Apple is borrowing Google’s biggest brain to reboot Siri – and the size of that brain is staggering. Multiple reports indicate that Apple will lean on a customized version of Google’s Gemini with roughly 1.2 trillion parameters to power the most demanding parts of Siri’s makeover. 
It’s a pragmatic move that blends on-device intelligence with carefully fenced cloud processing, and it tells us a lot about where Apple thinks consumer AI must go next: faster, more reliable, privacy-preserving – and immediately useful.
Why Apple is tapping Google now
Apple has been building its own models, but the company also needs a bridge to deliver complex features at scale. Internally, the Siri overhaul carries the codename Glenwood and is being pushed by leaders including Mike Rockwell and Craig Federighi. During development Apple reportedly evaluated OpenAI’s ChatGPT and Anthropic’s Claude before settling on a tailored Gemini variant for specific jobs. The goal isn’t to outsource everything, but to cover the high-compute tasks that benefit from massive scale while Apple’s in-house stack matures.
A split architecture: what runs where
- Query Planner: This is Siri’s new decision engine – a routing layer that decides whether the assistant should search the web, dig into your calendar, pull a photo, or fire an App Intent for an in-app action. Apple’s customized Gemini will shoulder a big part of this planning, especially when the request is multi-step or ambiguous.
- Summarizer: Within Apple Intelligence, summarization spans notification digests, Safari page briefs, writing tools, and audio/text compression. Again, the heavy lifting goes to the cloud-side Gemini when the request exceeds local capacity.
- Knowledge Search System: For quick factual answers and lookups, Apple leans on on-device models. That keeps latency low, preserves privacy, and avoids sending trivial queries to third-party services.
The connective tissue is Apple’s Private Cloud Compute – a design that treats cloud as an extension of the secure enclave rather than a data lake. Requests are encrypted and stateless; the servers don’t retain your personal context, and Apple says even it can’t read the transient payloads. Practically, that means you get large-model capability without trading away your data. The 1.2T-parameter Gemini operates as a temporarily rented brain, not a permanent memory.
The money question – and what it signals
Apple is expected to pay roughly $1 billion per year to license Google’s AI tech under a deal that is reportedly being finalized. In isolation that sounds enormous; in the AI gold rush, it’s almost conservative. For perspective, Google already pays Apple an estimated $20 billion annually to remain the default search on Safari and across Apple services. The delta is telling: even for a partner as valuable as Apple, today’s generative AI is priced like an enabling utility, not a direct profit center. That hints at the near-term business reality – the real value is in stickier devices, higher engagement, and new premium experiences rather than metered API profits.
Hardware and ops: whose chips are we on?
One debate swirling around the deal is whether Gemini must run on Google’s custom hardware stacks (like TPUs) or if Apple can execute the tailored model on industry-standard GPUs inside its private cloud. If the latter is true – and Apple’s framing suggests portability – then Google’s advantage is less about exclusive silicon and more about model quality and tooling. Either way, Apple’s objective is clear: keep personal context on device, burst out to the cloud for the heavy reasoning, and come back with an answer fast enough to feel local.
What you’ll actually notice
- In-app actions: Siri will finally complete tasks inside your apps – send a file in Messages, tweak a photo preset, start a Focus mode, or create a board in a third-party app – without you tapping through the UI.
- Personal context awareness: With your permission, Siri can blend signals from calendar, messages, mail, and photos to interpret intent (e.g., “reschedule lunch with Maya to next week and share the doc we discussed”).
- On-screen awareness: Ask about what you’re looking at. Siri can understand the current app or page to reduce friction and silly back-and-forth.
- Higher-quality summaries: Notification digests, web page briefs, and long-form text/audio summarization will be tighter, more faithful to source, and better at preserving structure.
Apple is targeting a major Siri revamp alongside a future iOS release cycle, with the Gemini assist acting as a critical crutch until Apple’s own large models can fully take over. The company is explicit that this is not ceding the crown jewels of search or ads to Google; it’s renting expertise to accelerate a user-visible leap.
The strategic read
This partnership is best viewed as a peace-time alliance: Apple gets immediate capability and time to iterate; Google gets distribution and revenue for a flagship model. The bigger picture is that parameter counts – whether 1.2 trillion or some meme-worthy “yotta-scale” – matter less than tight product integration, a robust privacy boundary, and measurable wins for everyday tasks. For users, the risk to watch is not corporate dependence but execution: latency, hallucination control, and guardrails around personal data access. If those land, Siri shifts from a command receiver to a reliable, context-rich agent – finally worthy of the iPhone’s home button legacy.
Bottom line: Apple is buying time and capability without buying out its strategy. If the Glenwood architecture delivers on its promise, today’s “crutch” may soon be the scaffold that helped build a stronger, more independent Siri.