
What "on-device AI" actually changes on a phone
Manufacturers now market local model execution as a headline feature. The honest version is narrower: it changes latency, privacy exposure and battery behaviour — not capability across the board.
Capability, data handling and price, assessed on identical task sets across providers.
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Nothing published until testing is finished.
We run every assistant through the same fixed task set — summarisation, reasoning, code, retrieval and refusal behaviour — and record the outputs so the comparison is reproducible. Data handling is weighted equally with capability: what is retained, what trains the model, and what a business tier changes.
This guide is in the research stage. We will not list a "best" product before the testing round behind it is complete — an unranked page is more useful than a ranked guess. When picks go live, each one will state what we tested, how long for, what it is good at, and who should buy something else instead.
Written down before any product is considered.
We write down what would make a product the right pick — and how each criterion is measured — before we look at what is on sale.
Anything we state about a product comes from our own testing or from the manufacturer's published documentation, linked on the page.
Where a category can be tested, we test it over weeks rather than an unboxing session, and we publish the conditions we tested under.
We do not print a price we have not verified, and we do not treat an RRP as evidence of a discount.
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The full process is documented in our review methodology and testing process.

Manufacturers now market local model execution as a headline feature. The honest version is narrower: it changes latency, privacy exposure and battery behaviour — not capability across the board.
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