Google Chrome is reportedly installing a 4 GB on-device AI model called Gemini Nano on users’ devices without explicit permission, using a folder named OptGuideOnDeviceModel and a weights.bin file to store the model.

A researcher exposes a silent, consentless download of Gemini Nano across user machines, mirroring past stealth, cross-application installs without user consent.

The optics of AI features are scrutinized, with a visible AI Mode pill in the omnibox that can mislead users into thinking processing is entirely local, while some queries may still be processed in the cloud.

Environmental concerns are raised: if half a billion devices download the model, the bandwidth could generate around 30,000 tonnes of CO2, equivalent to thousands of cars’ annual emissions.

A recommended workaround is to disable the on-device download through chrome://flags by turning off Enables optimization guide on device, though the steps are not straightforward.

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Deleting the weights.bin file does not permanently free space if On-Device AI remains enabled, as Chrome may re-download it later.

The model runs locally using on-device training parameters, offering privacy benefits but risking wasted storage on devices with limited space.

Verification across Windows and macOS relies on OS file system events, Chrome’s Local State, runtime feature flags, and updater logs, showing a profile-scoped installation on millions of devices.

The article argues Google should have obtained explicit consent, required user action before downstream downloads, surfaced and allowed removal of downloaded models, documented the feature, respected deletions, disclosed scale and emissions, and offered retrospective consent for existing installations.

Context contrasts AI-enabled browsers and Chrome-related AI features with the on-device model usage discussed in the piece.

Users can check for weights.bin in Chrome’s data folders under OptGuideOnDeviceModel to confirm the download.