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CUPERTINO, California—Apple announced earlier this year that its long-delayed Siri upgrade, announced this week as “Siri AI,” would use Google’s Gemini language models. What the company confirmed at its Worldwide Developers Conference yesterday was that it also ran on Nvidia hardware installed in Google servers. But the company is still making the same privacy promises it did before, when all of its AI models were either running locally on your devices or on Apple-controlled server hardware.
For years, Apple has touted user privacy as a key benefit of using its platforms. Its cloud services use encryption that’s intended to keep other people—including Apple employees—from being able to gain access to it. And the company has long advertised its use of on-device processing for things like scanning images, keeping as much data as possible from leaving your device in the first place.
But with Apple Intelligence, Apple has run up against the limits of its own hardware. The kinds of language and reasoning models that can run locally on an iPhone or Mac are relatively small, limiting their capabilities and accuracy. Apple’s Private Cloud Compute system was a partial solution but relied on Apple’s own server hardware; to get the kind of capacity it would need to support Siri AI, Apple would have had to commit to a huge data center buildout that it has so far avoided.
Apple’s Craig Federighi and other Apple executives got on a smaller stage after the WWDC keynote to explain to the press and other media how it planned to preserve user privacy while still getting the kind of compute capacity it needed and what its partnership with Google meant.
Taking Private Cloud Compute on the road
“This is the amount of the Google Assistant we use, which is none,” says Federighi, standing in front of a blank slide in a much more intimate theater than the giant outdoor auditorium where he had introduced CEO Tim Cook a couple of hours before.
Federighi has just outlined a “traditional chatbot architecture”—a client app running on your device that reaches out to cloud-based models running on third-party servers. Those models can then reach out to Google Search or something similar “to [ground themselves] in world knowledge.”
Apple’s system still depends on an on-device model for simpler queries. In this year’s OS releases, most Apple Intelligence devices get AFM 3 Core, a new Gemini-based model co-developed by Google and Apple. Newer devices with at least 12GB of RAM and a relatively recent chip (M3 and newer for Macs, M4 and newer for iPads, just the A19 Pro for iPhones) use AFM 3 Core Advanced instead, which leverages the extra hardware as well as your device’s storage to function (it’s used to improve dictation and power Siri’s more expressive voice).
For “more sophisticated” questions, your device will contact cloud-based models, again co-developed by Apple and Google: a general-use model called AFM 3 Cloud, an image-generation model called ADM 3 Cloud, and an advanced model called AFM 3 Cloud Pro for “agentic tool use and complex reasoning.” The first two models, Apple says, still run on Apple’s silicon on Apple’s servers. The Cloud Pro model is the one running on Google-owned Nvidia hardware.