Is running AI locally more private, and does it work offline?

The clearest reason to run a model locally is privacy. When the model runs on your own computer, your prompt and the model’s reply never leave your machine. There is no provider in the middle who could store the text, no network request carrying it anywhere. For sensitive material, like medical notes, legal drafts, or unreleased work, that is a meaningful difference.

A cloud API is the opposite by design: your prompt has to travel to the provider for the model to read it. That does not automatically mean your data is misused. OpenAI, for example, states that data sent to its API is not used to train or improve its models unless you opt in, and that abuse-monitoring logs are kept for up to 30 days unless a longer period is required by law.^[1] The point is that the data does pass through someone else’s systems, so you are trusting their policy and their security rather than keeping the information entirely under your own control.

The other local advantage is that it works offline. Once the model is downloaded, it does not need the internet to answer. That matters on a plane, in a location with poor connectivity, or in any setting where sending data outside the building is not allowed. A cloud API, by contrast, simply will not respond if you lose your connection.

The offline property has a privacy angle worth drawing out, not just a convenience one. Even a provider that keeps its promise not to log or train on your prompts still sees that a request happened: its size, its timing, the account it came from. A network positioned between you and the provider, an ISP, a corporate firewall, a compromised router, can see that same metadata even without reading the content, since encryption hides what you sent but not that you sent something, when, and roughly how much. Running locally removes that observation point entirely, because there is no request for anyone in the middle to observe.