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On-device AI

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D3 · Prompts, context, RAG, tools and agents

On-device AI executes AI inference on a local device, such as a phone or computer.

Review status: 2026-12-05

Technical explanation

A compatible model and runtime use the device’s available compute and memory.

Conceptual boundaries

The term identifies where inference runs. It does not imply that every part of the application is offline or that no data is transmitted.

Provider-neutral example

Illustrative: a note-taking app generates a draft summary with a locally installed model.

Limitations

A supported runtime or a successful phone demonstration does not establish compatibility with every device.

Related concepts

Atomic claims and evidence

  1. 1.1Google AI Edge: LiteRT-LM
    Source
    Google AI Edge: LiteRT-LM
    Source role
    Authoritative source
    Exact locator
    Run LLMs on-device with LiteRT-LM; Cross-platform; Hardware accelerated
    Supported claim
    Google documents LiteRT-LM for running language models on devices across mobile and desktop platforms.
    Last verification
    Review due
    Scope limitation
    This is one runtime’s scope, not a promise about all AI applications.
  2. 2.1Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
    Source
    Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
    Source role
    Authoritative source
    Exact locator
    Abstract: 3.8B phi-3-mini, phone deployment, and 7B phi-3-small
    Supported claim
    The Phi-3 report describes a model small enough for phone deployment.
    Last verification
    Review due
    Scope limitation
    This is a particular model demonstration, not evidence that all small models fit all phones.