The Information reports that Apple will use a licensed version of Google's Gemini model in Google Cloud for some queries to the new Siri, and that Apple recently approved the use of Nvidia confidential compute for that cloud processing, according to Aaron Tilley reporting for The Information. The Information also reports that Apple is "using a version of Google's large Gemini model to train a smaller version of the model that can run locally on Apple devices, a process known as distillation." Fortune reported on Jan 13, 2026 that the Apple-Google deal validates Gemini and has major industry implications, while financial terms and the deal duration remain unclear. Industry context: observers view the tie-up as a validation for Google Cloud and Gemini, and a shift in the supplier mix for mobile AI infrastructure.
What happened
Per reporting by The Information, Apple will run some user queries to a new Siri in Google Cloud on a licensed version of Google's Gemini model, and Apple has approved the use of Nvidia confidential compute in that setting, Aaron Tilley reports. The Information quotes sources saying Apple is "using a version of Google's large Gemini model to train a smaller version of the model that can run locally on Apple devices, a process known as distillation." The same reporting says the full Gemini model contains trillions of parameters and requires more compute than Apple's internal Private Cloud Compute has been able to handle.
Technical details
Per The Information, Nvidia's confidential compute is a security feature inside Nvidia GPUs that encrypts data and AI models while they are processed, and enabling it can slow inference slightly while providing stronger protections for data in use. The Information reports that Apple's decision to allow the technology in Google Cloud is recent, occurring "in recent weeks," according to its sources.
Editorial analysis - technical context
Companies that split workloads between on-device distilled models and larger cloud-hosted foundation models are using a hybrid pattern to balance latency, capability, and privacy constraints. Distillation into smaller local models reduces bandwidth and latency for many queries, while licensing a full Gemini instance in the cloud handles more complex requests that exceed on-device capacity. Confidential compute is emerging as a practical control point for vendors that need to combine third-party cloud compute with privacy commitments.
Context and significance
Fortune reported on Jan 13, 2026 that the Apple-Google agreement is a major validation for Google and Gemini, and that the deal has broader market implications; Fortune also noted that key commercial terms and the agreement duration were not disclosed. Industry observers have framed the tie-up as strengthening Google Cloud's position in mobile AI distribution, per Fortune. The combination of on-device distillation and selective cloud routing, plus the adoption of Nvidia confidential compute, signals a near-term architecture that mixes local models with licensed cloud-hosted foundation models.
What to watch
observers and practitioners will watch for published details at WWDC about how Apple implements local distillation, the scope of queries routed to Google Cloud, the latency and cost tradeoffs of confidential compute, and whether Apple or its partners disclose performance metrics or privacy guarantees for the hybrid architecture. Also monitor vendor disclosures from Google and Nvidia about supported confidential compute workflows and any developer-facing APIs for hybrid on-device/cloud models.
Scoring Rationale #
The story describes a major implementation detail of the Apple-Google partnership that affects mobile AI infrastructure, hybrid deployment patterns, and vendor positioning. It matters to practitioners integrating on-device and cloud models and to architects choosing compute and privacy protections.
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