{"slug": "apple-adopts-nvidia-chips-for-gemini-powered-siri", "title": "Apple adopts Nvidia chips for Gemini-powered Siri", "summary": "Apple will route some Siri queries to Google Cloud and run them on Nvidia Blackwell B200 GPUs as part of a licensed deployment of Google's Gemini model, according to The Information. Apple has also approved the use of Nvidia's confidential compute technology to encrypt data during processing on those chips. The move marks a departure from Apple's previous strategy of controlling all critical product components.", "body_md": "Photo: \n9to5mac.com\n \n· rights & takedowns\nThe Information reports that Apple will route some Siri queries to Google Cloud and run them on Nvidia Blackwell B200 GPUs as part of a licensed use of Google\u0002s \nGemini\n model, according to 9to5Mac's coverage of The Information. The Information also reports that Apple has approved the use of Nvidia's confidential compute technology to encrypt data while it is processed on the chips. 9to5Mac quotes The Information as saying the move diverges from Apple\u0002s prior attempt to control all critical product ingredients, and that it is unclear how Apple\u0002s previously launched server system will fit into the upcoming Siri rollout. Nvidia is quoted describing its confidential compute feature as preserving \"the confidentiality and integrity of AI models deployed on Rubin, Blackwell, and Hopper GPUs.\"\nWhat happened\nThe Information reports, via 9to5Mac, that Apple will route some user queries for a new version of Siri to Google Cloud and run them on Nvidia \nBlackwell B200\n GPUs as part of a licensed deployment of Google\u0002s \nGemini\n model. The Information also reports that Apple has approved the use of Nvidia\u0002s confidential compute feature to encrypt data while it is being processed on those GPUs. The Information, quoted in 9to5Mac, describes this choice as diverging from Apple\u0002s previous approach to controlling the full stack, and notes uncertainty about how Apple\u0002s previously launched server system will be used in the upcoming Siri product launch.\nEditorial analysis - technical context\nThe \nBlackwell B200\n is presented publicly by Nvidia as a data-center GPU designed for large-scale model training and inference; vendors describe Blackwell as the successor to \nHopper\n with improvements in inference throughput, memory bandwidth, and multi-GPU scaling. Nvidia\u0002s confidential compute is a hardware-based security capability that isolates and encrypts data during on-chip processing; Nvidia is quoted saying it \"preserves the confidentiality and integrity of AI models deployed on Rubin, Blackwell, and Hopper GPUs,\" enabling sensitive workloads to run in shared cloud environments with near-native performance.\nIndustry context\nCompanies deploying large foundation models often balance on-device execution and cloud-hosted inference to trade latency, model capacity, and privacy. Editorial analysis: industry observers note that using cloud-hosted GPUs with confidential compute is a growing pattern for organizations that need access to very large models but also want cryptographic protections for data during processing. Editorial analysis: relying on a cloud provider\u0002s GPU fleet can accelerate access to cutting-edge hardware while introducing operational dependencies on the cloud vendor and GPU vendor ecosystem.\nWhat to watch\nFor practitioners, useful indicators include:\n•\nthe latency and cost profile for queries routed to cloud-hosted \nGemini\n inference on Blackwell hardware;\n•\ntechnical documentation or SOC/attestation details showing how confidential compute is implemented and audited;\n•\nthe division of workloads between on-device Siri components and cloud-based \nGemini\n inference;\n•\nany public details about how Apple\u0002s existing server hardware will interoperate with Google Cloud-hosted inference.\nScoring Rationale\nNotable to practitioners because it documents a major consumer-device vendor using cloud-hosted, vendor-grade GPUs and confidential compute for assistant inference, affecting deployment, latency, and privacy tradeoffs.\nPractice interview problems based on real data\n1,500+ SQL & Python problems across 15 industry datasets — the exact type of data you work with.\nTry 250 free problems", "url": "https://wpnews.pro/news/apple-adopts-nvidia-chips-for-gemini-powered-siri", "canonical_source": "https://letsdatascience.com/news/apple-adopts-nvidia-chips-for-gemini-powered-siri-01afb086", "published_at": "2026-06-04 01:49:29.668654+00:00", "updated_at": "2026-06-04 01:49:32.373893+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-infrastructure", "ai-chips", "ai-products"], "entities": ["Apple", "Nvidia", "Google Cloud", "Gemini", "Blackwell B200", "Siri", "The Information", "9to5Mac"], "alternates": {"html": "https://wpnews.pro/news/apple-adopts-nvidia-chips-for-gemini-powered-siri", "markdown": "https://wpnews.pro/news/apple-adopts-nvidia-chips-for-gemini-powered-siri.md", "text": "https://wpnews.pro/news/apple-adopts-nvidia-chips-for-gemini-powered-siri.txt", "jsonld": "https://wpnews.pro/news/apple-adopts-nvidia-chips-for-gemini-powered-siri.jsonld"}}