Alphabet is facing increasing investor pressure as it approaches the release of its second-quarter results. This pressure is compounded by the postponement of a strategic artificial intelligence (AI) model launch, adding to concerns about the return on large investments made in data center infrastructure.
This scenario contrasts with the optimism of previous months, when the company exceeded expectations thanks to the solid performance of its cloud computing unit. Google's parent company will present its second-quarter financial figures on Wednesday, the 22nd. One of the market's biggest points of interest is the delay of Gemini 3.5 Pro, which was set to be the company's next major AI model.
Originally scheduled for June, this model aimed to strengthen Alphabet's position in the agentic AI applications and AI-powered programming tools market. However, the company managed to alleviate some of this apprehension on Tuesday, the 21st, by releasing other updates for Gemini.
The delay of Gemini 3.5 Pro occurs at a time of intensifying competition, as Chinese open models are gaining ground against major US-based laboratories in the race for clients. Additionally, there are growing fears about the high costs inherent in AI development, raising suspicions that large technology corporations may be investing in capacity exceeding future demand.
Dave Wagner, portfolio manager at Aptus Capital Advisors, commented to Reuters that while Google might be falling behind in AI programming—which he considers a real and growing concern—Google's strategy is entirely focused on its ecosystem.
In April, Alphabet revised upward its capital investment projections for 2026, estimating expenses between US$ 180 billion and US$ 190 billion. Concurrently, the company announced plans to raise about US$ 85 billion through stock offerings, including an investment from Berkshire Hathaway.
Since the end of April, Alphabet's shares have fallen by approximately 9%, a period during which the company had achieved 63% growth in sales of its cloud division. Due to this performance, the stocks lagged behind other companies in the group known as 'The Magnificent Seven.'
In addition to financial pressure and recent stock movements, the company has also lost important talent to competitors. Among these professionals are Noam Shazeer, co-lead of the Gemini project, and John Jumper, a Nobel laureate and considered a key executive at Google DeepMind.
Despite these obstacles, analysts point out that Alphabet's main competitive advantage in the AI race lies in its vast consumer-facing distribution network, combined with its AI models, cloud computing infrastructure, and proprietary chips.
Looking at the full year of 2026, the company's shares still show an appreciation close to 13%, positioning Alphabet as the second best-performing company among the members of 'The Magnificent Seven.'
For the second quarter, analysts predict only a modest slowdown in revenue growth compared to the first three months of 2026, keeping the cloud division as the main driver of results.
According to data compiled by LSEG, Alphabet is expected to generate US$ 116.9 billion (R$ 594.7 billion) between April and June, representing a 21.3% increase compared to the same period last year. The forecast also indicates that cloud computing division sales should maintain an expansion rate of 64%, while advertising revenue growth should be more contained, at 13.7%.
The strong performance of the cloud sector has been driven by the expansion of contracts related to Google's custom AI chips, including multi-million dollar deals closed with Meta and Anthropic.
Google has introduced three new artificial intelligence versions with the aim of intensifying competition against OpenAI and Anthropic. These new offerings include faster, more economical models, and those specialized in digital protection.
The main launch is Gemini 3.6 Flash, presented by Google as the company's most advanced Flash model. This model promises performance improvements in programming, knowledge tasks, and multimodal features, while consuming 17% fewer tokens than its predecessor, resulting in reduced operational costs.
Alongside Gemini 3.6 Flash, Gemini 3.5 Flash Cyber, focused on identifying and correcting software flaws, and Gemini 3.5 Flash-Lite, designed to handle large workloads and autonomous AI agents, were launched.
Security is a key differentiator for this new generation of models, according to Google. Gemini 3.6 Flash has been strengthened to offer greater resistance to misuse in cyberattacks without compromising legitimate applications.
Among the important announcements are: Gemini 3.6 Flash, for being more economical and efficient; Gemini 3.5 Flash Cyber, dedicated to digital security; Gemini 3.5 Flash-Lite, intended for AI agents and large-scale tasks; and the start of Gemini 4 pre-training.
In tests conducted by the company itself, Gemini 3.5 Flash Cyber detected 55 issues in the V8 JavaScript Engine, including 10 vulnerabilities that other models had failed to identify. Because of this, its initial access will be restricted to governments and trusted partners.
While the new models reach the market, Google announced that Gemini 3.5 Pro remains in testing and will be made available when ready. Furthermore, the company revealed that it has started pre-training Gemini 4, indicating that the next iteration of the platform is already under development.
In parallel, Gemini 3.6 Flash and Flash-Lite are beginning to be released to developers, businesses, and Gemini application users. Flash-Lite will also undergo gradual integration with Google Search.
In recent months, the competition for increasingly specialized and efficient models has been fierce among Google, OpenAI, Anthropic, Meta, and various Chinese startups. With these new releases, Google seeks to regain ground in a rapidly evolving dispute, where factors such as cost, performance, and security have gained comparable weight to the quality of responses.
