PocketBrain guide
Offline AI vs Cloud AI: Privacy, Performance and Tradeoffs
Understand the practical differences between offline AI and cloud AI, including connectivity, device limits, and data flow.
Two different delivery models
Cloud AI typically sends a prompt to a remote service. Offline AI uses a model installed on the device for compatible local work. The distinction matters for connectivity, storage, and how a workflow is designed.
Privacy and data flow
Local execution can keep compatible chats and workspace work on the device. It does not remove the need to understand model sources, permissions, or links you choose to open.
Performance and limits
Device hardware and model size influence local AI. Offline AI is not offline-everything: model downloads and external links still need a connection.
Choosing a workflow
Use the model and workflow that fit the task, device, and connectivity you have. PocketBrain is designed around compatible on-device models and has no cloud chat backend.
Learn more about offline AI in PocketBrain, local model management, PocketBrain features, and how PocketBrain works.