Apple and Google jointly announced a multi-year agreement under which Google’s Gemini model will provide the core AI capabilities powering Apple’s Siri and other AI features. The market voted with real money: Google’s share price spiked, and its market cap leapt past the $4 trillion threshold. This is more than just a win from a single partnership — it marks a wholesale re-rating of Google’s full-stack AI strategy and its control over the broader ecosystem.

The Strategic Significance Behind the Apple Deal

This cooperation with Apple goes far beyond a technology services contract that might be worth around $1 billion a year. It is a landmark “territory-seizing” move whose strategic value shows up on three levels:

First, it is a top-tier “technology endorsement.”Apple is famous for its extreme obsession with user experience and privacy. Its choice of Google’s Gemini as the foundation for upgrading Siri is effectively a global announcement that, in the current AI model race, Google’s technology is at the forefront. More importantly, this allows Google to inject its AI capabilities into the very heart of the iOS ecosystem, which Apple has tightly controlled and historically kept closed. From now on, the smart features used by billions of Apple device users worldwide will be running on Google’s technological “blood.”

Second, the cooperation model reinforces Google’s role as “infrastructure.”Under the agreement, the Gemini model will run on Apple’s private cloud servers. Google will not have access to user data and will instead act more like a “power plant” providing the core intelligence. This setup allows Google to avoid complex privacy controversies while firmly occupying the foundational layer of the AI value chain. It signals that Google is accelerating its shift from a consumer-facing applications company to the underlying infrastructure provider powering the intelligent transformation of the entire digital world.

Third, the deal fundamentally changes the terms of the AI race.While the industry is still fixated on comparing model size and parameter counts, Google has already, through this partnership, used Apple’s devices — one of the world’s most valuable distribution endpoints — to achieve unmatched scaled “distribution” of its AI capabilities. This validates a forward-looking view within the industry: by 2026, the real moat in AI competition may no longer be model performance alone, but “distribution power” — whoever can embed intelligence most seamlessly into the largest number of critical user scenarios will win the scale war.

Four Growth Engines Powering Google’s Market Value Boom

The Apple deal is the spark, but the “fuel” behind Google’s $1 trillion surge in just two months is its carefully built, now fully engaged “full-stack flywheel.” Its powerful momentum comes from the combined force of four key pillars:

In-house chips (TPU): Unlike many competitors who are heavily reliant on Nvidia GPUs, Google has built a massive advantage through over a decade of investment in its own Tensor Processing Units (TPUs). TPUs are deeply integrated with Google’s software ecosystem and are more efficient and cost-effective when handling Google’s own AI workloads. This structural edge not only lifts Google Cloud’s profit margins but has also attracted top AI companies such as Anthropic to purchase TPU capacity at scale, turning TPUs from an internal tool into a competitive, externally offered product.

Large models (Gemini): The Gemini family represents the culmination of Google’s AI capabilities. The version reportedly provided to Apple — the 1.2-trillion-parameter Gemini 2.5 Pro — ranks among the top performers in benchmark evaluations. Through cloud APIs and the Android ecosystem, Google is actively “distributing” Gemini’s capabilities to millions of developers and billions of devices, building a far-reaching developer ecosystem.

Cloud computing (Google Cloud): Once seen as lagging behind, Google Cloud has now transformed. Driven by AI demand, its revenue is surging — last quarter, revenue grew 34%, while operating profit for the division jumped 84%. This rapid growth and margin improvement have given capital markets a solid second growth engine and valuation anchor beyond advertising, easing earlier concerns over Google’s long-term growth.

A global product matrix forming “distribution supremacy”: This is Google’s most irreplaceable advantage. More than 3 billion active devices worldwide run Android; Google Search processes over 10 billion queries a day; YouTube has around 2 billion monthly active users. Together, these products create a default network of traffic and interaction endpoints that reaches nearly every corner of the globe. Any improvement in AI capabilities can be instantly delivered to massive user bases through this network, turning into commercial value almost immediately.

What truly unnerves its competitors is that these four pillars reinforce one another, forming a powerful flywheel:

TPUs lower AI computing costs →making Gemini training and inference more efficient →attracting more cloud and AI customers and richer use cases →feeding back more data and demand to further optimize chips and models →and ultimately maximizing value through Google’s global distribution network.

Opportunities and Challenges

Reaching the $4 trillion table is one thing; holding that seat is an even tougher battle. Whether Google can remain firmly in the $4 trillion club hinges on its ability to turn current momentum into sustained financial performance and ecosystem expansion. In the short term, the positive impact of the Apple deal, ongoing improvements in Google Cloud’s profitability, and AI-driven gains in the advertising business should all provide support. Citing this, institutions such as Citigroup have named Google a top sector pick and remain bullish on its outlook.

But the risks are real as well:

1. Antitrust regulation:
   With control over the Android ecosystem, the world’s largest search engine, and now deep integration into Apple’s iOS, Google’s “distribution supremacy” could trigger tougher antitrust scrutiny from regulators around the globe.
2. Technology-path disruption risk:
   AI technology is evolving at breakneck speed. The emergence of a disruptive new architecture or algorithm could erode today’s TPU and Gemini advantages.
3. “De-Googling” among ecosystem partners:
   Many see Apple’s current cooperation as an interim solution while it builds out its own AI capabilities. Over the long run, Apple and other tech giants have never wavered in their ambition to own core technologies. Google will have to continuously prove that it is truly indispensable.