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Appofficial publisher

Ollama

App : A product you use directly

Run an open-weight model in one command, with a local OpenAI-compatible API.

The de facto standard for running models locally and connecting them to other tools.

Official site GitHub · 184,673 ★
Overall score
9.7 /10
Security: nothing to flag
Utility
9.5
Reliability
10.0
Security
No caveat on record
Ease
1 click · Comfortable

Security reflects where data goes, requested permissions and incidents on record at the verification date. It is not a guarantee of zero risk: check the deployment mode and the connections you enable.

What it does, concretely

Running a language model locally usually requires setting up Python environments, managing dependencies, and understanding complex file formats. Ollama reduces all of this to a single command in the terminal.

In practice, you install Ollama on your machine, then launch a model such as Gemma 4 or DeepSeek with the command ollama run model-name. Ollama downloads the model, loads it into memory, and exposes a local REST API on port 11434, compatible with the OpenAI format, making it possible to connect it to existing tools without changing their code.

Ollama is aimed at developers who want to integrate a local model into their projects, at users concerned about data privacy, and at anyone who wants to experiment with open-weight models without relying on a cloud service. Official libraries are available in Python and JavaScript.

However, Ollama is not suited to users looking for a ready-to-use graphical interface: the tool is primarily command-line. For a web interface, a third-party tool such as Open WebUI needs to be added.

What it offers

  • ·Launch an open-weight model with a single command (ollama run model-name).
  • ·Local REST API on port 11434, compatible with the OpenAI format, usable from any application.
  • ·Official libraries for Python (pip install ollama) and JavaScript (npm i ollama).
  • ·Launch third-party integrations with one command, for example Claude Code, Codex, or Copilot CLI (ollama launch claude).
  • ·Docker deployment with the official ollama/ollama image available on Docker Hub.
  • ·Model library browsable at ollama.com/library, including Gemma 4 and DeepSeek.
  • ·Compatibility with a wide ecosystem of web interfaces, code editors, and agent frameworks via the local API.
  • ·Cloud usage with hosted models in the US, Europe, and Singapore, with no training on your data (paid depending on usage level).

In practice

Price
Free
Commercial use
Commercial use: yes
Available on
macos, windows, linux, cli
Licence
MIT

Security and data

Rating
Security: nothing to flag
Your data
Local or cloud depending on use
Maintenance
Active
Last release
24 October 2026

Links and repository checked on 25 October 2026 · added on 1 July 2023

How to install Ollama

1. Download and install Ollama for your system (macOS, Windows, or Linux) from ollama.com or via the command-line install script. 2. On macOS and Linux: curl -fsSL https://ollama.com/install.sh | sh 3. On Windows: irm https://ollama.com/install.ps1 | iex 4. Once installed, launch a model with ollama run gemma4 (or any other model available at ollama.com/library). 5. The REST API is then accessible locally at http://localhost:11434. 6. Never expose this port on the Internet without authentication.
curl -fsSL https://ollama.com/install.sh | sh

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