The launch of Google's Gemini 3 has changed the pace of the race for generative artificial intelligence. After years riding the wave of ChatGPT's initial impact, the company has accelerated both the development and deployment of its new model, and early data points to a turning point in the industry.
In just a few weeks, Gemini 3, Gemini 3 Pro, and Gemini 3 Deep Think have gone from limited availability in the United States to dozens of markets, with a particularly strong presence in Europe and Spain. At the same time, their performance in benchmark tests and their popularity among advanced users have increased the pressure on OpenAI, which has responded by activating an internal "red alert" to strengthen ChatGPT.
Accelerated global rollout of Gemini 3 and focus on Europe
This time, Google has opted for a much faster approach than in previous launches: Gemini 3 is being integrated into the search engine's AI mode in more than 120 countries across the Americas, Asia, and the EMEA region. This massive rollout contrasts sharply with the more gradual strategy the company followed with previous models.
Within this map, the expansion in Europe is particularly noteworthy . Markets such as Spain, France, Germany, Italy, the United Kingdom, and the Nordic countries can already access the new model through Google Search's AI mode. Several countries in North Africa, the Middle East, and sub-Saharan Africa are also joining, creating a very broad presence in the region.
In these regions, users with Google AI Pro and Google AI Ultra subscriptions can select the "Thinking with 3 Pro" option within the search engine's AI mode to run their queries using the most advanced, general-purpose model. However, for now, Gemini 3 Pro is only available in English , a relevant detail for countries like Spain, where a large portion of the population is not yet familiar with AI models in that language.
The company emphasizes that Gemini 3 improves user intent understanding and prompt reading thanks to a revamped reasoning engine. The goal is to reduce the need for highly detailed instructions and provide more accurate responses in fewer iterations, both in everyday query tasks and professional scenarios.
In parallel, Google is expanding Nano Banana Pro , its image generation and editing tool integrated into the Gemini 3 family, to more countries. This visual component combines with the text and code capabilities of the main model to create a more complete ecosystem around the new release.
Gemini 3 Deep Think: deep reasoning and slow but accurate response
Beyond the general-purpose model, one of the major new features is Gemini 3 Deep Think , presented by Google as its "most advanced reasoning model" to date. This variant has already been launched in Spain and globally for Google AI Ultra subscribers, accessible through the Gemini app via the model selector and the "Thinking" tools.
Deep Think stands out for its reliance on an advanced parallel reasoning technique , designed to explore multiple hypotheses simultaneously before returning an answer. This approach prioritizes quality over immediacy, which is evident in the fact that responses can take several minutes to generate when the task is complex.
The company's approach involves transforming Gemini 3 Deep Think into a kind of "laboratory brain" focused on math, science, and logic problems , as well as advanced programming. Through iterative rounds of reasoning, the model promises better visualizations, more polished prototypes, and more nuanced code than previous versions.
From a technical standpoint, Deep Think is built on Gemini 2.5 and inherits part of its architecture, but adds a more sophisticated parallel reasoning system. Google maintains that this approach has allowed for a significant leap forward in various benchmarks, especially those measuring abstract reasoning and code execution.
Regarding access, Gemini 3 Deep Think is only available with the Google AI Ultra subscription , the most expensive in the range. The company itself admits that it is an extremely computationally demanding model that requires longer periods of time to explore different hypotheses in parallel. This resource requirement explains why it is offered only through the highest-priced plan and with stricter usage controls.
Benchmark results: Gemini 3 and Deep Think take the lead
One of Google's main arguments for supporting the arrival of Gemini 3, and especially Gemini 3 Deep Think , is the results of a series of independent benchmark tests. The company prominently cites the Humanity's Last Exam , a 2.500-question test that combines mathematics, science, history, and general reasoning.
In this test, the standard Gemini 3 model scored 37,5% without access to external tools , while the new Deep Think raised that figure to 41% , also without relying on additional utilities. Google interprets this data as a sign that the model is capable of solving complex problems with a higher level of reliability than previous systems.
