Why 8.5/10: Top pick for local LLMs: free, MIT-licensed, very widely used, and the simplest route from install to a running model with a local API. Points off for limited low-level tuning compared with llama.cpp and for a growing paid cloud side that blurs the 'local' message.
By ToolSift editorial. Last checked . Prices change often; "check site" means verify with the vendor.
What it does
Ollama is a desktop tool and command-line runner for open-weight language models. You install it on macOS, Windows or Linux, run a command such as `ollama run` with a model name, and it downloads and runs the model locally. It also exposes a local HTTP API (documented at docs.ollama.com), which is why so many tools, from editors to chat front ends and automation platforms, list Ollama as a model provider.
Its homepage says Ollama gives access to the latest open models "with complete privacy locally or in the cloud" and that prompts are never stored or trained on. It reports 9M+ monthly installs and 1B+ model downloads. The ollama/ollama GitHub repository had about 184,000 stars on 19 Oct 2026, an MIT licence and a latest release of v0.40.6 (16 Oct 2026).
Ollama now also runs larger open models in its cloud. The pricing page lists a Free tier that includes running models locally plus starter cloud credits, and paid plans with monthly usage credits for larger "pro" models, with per-million-token prices for each cloud model and off-peak discounts.
Against our runners-up: LM Studio offers a polished graphical app for downloading and chatting with local models, which suits people who don't want a terminal; llama.cpp is the low-level engine for maximum control and performance tuning. Ollama sits between them: a one-command install, a simple model library and an API that other software already speaks, which is why it is often the default 'local model' option in other tools.
Our verdict
Ollama is the simplest way to run open models on your own machine. Install it, pull a model with one command, and you have a chat in the terminal and a local API that many apps already support. It is free and MIT-licensed. In 2026 Ollama also added cloud models with usage credits and paid plans, but running models locally remains free. Pick it to get local models working in minutes. Choose llama.cpp if you want maximum low-level control, or LM Studio if you prefer a graphical app.
✅ Pick it if You want local models working in minutes and an API your apps can call, at no cost.
⛔ Skip it if You want maximum low-level tuning, or a purely graphical workflow without the command line.
Pricing: As of 19 Oct 2026 (USD): local use free (MIT licence). Cloud: Free $0 (run models locally, starter usage credits, starter models); Pro $20/month or $200/year ($60 of usage credits a month, larger pro models, multiple models at once); Max $100/month ($300 of usage credits a month, early access to the newest models, 10 concurrent requests); Team $500/month in early access (unlimited users, $1,000 of shared credits); Enterprise custom. Cloud models are pay-as-you-go per million tokens beyond included credits. Check site.
Ollama is developed by Ollama, Inc.; the code is public on GitHub under the MIT licence.
What to watch
Hardware decides what you can run: bigger models need lots of RAM or VRAM. Start with small or quantised models on laptops.
Local vs cloud: cloud models send prompts to Ollama's servers (which it says are not stored or trained on). If you need data to stay on your machine, make sure you're running a local model.
Model licences vary: Ollama is MIT, but each model has its own licence. Check it before commercial use.
Less fine control than llama.cpp for advanced quantisation and inference flags.
Exposing the API: by default it listens locally; if you open it to a network, add authentication in front, since the local API has none built in.