ollama/ollama
Get up and running with Kimi-K2.5, GLM-5, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
Ollama is an open-source local LLM runner by the Ollama team that lets you download and run 50+ AI models on your own hardware with a single command. With 168,000 GitHub stars and 52 million monthly downloads, it is the most widely adopted tool for private, zero-cost AI inference in 2026.
Our Review
Ollama is the most popular local LLM runtime in the developer ecosystem -- 168,000 GitHub stars and 52 million monthly downloads as of April 2026. Built in Go and released under the MIT license, it turns running open models into a one-liner.
What Ollama does:
- •One-command model running
ollama run gemma3downloads and launches any supported model instantly. No config files, no environment setup. - •50+ model library run Llama 3, Gemma 3, DeepSeek, Qwen, Mistral, Kimi-K2.5, GLM-5, MiniMax, and more from ollama.com/library.
- •REST API on localhost every running model exposes an OpenAI-compatible API at localhost:11434 for integration into any app.
- •Python and JavaScript SDKs official ollama-python and ollama-js libraries for building applications on top of local models.
- •Agent integrations launch Claude Code, Codex, OpenClaw, and Droid directly from the Ollama CLI with
ollama launch claude. - •Cross-platform install one-line scripts for macOS, Windows (PowerShell), Linux (apt/rpm/flatpak), and Docker.
Ollama ecosystem:
- •Open WebUI the most popular web interface for Ollama, with RAG, voice input, and multi-model chat.
- •Claude Code + Codex Ollama serves as the local model backend for AI coding agents.
- •OpenClaw turns Ollama into a personal AI assistant across WhatsApp, Telegram, Slack, and Discord.
- •Dify, AnythingLLM, Cherry Studio desktop and enterprise platforms that connect to Ollama for private inference.
Getting started:
Install with curl -fsSL https://ollama.com/install.sh | sh (macOS/Linux) or irm https://ollama.com/install.ps1 | iex (Windows). Run your first model with ollama run gemma3. Full docs at docs.ollama.com.
Limitations:
Performance depends on local hardware -- running large models (70B+) requires a dedicated GPU with 48GB+ VRAM. No built-in web UI (use Open WebUI separately). No cloud hosting option from Ollama itself -- it is local-only by design. Community support via Discord and Reddit, no enterprise support tier.
Our Verdict
Ollama is the standard runtime for running open AI models locally in 2026. If you need private, zero-cost inference on your own machine -- for development, testing, or production -- Ollama is where most developers start.
For Vibe Builders, Ollama pairs with tools like Claude Code and Open WebUI to create a fully local AI stack without touching an API key or paying per token. The ollama launch claude integration means you can start coding with AI in minutes.
For Developers, the REST API at localhost:11434 and official Python/JavaScript SDKs make Ollama the fastest path to embedding local models into applications. The OpenAI-compatible API means existing code works with minimal changes.
Skip if you need managed cloud inference, a built-in web UI, or enterprise-grade SLA support. For GUI-first workflows, LM Studio offers a better visual experience. For high-throughput production serving, vLLM provides better batching and memory management.
Frequently Asked Questions
What is Ollama and what does it do?
Ollama is an open-source local LLM runner that lets you download and run AI models on your own hardware with a single command. Built by the Ollama team in Go and licensed under MIT, it supports 50+ models including Llama 3, Gemma 3, DeepSeek, and Qwen. As of April 2026, Ollama has 168,000 GitHub stars and 52 million monthly downloads, making it the most widely used local AI runtime.
Is Ollama free and open source?
Ollama is completely free and open source under the MIT license. There are no usage fees, no per-token charges, and no subscription required. All inference runs on your local hardware at zero cost. The source code is publicly available on GitHub at github.com/ollama/ollama.
How does Ollama compare to LM Studio?
Ollama is CLI-first and developer-focused -- ideal for scripting, automation, and embedding into applications via its REST API and SDKs. LM Studio is GUI-first and designed for visual model exploration and prompt testing. Choose Ollama when you need programmatic access, Docker deployment, or integration with coding tools like Claude Code. Choose LM Studio when you want a visual interface for discovering and testing new models from Hugging Face.
What hardware do I need to run Ollama?
Ollama runs on macOS, Windows, and Linux. For small models (7-8B parameters), 8GB RAM and a modern CPU are sufficient. For larger models (13-34B), 16-32GB RAM and a GPU with 8-16GB VRAM dramatically improve speed. Ollama delivers 300+ tokens per second on consumer GPUs. The largest models (70B+) require 48GB+ VRAM on a dedicated GPU like the NVIDIA A6000 or dual consumer GPUs.
How do I get started with Ollama in 2026?
Install Ollama with one command: `curl -fsSL https://ollama.com/install.sh | sh` on macOS or Linux, or `irm https://ollama.com/install.ps1 | iex` on Windows. Then run `ollama run gemma3` to download and start chatting with your first model. For coding, run `ollama launch claude` to connect with Claude Code. Full documentation is at docs.ollama.com.
What is ollama?
Ollama is an open-source local LLM runner by the Ollama team that lets you download and run 50+ AI models on your own hardware with a single command. With 168,000 GitHub stars and 52 million monthly downloads, it is the most widely adopted tool for private, zero-cost AI inference in 2026.
What license does ollama use?
ollama uses the MIT license.
What are alternatives to ollama?
Explore related tools and alternatives on My AI Guide.
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