Ollama

Ollama is an open-source tool for easily downloading and running open LLMs like Llama, Qwen, DeepSeek, and Gemma on your local machine. It packages models like containers so you can call them directly through a local HTTP API on macOS, Windows, and Linux, which fits developers who want to run models in their own environment and teams for whom data control matters.

Its strengths are simplicity and control. A single command pulls an open model and stands it up as a local API server, and because inference happens on your machine, data never leaves it. Being open source, you can self-host and use it freely for commercial purposes, and the API makes it easy to wire into your own applications. In our evaluation its local-execution score of 95 and value-for-money score of 95 sit jointly at the top, reflecting a setup that runs at no software cost once you have your own hardware.

The limits are environmental and linguistic. Inference speed and quality ultimately depend on the hardware you own, so running large models comfortably requires capable gear. Korean support is relatively weak, so for local work you need to choose models that handle Korean well.

In short, it fits developers who prioritize privacy and control and want to run LLMs locally or offline. The software itself is free; you only cover hardware costs. If you instead want top-tier models with no setup or treat Korean quality as the top priority, a commercial cloud LLM is worth considering alongside it.