Local or cloud AI: differences in privacy and cost

This text compares two ways of running an AI model, on your own computer or phone (local) or on a company's servers, accessed through the internet (cloud), looking closely at two points: what happens to your data and what each option costs. The other criteria appear as context.

Criteria for comparison

• Privacy. With local AI, data stays on your device. In the cloud, what you send is processed by the service, subject to its policy.
• Cost. Local may require a powerful device but does not charge per use. In the cloud, the cost can come as a subscription or by volume.
• Performance. Cloud services usually offer the larger, more capable models. Local models tend to be smaller, and capability depends on your hardware.
• Ease. The cloud works without setup. Local options require installation and some technical familiarity.
• Connection. Local AI may work without internet; cloud AI depends on it.
• Maintenance. In the cloud, updates come automatically. Locally, you handle that.

Pros and limits

Local AI

Pros: more control over data, offline use and no charge per use. Limits: requires adequate hardware, tends to have less powerful models and demands setup.

Cloud AI

Pros: access to advanced models, ease and constant updates. Limits: sending data to third parties, dependence on internet and recurring cost.

Alternatives

There are middle-ground solutions: cloud services with options not to use your data for training, business plans with contractual guarantees and local models used for simple tasks, leaving the cloud for complex ones.

An example

A law firm wanted to summarize documents with sensitive information. It chose a local model for confidential texts, accepting somewhat lower quality, and used a cloud service only for tasks without sensitive data. This is an illustrative example.

Before you decide

In any case, read the privacy policy and avoid sending information you cannot share.