Alphabet raises its 2026 investment forecast to between 5 billion and 5 billion
Google reported revenue of $119.8 billion for the second quarter of 2026. That figure represents a 24 percent increase year on year and beats analyst expectations of $116.9 billion. Google Cloud grew 82 percent to $24.8 billion. The Services segment rose 15 percent to $94.5 billion.
The Gemini app now has 950 million monthly active users. That is up from 750 million in February. AI Mode in Google Search has crossed one billion monthly active users since its global launch in October. Google claims AI Mode is driving more overall search queries. That does not mean more traffic to websites compared to traditional search.
AI Max has left beta and already has 500,000 advertisers using it. Alphabet says AI is unlocking billions of new search queries that were previously hard to monetize. The cost per AI response in AI Mode has dropped to its lowest level since launch. That points to growing efficiency gains. The recent Flash 3.6 release also showed this trend.
Google CEO Sundar Pichai said the company sees tons of demand for the workhorse Gemini Flash series. He noted the series hits the sweet spot of performance and cost. He also pointed to specific weaknesses Google is trying to fix. Coding and agentic coding is an example of that. He said the teams are very, very focused on it.
Google bets on Gemini 4 to close the gap with frontier rivals
Google is still working on a new frontier model and plans to ship new models monthly. Gemini 3.5 Pro apparently is not part of that cadence. Google says it is currently being tested.
Pichai acknowledged during the earnings call that Google needs a more capable base model first to catch up with the leaders. The next generation of frontier AI models requires much larger base models. Google is training Gemini 4 to meet that bar.
“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,” Pichai said.
What it means
For the people making things, the shift means the daily tools will get faster and cheaper. The company is moving away from relying solely on massive models for every task. Instead, it is betting that bigger foundation models will allow smaller, faster tools to perform better. This approach should lower the cost of running AI features while improving results in areas like coding.
