Alphabet has built a vertically integrated AI stack—custom Tensor Processing Units (TPUs), the Gemini large language model and vast training data from its user base—and is renting TPU capacity via Google Cloud, helping drive adoption (Gemini app ~650 million MAU) and strong end-market performance (Google Search +14.5% y/y, YouTube ads +15%, Cloud +34%, subscriptions >20%). The piece highlights Alphabet’s operating income of $127 billion trailing 12 months (versus Apple $133 billion and Nvidia $110 billion) and notes reported deals to power Siri and supply Meta, arguing that broader TPU adoption could slow Nvidia’s growth and multiple. If Alphabet continues to take AI market share and grow operating earnings, the author contends it could become the world’s largest market cap by 2026, though that outcome depends on execution and competitive dynamics.
Alphabet has constructed a vertically integrated AI stack centered on custom Tensor Processing Units (TPUs) that it deploys in-house and rents via Google Cloud, combined with the Gemini large language model and Google’s large proprietary training data set from billions of users. The Gemini App reached roughly 650 million monthly active users versus an estimated 845 million for ChatGPT, and Gemini is being embedded across Google services, which supports distribution-led adoption. That integration is already showing in revenue growth: Google Search grew 14.5% year over year, YouTube advertising revenue rose 15%, Google Cloud grew 34%, and subscriptions (where Gemini revenue is segmented) grew over 20%; Alphabet generated $127 billion in operating income on a trailing-12-month basis versus Apple’s $133 billion and Nvidia’s $110 billion. Nvidia’s revenue grew 62% year over year last quarter, but the author argues TPUs and enterprise deals (reported arrangements with Apple for Siri and Meta for cloud compute) could slow Nvidia’s growth and compress its multiple in 2026. If Alphabet continues to scale TPU adoption and monetize Gemini across its user base, the company could materially expand operating earnings and contend for the top market-cap spot in 2026; key risks include execution on chip deployment (manufacturing is excluded), customer adoption pace, and competitive responses that could blunt margin or share gains.
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