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How to use Ollama: what you can do with it

Ollama runs open models such as Gemma, Qwen, DeepSeek, Kimi and gpt-oss locally or in the cloud, with a CLI, a local REST API and official Python and JavaScript libraries.

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3 use cases

Quick start with Ollama

  1. Check you have what it needs: macOS, Windows, Linux or Docker; Enough RAM or VRAM for the model you pick.
  2. Open ollama/ollama on GitHub and read the README and license.
  3. Install with curl -fsSL https://ollama.com/install.sh | sh (or irm https://ollama.com/install.ps1 | iex on Windows)
  4. Run ollama run gemma4
  5. Chat in the terminal
  6. Try other models from the library

These steps come from our top use case, Run an open model on your machine in one command, which also has a copy-paste agent prompt.

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Requirements

  • macOS, Windows, Linux or Docker
  • Enough RAM or VRAM for the model you pick

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Questions about Ollama

What is Ollama?

Ollama runs open models such as Gemma, Qwen, DeepSeek, Kimi and gpt-oss locally or in the cloud, with a CLI, a local REST API and official Python and JavaScript libraries. It is an open-source project on GitHub: https://github.com/ollama/ollama.

Who is Ollama for?

Developers and tinkerers who want to run open models on their own machine and call them from code.

What can I do with Ollama?

3 use cases so far, for example: Run an open model on your machine in one command; Call a local model from Python or JavaScript; Launch a coding agent backed by Ollama. Each has steps and a copy-paste agent prompt.

What do I need to run Ollama?

macOS, Windows, Linux or Docker; Enough RAM or VRAM for the model you pick.

What are alternatives to Ollama?

Other hot AI repos in Software and DevOps: Deep Infer, Harness2, Orca, Opencode, Graphify.

Is Ollama safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.