Apple Intelligence relies on Google and Nvidia tech while downplaying Gemini's contributions

Apple partnering with Google and Nvidia for most advanced AI model

Apple making a 'solid step in the right direction' when it comes to AI, says Seaport's Jay Goldberg Apple on Monday revealed what it's been working on in artificial intelligence at its annual Worldwide Developers Conference in Cupertino, Calif. WWDC showed off demos of its redesigned Siri, which can speak back and forth with the user, a major improvement over previous versions of the assistant. In a demo, Siri was able to check concert dates, set a reminder to buy tickets, and even get directions to pick up a friend on the way to the concert venue. But the announcement also highlighted that Apple has taken a different strategy to many of its Silicon Valley rivals, choosing not to spend billions on infrastructure and the biggest, most advanced models, and instead focusing its message to potential customers on privacy advantages and convenience. Apple executives highlighted the difference in remarks on Monday. "Some appear to be racing forward, seemingly pursuing AI for the sake of AI, without clear regard for the people -- all of us -- that it's ultimately meant to serve," said Apple software SVP Craig Federighi in the launch announcement. But it turns out two of the traditional AI leaders, Google and Nvidia, are helping Apple out with its most advanced model, called Apple Foundation Model Cloud Pro, Apple executives told media in a talk at its headquarters on Monday. While Apple and Google announced their partnership for Apple Intelligence in January, this is the first time that the company has officially confirmed that some of its Apple Intelligence features will run on Nvidia chips.

Apple's New AI Models Contain 'None' of Google's Gemini Assistant

Apple executives have detailed the architecture of the company's new Apple Foundation Models (AFM) and clarified exactly how Google's technology factored into their development. Craig Federighi, Apple's SVP of Software Engineering, held a post-keynote tech talk (via 9to5Mac) with press on Monday alongside AI VP Amar Subramanya, Siri lead Mike Rockwell, and software VP Sebastien Marineau-Mes to walk through how the third-generation AFM family was built and how it powers Apple Intelligence. "The amount of the Google Assistant we use is none," Federighi said, explaining that Apple uses none of the Gemini models deployed to Google's customers, none of Google's client-side code, and no Google Search infrastructure as the knowledge backbone. Of course, we don't have the Gemini app as our app. In fact, none of that client code is part of how we run on iOS. For these models, we use none of the models that Google deploys to their customers, nor do we use the infrastructure and means by which they deploy models to their customers. And then, when it comes to the knowledge base, we of course don't use Google Search or anything like that as the foundation of our system. Subramanya outlined the new AFM family, which spans two on-device models and three server-side models. The on-device tier consists of AFM Core, a next-generation dense architecture model, and AFM Core Advanced, which uses a sparse architecture and is natively multimodal. Subramanya said AFM Core Advanced is "unlike any on-device model we've run before," enabling new features including invitation and expressive voices without any cloud requests. On the server side, AFM Cloud handles latency-optimized Private Cloud Compute requests, while AFM Cloud Image powers image generation and editing features including spatial reframing. The key detail on the Google collaboration came in Subramanya's description of how these four models were trained. "All of these are custom built for Apple Silicon, trained using proprietary data with reinforcement learning and refined using outputs from Gemini frontier models," he said, making clear that Google's contribution was distillation-based, not a wholesale adoption of Gemini. The fifth and most capable model, AFM Cloud Pro, is designed for agentic tool use and complex reasoning tasks, with quality that Subramanya said is "similar to Gemini frontier models." This model marks a departure from Apple's standard Private Cloud Compute setup. To run it, Apple worked with both Google and Nvidia to extend its private cloud infrastructure to Nvidia GPUs hosted in Google's cloud. Marineau-Mes said Apple wanted to use Nvidia's latest chips but required them to be configured so they couldn't read the contents of Apple's servers. A recent Nvidia technology called "ambiguous confidential compute" provided the solution. We wanted to avail ourselves of the latest technology from Nvidia, and so we set out to extend private cloud compute to third-party cloud. Federighi described the broader system architecture as being organized around a System Orchestrator, a piece of software he called "key to the privacy architecture of our entire system." The orchestrator routes any given query to the appropriate model, on-device or cloud, based on the complexity of the request and the personal context required. It draws on an App Toolbox for in-app actions, a Spotlight Semantic Index for personal content, and on-screen context for real-time awareness. For queries involving current events, responses are found through Apple's own World Knowledge Service, which Federighi said the company has been building for several years. Apple also maintains that all Private Cloud Compute infrastructure, including the extended Nvidia GPU capacity in Google's cloud, can be independently verified by third-party researchers to confirm that user data is never stored or accessed.

