How the Gemini-Powered Siri Could Work Under the Hood

Apple seems to be gearing up for Siri’s most substantial overhaul to date, potentially powered by Google’s Gemini AI model. According to Bloomberg, Apple and Google are reportedly near finalizing a deal valued at around $1 billion annually, which could see Apple embedding a version of Gemini into Siri alongside its Private Cloud Compute platform.

Apple’s Plan to Integrate Gemini Into Siri

Bloomberg says that Google would provide Apple with a Gemini model featuring 1.2 trillion parameters to boost Siri’s capabilities. Importantly, this data processing would occur entirely on Apple’s Private Cloud Compute servers, ensuring that Google won’t have any access to user interactions. This arrangement is in line with Apple’s enduring commitment to privacy by combining enhanced AI functionalities with its privacy standards, something no other major digital assistant has accomplished on this scale.

1.2 Trillion Parameters Explained

The Gemini model designed for Siri could boast about 1.2 trillion parameters, far exceeding Apple’s current models, which reportedly have around 150 billion parameters. In the world of AI, parameters are crucial in determining a model’s ability to grasp language, understand context, and interpret intent.

While Apple’s figure seems staggering, direct comparisons to models like GPT-5, Gemini 2.5 Pro, or Claude Sonnet 4.5 aren’t feasible since those companies no longer disclose their model sizes. However, a model with over a trillion parameters typically ranks among the top-tier AI systems, capable of managing complex queries, generating human-like responses, and even performing intricate reasoning across various tasks.

Likely Use of Mixture of Experts (MoE) Architecture

The Gemini model Apple might employ could utilize a strategy known as Mixture of Experts (MoE). Instead of a single, enormous network processing everything, MoE splits the AI into several specialized sub-networks or “experts.” For each user query, only the most relevant experts are activated, which makes the system faster and more efficient.

In a setup featuring 1.2 trillion parameters and 32 experts, for example, perhaps just two to four experts would tackle an individual input at a time. This enables Siri to operate with the sophistication of a vast model while maintaining the speed and cost efficiency of a smaller one. MoE lets Apple provide sophisticated AI responses without demanding excessive computational resources for each user interaction.

Why This Architecture Matters for Siri

If Apple embraces this MoE-based model, users could experience significant enhancements in Siri’s ability to handle follow-up questions, comprehend context, and keep conversations flowing across various apps and devices. For example, a request such as “Show me the pictures I took at the beach last weekend and text them to my mom” might be processed smoothly without losing context or needing additional manual steps.

Crucially, Apple’s Private Cloud Compute would safeguard user privacy by ensuring that even though Gemini delivers exceptional intelligence, all personal data remains within Apple’s encrypted environment. This approach balances advanced AI capabilities with robust privacy protection.

Whether a 1.2 trillion-parameter setup will suffice to keep Siri competitive against the forthcoming models from OpenAI, Anthropic, and Google is still to be determined. Nonetheless, this could lay the groundwork for Siri to become both the smartest and most private assistant available.

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