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Local & Self-hosted AI

Ollama

Ollama is a public, MIT-licensed Go project that provides a local or containerized runtime for running and building with open language models. It supports macOS, Windows, Linux, and Docker, and documents API availability.

Independent OpenViST project profile, based on linked sources.

Ollama — OpenViST project profile in Local & Self-hosted AI.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Ollama when local or self-hosted model execution is central to the project, including development, experimentation, containerized serving, and application integration.

Who it is for

  • Developers building applications with open language models
  • Teams exploring self-hosted assistants for document or code workflows
  • Users testing different models locally or in containers
  • Engineers adding a language-model service to an application backend

Documented uses

  • Run open language models on a local computer
  • Serve models through a containerized environment
  • Build a local chat application
  • Prototype assistants for private document or code workflows
  • Test and switch among supported model families
Before you choose

Requirements & limits

The project is available as a public repository. Its source code is licensed under MIT.

  • Whether the required model is among the documented ecosystems, including DeepSeek, Gemma, GLM, GPT-OSS, Llama, MiniMax, or Qwen
  • Whether the project should run locally or through Docker
  • Whether an API is needed for application integration
  • Whether an MIT-licensed, public open-source project fits the implementation

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Evidence and transparency

Sources & review

Source record details
Source availability
Active
Sources checked
30 September 2026
Original website title
ollama/ollama · Official homepage title · retained in its source language