What Ollama is
Ollama is an open source tool for running large language models locally. The README summarizes it as a way to start building with open models, with installers for macOS, Windows, Linux, and an official Docker image.
The GitHub description names model families such as Kimi, GLM, MiniMax, DeepSeek, gpt-oss, Qwen, and Gemma. For developers, Ollama provides a local model runtime plus CLI/API so experimentation does not require a new cloud setup every time.
How it is used
A common path is to install Ollama, pull a model from the library, run it through the CLI, then connect an application through the local API or a client library. The README also points to ollama-python and ollama-js.
Ollama CLI shape
The basic workflow is local model pull/run, with client libraries available for apps.
ollama pull gemma3
ollama run gemma3
# client libraries:
# ollama-python
# ollama-jsWhy it matters
Ollama became a convenient entry point for local-first LLM workflows. It lowers the gap between wanting to try a model and actually getting responses on your machine.
Limits
Local models depend on hardware, memory, quantization, context size, and model quality. Ollama simplifies running them, but latency, concurrency, model selection, data safety, and monitoring still need engineering attention.