The Case for On-Device

On-device inference keeps winning territory because three independent pressures point the same way:

• Privacy — data that never leaves the device can't leak in transit, can't be subpoenaed from your server, can't be breached centrally. For health, voice, and personal data, on-device isn't a preference — it's the only acceptable architecture.
• Latency — a round-trip costs whatever the network costs: tens of milliseconds on a good day, unbounded on a bad one. Interactive features have hard deadlines; a UI that must respond in a frame budget can't route through a datacenter.
• Cost — cloud inference bills you per query forever; on-device runs on silicon the user already owns. At scale, the difference between 'we pay per inference' and 'the user's phone pays' is the difference between a feature and a business model.