Apple's Private AI Will Run on Google's Servers

Apple today said it is expanding Private Cloud Compute (PCC) beyond its data centers, partnering with Google and NVIDIA to run Apple Intelligence workloads on Google Cloud. Private Cloud Compute is Apple's cloud intelligence system for private AI processing, used to keep Apple Intelligence requests secure while handling processing in the cloud. PCC has been limited to Apple silicon servers in Apple data centers, but Apple is now relying on Google servers to handle some Apple Intelligence processing. Apple partnered with Google to use the technologies behind Google's Gemini AI models for its own Apple Foundation Models. While some processing is done on-device, agentic tool use and complex reasoning require cloud processing. Apple says it worked with Google and NVIDIA to extend its PCC infrastructure to Google Cloud systems that run NVIDIA GPUs without compromising privacy and security protections. Our core PCC requirements remain exactly the same: stateless computation, enforceable guarantees, no privileged runtime access, non-targetability, and verifiable transparency. What's new with PCC on Google Cloud is the implementation: NVIDIA Confidential Computing with NVIDIA GPUs, Intel CPUs with TDX, and Google's Titan chip. All server components and software are part of a trusted computing base subject to verifiable transparency and no-privileged-access guarantees, plus Apple has a cryptographically verifiable ledger of all Google Cloud hardware that is part of the PCC fleet to mitigate the risk of supply chain attacks. PCC on Google Cloud also uses many of the same architectural security patterns as PCC on Apple silicon. Apple says the efforts it has made to bring PCC to Google Cloud will mean user data continues to be protected by PCC's security and privacy properties even outside of Apple hardware and data centers. Apple maintains control over PCC software and Apple devices will only trust PCC software cryptographically approved by Apple. PCC on Google Cloud is not fully implemented, and Apple plans to gradually add the full set of protections throughout the beta testing process. PCC on Google Cloud binaries will be available for public inspection. Apple plans to provide public research tooling and access to live PCC nodes in research mode through its Apple Security Bounty Program.

Apple Removes The Fog Around Its New Cloud-Based, And 20-Billion-Parameter On-Device AI Models, Brushes Aside Google's Contributions While Hyping NVIDIA's

Apple has established a sprawling and intricate compute architecture, one that ropes in Google and NVIDIA to paper over its embarrassing AI-related shortcomings. Even so, Apple's WWDC 2026 keynote answered as many questions as raised new ones. Thankfully, the Cupertino-based tech giant is now issuing clarifications at the speed of lightning, resolving lingering uncertainties on a war footing of sorts. Apple craftily obfuscates Google's contributions to its new Apple Intelligence architecture, taking pains to point out its own technologies at the core of this new paradigm We already know that Apple Intelligence consists of a combo of on-device and cloud-based models. Even so, this distinction was not very granular. Thankfully, Apple has just provided a critical update, noting that the gigantic cloud-based Apple Foundation Model (AFM) is its own creation, albeit distilled from an equivalent Google Gemini model. Of course, we already know that Apple licensed a 1.2-trillion-parameter Gemini model from Google a few months back. It seems the iPhone maker had only licensed Google's technology for model distillation purposes. Apple also takes pains to note that it conducted its own pre-training and post-training operations on the AFM Cloud. Apple has also detailed the architecture of its Private Cloud Compute (PCC) framework, going on to note: Apple has further clarified that the AFM Cloud itself is divided into 2 categories: a Pro model that runs on NVIDIA GPUs within Google Cloud, and a vanilla model as well as an image generation one that runs on Apple's own servers. As far as on-device Apple Foundation Models are concerned, the AFM Core Advanced has 20 billion parameters, but only needs the quantum of parameters strictly needed to process a given inference request. Critically, this model was entirely designed by Apple, and requires the A19 Pro chip to run on an iPhone. Of course, Apple has also prepared a less powerful on-device model for generalized inferencing on older iPhones. When a user submits a request, for instance, via the Siri AI, a localized orchestrator calls the required tools, collects data, and then generates the prompt for the AFM Cloud. Critically, raw data is not sent to the cloud, just the structured prompt. Of course, this comes as Apple spent the better part of the technical presentation downplaying Google's role within the new Apple Intelligence and Private Cloud Compute framework. Follow Wccftech on Google to get more of our news coverage in your feeds.