AI Everything Today

Quick overview

Apple plans to use a custom version of Google Gemini, reportedly a model with about 1.2 trillion parameters, to power upgraded Siri and Apple Intelligence features. According to reports citing Bloomberg and The Verge, Apple will run that Gemini model on its Private Cloud Compute and pay Google roughly $1 billion per year for access, while continuing to develop and use some of its own AI models.

This move affects several actors and technologies: Apple, Google and its Gemini model, Apple Private Cloud Compute, Siri, and Apple Intelligence. The company aims to add features such as summarization and planning to Siri, with a wider rollout expected next spring.

What the report says

Reporters say Apple negotiated access to a custom Google Gemini model rather than licensing an off-the-shelf version. The custom model is reported to be around 1.2 trillion parameters. Apple will host the model on its own Private Cloud Compute infrastructure. The deal is said to cost roughly $1 billion per year.

At the same time, Apple will keep developing some in-house models to handle certain tasks or features. The goal is to speed up delivery of powerful assistant features while still investing in long term internal capabilities.

Why this matters to everyday users

Apple’s choice could change what Siri can do for regular users. The company plans to add better summarization and planning features to Siri. That could mean clearer answers to complex questions, step by step help in planning tasks, and more useful synthesis of information across apps and messages.

For Apple customers, the key facts are simple:

• Apple will use a custom Google Gemini model to improve Siri and Apple Intelligence.
• The model will run in Apple’s Private Cloud Compute environment.
• Apple reportedly pays about $1 billion annually for access to Google’s model.
• New features are expected to arrive in the spring following the report.

Technical deployment and what Private Cloud Compute means

Private Cloud Compute refers to Apple’s cloud infrastructure that handles services and data for Apple devices and accounts. By running Gemini on Private Cloud Compute, Apple keeps model execution within its own managed environment rather than relying on a third party for live hosting.

That setup implies a mix of roles:

• Google provides the model architecture and training support for the custom Gemini variant.
• Apple handles runtime, service integration, and connections to user data on its cloud systems.
• Apple may still use smaller in-house models for tasks that should stay local to devices or that require extremely tight privacy controls.

Product timeline and expected features

Apple reportedly plans to deploy upgraded assistant features next spring. The immediate improvements tied to Gemini include better summarization and planning functions. That could allow Siri to:

• Summarize long emails, articles, or message threads quickly and clearly.
• Create step by step plans for tasks such as travel, events, or multi-step workflows.
• Provide more contextual, conversational responses that combine information from multiple apps.

These features are meant to make Siri more helpful in everyday tasks, especially when dealing with longer or more complex information.

Privacy, security, and user data

Apple has long emphasized privacy as a central selling point. Using a Google model raises reasonable questions about how user data enters the AI pipeline and how it is protected.

Key privacy points to watch:

• Hosting the model on Apple’s Private Cloud Compute keeps the inference process under Apple’s control, which may reduce the need to send live queries to Google systems.
• Apple still decides what user data to route into the model, and how to anonymize or minimize sensitive inputs before processing.
• Some features may still run on-device or on smaller in-house models if data cannot be shared with cloud services at all.

Users should expect Apple to clarify which signals go to the cloud, how long they are stored, and how the company limits exposure of personal data when using third party models.

Why Apple might choose a third party now

There are several practical reasons a company like Apple would license or customize a third party model rather than relying entirely on its own systems.

• Speed to market. Building and training a multi trillion parameter model takes time and infrastructure. A custom model lets Apple deliver advanced features more quickly.
• Capability gap. Big generative models already demonstrate broad language and reasoning abilities that can be expensive to reproduce from scratch.
• Cost tradeoffs. Paying for a model while running it on Apple’s cloud can be less costly or risky than bearing the full cost of development, research, and training internally.

Apple’s continued investment in internal models suggests the company views this as a mixed approach, using external models where they speed progress and internal models where privacy or differentiation matters most.

Strategic and competitive implications

This move shifts competitive dynamics among major AI providers and device makers. Apple has traditionally emphasized hardware, software integration, and privacy. Turning to Google for core model capabilities shows the company is prioritizing feature parity and user experience right now.

How this affects the broader market:

• Apple gains access to leading language model capabilities without fully outsourcing hosting or control.
• Google strengthens its position as a provider of large scale models to other big tech firms.
• Other AI firms, including OpenAI and Anthropic, remain competitors for assistant and cloud AI services, but Apple’s decision signals demand for flexible partnerships.

Long term, Apple may replace third party models with its own systems as internal models improve and training infrastructure scales.

Developer and enterprise impact

Developers and enterprise customers can expect Apple Intelligence and Siri to become more capable at synthesizing information across apps and services. Potential effects include:

• New APIs or system-level hooks to access summarization, planning, and conversational features.
• Stronger value for apps that integrate with system assistants, since the assistant itself can offer richer outputs.
• Questions about data routing for enterprise customers who need strict controls on where data is processed.

Apple will need to provide clear documentation and controls so developers and IT teams can manage data flows and compliance requirements.

Key takeaways

• Apple plans to use a custom Google Gemini model, reportedly around 1.2 trillion parameters, to power upgraded Siri and Apple Intelligence.
• The model will run on Apple Private Cloud Compute. Apple is said to pay Google roughly $1 billion per year.
• New features will focus on summarization and planning, with a broader rollout expected next spring.
• Apple will continue developing in-house models and decide which tasks must stay local to devices for privacy reasons.
• Expect clearer privacy disclosures and developer controls as Apple integrates third party model capabilities.

FAQ

Will my private data be sent to Google?

Apple says the model will run on its Private Cloud Compute. That means Apple controls the runtime environment for the model. The exact data paths and retention policies will depend on Apple’s final implementation and public privacy statements.

Why does Apple not build its own model right away?

Training and refining very large models takes significant time and money. Using a custom third party model speeds delivery of advanced features while Apple continues investing in its own capabilities.

Will Siri get better at long answers and planning?

Yes. The reported improvements include better summarization and planning, which should help Siri handle longer content and multi step tasks more effectively.

Could Apple switch away from Google later?

Yes. Apple appears to be following a hybrid approach. It will keep developing internal models and could rely less on external partners as its own models mature.

Concluding thoughts

This reported deal shows how big technology companies are finding pragmatic ways to combine strengths. Apple gets advanced language model capabilities faster by working with Google, while keeping model runtime inside its own cloud. That approach could bring more useful assistant features to everyday users, and at the same time it raises clear questions about data handling and long term vendor reliance.

For now, users should expect improved Siri abilities next spring, and watch for Apple to explain how it will protect private data and give developers the tools they need to integrate new assistant features safely and responsibly.