Ollama
Run, manage, and serve open-source language models locally on macOS, Windows, Linux, and Docker.
Bundles model weights, execution, and custom prompts into a local CLI service and HTTP API.
Ollama lets you run open-source large language models locally on your machine or server. It provides a simple CLI and local REST API to serve models like Gemma, Qwen, and DeepSeek. Software developers should use it to integrate local AI into their applications, IDEs, and agent workflows.
What it is
Ollama packages open LLM weights and configurations into reusable Modelfiles powered by llama.cpp. It exposes a localhost REST endpoint along with official Python and JavaScript libraries for direct application integration. You can also launch dedicated CLI bindings to bridge local models directly with agent frameworks like Claude Code or Copilot.
Who it's for
It suits developers and team leads who need local, offline LLM inference for coding tools and private API endpoints. It does not suit engineers who lack local GPU memory or need hosted enterprise-scale inference without managing hardware resources. It is also less ideal if you rely exclusively on proprietary cloud model APIs.
Key features
One-command model execution
Downloads weights and starts local chat sessions with a single terminal command.
Built-in developer HTTP API
Exposes local HTTP endpoints for chat and text completion.
CLI coding integrations
Launches direct bindings for tools like Claude Code and Copilot CLI.
Custom Modelfile configuration
Defines system prompts, parameters, and base weights in reproducible configuration files.
Up and running in 3 steps
Our honest verdict
What's great
- Direct launcher integrations for developer tools like Claude Code, OpenCode, and Copilot CLI.
- Exposes a local REST endpoint with official Python and JavaScript client SDKs.
- Uses llama.cpp as a backend for CPU and GPU quantized inference.
- Provides native installers for macOS, Windows, Linux, and Docker containers.
Where it falls short
- Requires significant local RAM or GPU VRAM to run large model parameters effectively.
- Does not offer a native built-in graphical interface out of the box.
- Model context length and response generation speed depend entirely on your hardware.
- Running high-performance models locally increases host machine power consumption and hardware stress.
Pricing & license
Ollama is completely free and open source under the MIT licence. There are no paid hosted tiers provided in the repository, so your only costs are the hardware and electricity needed to host models yourself.
Open remote AI-training roles
874 open remote AI-training roles, updated November 15, 2026; most pay $20–$170 an hour. Zekai lists them free; the application goes to the employer’s platform.
Alternatives
These reviewed AI tools do the same job instantly — from our scored directory.
Use it, or have us set it up
FAQ
Does Ollama include a web interface?
No, Ollama runs as a background service and CLI tool, though community projects like Open WebUI connect to its REST API.
Which engine powers Ollama under the hood?
Ollama uses llama.cpp to manage model execution and quantization.
