Alphabet delivered another quarter of accelerated growth. Revenue climbed 24% to $119.8 billion. Cloud revenue jumped 82% to nearly $25 billion. And Gemini? It added hundreds of millions of users while its models now handle 22 billion tokens every minute.
Those numbers come straight from the earnings report and call on July 22. CEO Sundar Pichai struck a confident tone. “Our AI investments are redefining what’s possible across every part of our business,” he said, according to 9to5Google. The results sent shares higher in after-hours trading despite some investor questions on capital spending.
Yet the story runs deeper than one set of figures. Google’s long-standing search franchise still throws off enormous cash. YouTube keeps expanding its audience. The real action, though, centers on artificial intelligence. Gemini now sits at 950 million monthly active users. That’s up from 750 million in February and 650 million last October. Daily active users have tripled over the past year.
Gemini Closes the Gap on ChatGPT
The user surge puts Gemini within striking distance of OpenAI’s ChatGPT. Recent Sensor Tower data pegs ChatGPT at roughly 1 billion monthly users. Pichai highlighted the momentum on the call. He noted the app’s rapid adoption and the model’s expanding role inside Search, ads, Cloud, coding tools and YouTube.
But growth didn’t come without trade-offs. Google delayed the launch of its flagship Gemini 3.5 Pro model. The holdup stemmed from shortcomings in coding and agentic tasks, Reuters reported days before the earnings release. That delay fueled some skepticism. Analysts wondered whether Google could match rivals’ pace in the lucrative market for AI coding assistants.
Still, the company pushed forward with lighter, faster models. This week it released Gemini 3.6 Flash. Executives claim it outperforms its predecessor on coding benchmarks while consuming fewer tokens. The efficiency gains matter. They lower costs and let the system serve more users without exploding infrastructure bills. Early work on Gemini 4 has already begun. The pace of iteration feels relentless.
Enterprise traction tells another strong chapter. Nearly 90% of the Fortune 100 now use Gemini Enterprise, Pichai said. The Antigravity AI coding tool reached 2.4 million weekly active users. And the overall Google Cloud backlog doubled to more than $514 billion, heavily weighted toward AI infrastructure and solutions. Demand for TPUs and custom silicon keeps rising. So does spending. Capital expenditures remain elevated as Google races to build out data centers.
Search advertising held steady. It met expectations but didn’t exceed them by much. YouTube ads benefited from global events. More than 1.7 billion unique viewers watched World Cup-related videos during the 2026 tournament. The mix shows how Google’s traditional businesses still anchor the financials. AI simply adds a new, faster-growing layer on top.
Operating income reached $40.77 billion. Net income hit $112.1 billion for the quarter. Those headline profits reflect scale. They also reflect the bet that current AI outlays will deliver outsized returns later. Ruth Porat, the chief financial officer, has repeatedly defended the investment level. The market appears willing to accept it for now. Shares have gained this year even after a spring pullback.
Competition keeps intensifying. OpenAI pushes its own user base and API business. Anthropic secured fresh funding and chips from AMD. Meta and others pour money into open-source alternatives. Google counters with integration. Gemini appears inside Chrome, inside Search results, inside Workspace apps. The strategy aims to make AI feel native rather than bolted on.
Cost per query has dropped. Upgrades to AI Overviews and AI Mode using Gemini 3 cut expenses by 30%, according to analysis in Seeking Alpha. That improvement helps protect margins while expanding features. Investors watch these unit economics closely. A widening gap between AI revenue and AI cost could unlock further upside.
Wall Street mostly cheered the report. Cloud growth at 82% handily beat forecasts. Investor’s Business Daily noted the acceleration driven by AI workloads. Yet questions linger on the payoff timeline for all those data-center dollars. Pichai pointed to the $514 billion backlog as evidence of committed demand. The figure more than doubled from the prior quarter.
Token processing capacity now stands at 22 billion per minute across Gemini models. That’s a massive leap in throughput. It supports everything from consumer chat to enterprise agents. The Gemini app itself benefits from frequent updates. New capabilities in slide creation, code assistance and real-time context have driven retention.
Analysts had expected some moderation in overall revenue growth. The actual 24% pace beat those lowered bars. Advertising remains the profit engine. AI adds the growth narrative that keeps valuations elevated. The combination explains why Alphabet trades at a premium to historical averages.
Of course risks remain. Regulatory pressure continues in Europe and the United States. Antitrust cases could force changes to search defaults or app bundling. AI itself faces scrutiny over training data, energy consumption and potential job displacement. Google has tried to address some of these issues with transparency reports and efficiency-focused models.
But on the earnings call the focus stayed squarely on execution. “AI adoption continues at an unprecedented scale,” Pichai told analysts. The numbers back him up. 950 million monthly users. Tripled daily engagement. Record cloud growth. A massive backlog. The pieces are falling into place faster than many expected even six months ago.
Whether that momentum carries Gemini past the 1 billion mark by year-end remains to be seen. ChatGPT isn’t standing still. Neither are the other frontier labs. The race has become a multi-horse sprint with huge financial stakes. For now Google can claim one of the largest user bases in consumer AI and the fastest-growing cloud business among hyperscalers.
That position didn’t arrive by accident. Years of investment in infrastructure, research and product integration finally show returns at scale. The next quarters will test whether those returns compound or whether competition and capex pressure begin to weigh. So far the data points look promising. Very promising.
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