How a Go wrapper around llama.cpp became local LLM infrastructure

What it does

Ollama is a Go runtime that fetches, manages, and runs open-weight LLMs on local hardware. It packages model downloading, a conversational CLI, and a REST API into one binary, letting you replace remote endpoints with your own CPU or GPU. The tool also plugs into existing developer workflows—Claude Code, Copilot CLI, Codex, and others—routing their inference requests to your machine instead of the cloud.

The interesting bit

The README feels more like a census than a project page: dozens of third-party chat UIs, editors, mobile apps, and language SDKs all list Ollama as their default local backend. That ubiquity suggests its real value is not the binary, but the interoperability layer it built on top of llama.cpp.

Key highlights

• Local REST API for chat and model management, consumed by official Python and JavaScript libraries and a sprawling list of community integrations
• CLI supports direct model chat and launching integrations with coding assistants and AI tools
• Cross-platform runtime for macOS, Windows, and Linux, distributed as a native binary and Docker image
• Model library includes Gemma, DeepSeek, Qwen, Llama, and others
• Inference engine is llama.cpp

Verdict

Grab it if you want to experiment with open models locally or wire them into editors without managing API keys. Pass if you need managed scaling or have no use for on-premise inference.