
Google Q1 earnings 2026
Google Q1 earnings 2026On April 29, Alphabet's Google released its quarter 1 earnings report for 2026, revealing major growth in its Google Cloud services. According to the US Securities and Exchange Commission filing, the company's total revenue rose 22% to $109.9 billion in the first quarter, largely due to its strong enterprise demand for AI products, cloud infrastructure, and generative AI services.
Google Cloud also crossed the $20 billion revenue mark for the first time with 63% revenue growth, highlighting the growing momentum of AI-led cloud adoption across industries. Sundar Pichai, Alphabet and Google CEO, said, “2026 is off to a terrific start.”
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Pichai further revealed that the strong quarter was driven by AI-powered features in Google Search, with search revenue grew 19%. In addition, its backlog nearly doubled to over $460 billion.

“These outstanding results are built on our differentiated, full-stack approach. Our first-party models, like Gemini, are now processing more than 16 billion tokens per minute via direct API use by our customers, up 60% from last quarter. It’s really exciting to see how our AI investments are delivering value for our users, customers and business,” Pichai added.
Google’s Gemini app was the main reason behind this growth, with paid subscriptions reaching 350 million across its services. Gemini Enterprise grew 40% quarter-on-quarter in paid active users, showing strong enterprise adoption.
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Lastly, Waymo, Google’s self-driving car company, completed more than 500,000 fully autonomous rides every week.
Google also started selling its AI chips, called TPUs (Tensor Processing Units), directly to some customers for the first time to handle AI workloads and machine learning tasks. Previously, Google only used TPUs internally for products like the Gemini AI model. However, the company expects a small amount of revenue from TPU sales this year.
Pichai believes direct TPU sales can help Google enter a much larger AI hardware market. However, Google is still facing limits on computing power and chip supply due to huge AI demand.
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