Google has just posted a ‘historic’ quarter. Alphabet made history Wednesday with a quarterly profit that stretched into 12 figures for the first time in the search giant’s history. Google-parent Alphabet’s second quarter revenue increased by a very impressive 24%, to $119.8 billion, with the Google Cloud business reaching an 82% growth. CEO Sundar Pichai called Google’s Q2 results proof that the company’s “full stack approach to AI is delivering real, measurable value.”Pichai also shared some impressive figures that got accolades from Tesla CEO and the world’s richest man Elon Musk. “Q2 was an amazing quarter, with our AI investments redefining what’s possible across every part of our business. Alphabet revenue grew 24% YoY and Google Cloud accelerated to 82% growth. We saw exciting momentum across the board from Search to YouTube to the Gemini app (which reached 950M monthly active users). Our model APIs are processing 22B tokens/min (up from 16B+ last quarter) driven by our workhorse Flash models. We’re also seeing great adoption of Gemini Enterprise, used by 90% of the Fortune 100, as well as strong demand for our security solutions. Outstanding results and momentum, and such an exciting moment—thanks to all of our partners and employees around the world! 🙌 About to hop on the call!,” wrote Pichai. To this Musk responded “Impressive”.Google CEO’s numbers on Gemini app should also answer Meta AI CEO Alexandr Wang, who recently shared a graph making fun of Google Gemini. Wang reposted a Twitter post that said that Meta is ‘beating’ Google Gemini hard. He captioned it with two words: “Gemini who”.
The post Wang reposted said: “Google getting beaten by @alexandr_wang this early, when Meta’s new AI team is tiny in comparison, is absolutely embarrassing for Google.”
Sundar Pichai on Google’s AI progress
In a blog post, Pichai said the rapid growth of the Gemini app has been fuelled by new AI-powered features such as Daily Brief and the personalised Gemini Spark assistant, which is now available in the US and several international markets. Here’s what he wrote:Yesterday we announced new models — Gemini 3.6 Flash and Gemini 3.5 Flash-Lite — which are cost effective and highly efficient. We’re seeing tons of demand for our workhorse Gemini Flash series, because it hits the sweet spot of performance and cost.We also launched Gemini 3.5 Flash Cyber, which I’m really excited about. Paired with our CodeMender agent, it finds and fixes vulnerabilities and delivers performance at the frontier, comparable to far bigger cyber models.Gemini 3.5 Pro is currently in testing. And our team is already building the next generation of models. We have started our most ambitious pre-training run yet, for Gemini 4, and are excited by the progress we are seeing at the frontier.Demand for our models is translating to strong token usage across developers and enterprise customers, and we continue to be supply constrained — a sign of momentum and rapid adoption.More than 9 million developers are building each month with our models across our APIs and key developer products. Our model APIs are now processing approximately 22 billion tokens per minute. That’s up from 16 billion just a quarter ago.Additionally this quarter, we launched Omni. It allows users to create anything from any input, starting with video. Since launching at I/O in May, there’s been a 40% increase in daily active users creating videos on the Gemini app.Our Gemma family of open models small enough to run on local devices are hugely popular — these models have been downloaded over nine hundred million times. And our latest Gemma 4 models have been downloaded over 300 million times since launching in April.Our agentic development platform Antigravity allows anyone to build in the agent-first era. It has more than 2.4 million weekly active users. Antigravity is a powerful tool for users and enterprises, and it’s completely accelerated how we build internally. As just one example, a team in Chrome is now on track to accelerate delivery by eight times, compressing a two-year timeline into three months through model-driven refactoring.