-Optional Deployment

Ollama's design philosophy is "start local, scale with cloud." Running models on local hardware is always unlimited and fully offline-capable. The cloud layer — powered by NVIDIA Cloud Providers (NCPs) — adds access to larger models on datacenter hardware, parallel request handling, and real-time web access. Ollama states that prompt and response data is never logged or trained on, and that NCP partners are contractually required to enforce no-logging and zero data retention policies. Cloud models are hosted primarily in the United States, with additional capacity in Europe and Singapore.

Update: v0.24.0

The latest release is v0.24.0, published May 14, 2026. The repository remains actively maintained with pushes as recent as May 19, 2026. The project direction shows continued expansion of cloud model support alongside the core open-source local runtime, with the homepage prominently featuring the OpenClaw integration as a flagship use case for turning Ollama into a personal AI assistant across WhatsApp, Telegram, Slack, and Discord.