The comparison with its main rivals is one of the most sensitive points. In the same Humanity's Last Exam, OpenAI's GPT-5.1 scored only 26,5% without tools , clearly below the two models in the Gemini 3 family. In other benchmarks, such as GPQA Diamond (focused on advanced scientific knowledge), Deep Think approaches 93,8%, and in ARC-AGI-2 (visual reasoning and puzzle-solving with code execution) it achieves 45,1% , which Google describes as "unprecedented."
In this latest test, the difference compared to other models is remarkable: Claude Sonnet 4.5 scores around 13,6%, GPT-5.1 reaches 17,6%, and the Gemini 3 Pro itself falls short at 31,1%. This gap suggests that Deep Think's parallel reasoning approach is creating a specific advantage in tasks that require exploring many variations before arriving at the correct solution.
Google also highlights the achievements of its predecessor, Gemini 2.5 Deep Think , which recently reached gold medal level at the International Mathematical Olympiad and the finals of the International University Programming Contest. In this way, the company attempts to trace a clear line of progress that ultimately leads to the third generation of the family.
Beyond the laboratory figures, some researchers and AI experts have described Gemini 3 as the most significant advance of the year in large language models. Its ability to work seamlessly with text, video, audio, and code is particularly noteworthy—an approach many see as a step toward systems capable of handling multimodal tasks under a single umbrella.
Success in use, limitations in the free version, and a surge in searches
The strong interest in Gemini 3 is evident not only in benchmarks but also in real-world usage. According to data shared by Google, the Gemini app's monthly active user base grew from approximately 450 million in July to 650 million in October . Part of this growth is directly linked to the launch of Gemini 3 and its deeper integration with services across the company's ecosystem.
This surge is also reflected in search trends. In the annual " Year in Search " report, the term Gemini appears as the most prominent global trending query, surpassing other media topics and sporting events. Google attributes this spike, especially since September, to the announcement of numerous new AI features in products like Chrome, Search, and Android , with Gemini 3 taking center stage.
The less glamorous side of this success is that Google has begun limiting access to certain high-quality features for free accounts. On its support page, the company acknowledges that, to maintain service stability, it has had to reduce the number of instructions and conversations that can be sent, as well as the quality and frequency of image generation using Nano Banana Pro for non-subscribers.
The logic behind this measure is simple: the launch of Gemini 3 Pro and the initial positive experiences have led to a massive increase in usage, to the point that, without restrictions, saturation and a degraded user experience could arise. Google's message leaves the door open to limiting, during specific periods, both the number of prompts and the use of some advanced features.
For those who have found that Gemini 3 Pro meets their needs and want to avoid these limitations, the company offers its paid plans. Google AI Pro , priced at $19,99 per month, provides access to the latest model for intensive use, as well as integrating coding tools, the Gemini assistant in Chrome, and AI within applications like Gmail, Docs, and Drive . Above that, the Google AI Ultra plan , at around $249,99 per month, significantly expands the credits for AI video creation and includes additional benefits, positioning itself as an offering designed for professionals and businesses with very demanding needs.
Integration into the Google ecosystem and new ways of using it
One of the most significant aspects in Europe and Spain is how Gemini 3 integrates into users' daily digital lives . Unlike other models that rely on specific applications or third-party integrations, Google's approach involves bringing AI directly to where people already are.
First, Gemini 3 is integrated into Google Search via a native "AI Mode." Without needing to download anything or switch platforms, subscribers can simply tap this mode and access the model with advanced reasoning capabilities. In practice, this transforms traditional search into a much more conversational and task-oriented experience.
Secondly, the model connects with Google Workspace applications . Tools like Gmail, Docs, Sheets, Drive, and Calendar can leverage Gemini 3 to compose emails, summarize long documents, generate more complex spreadsheets, or assist in project planning. For many European companies, especially SMEs already established in the Google ecosystem, this integration can be a compelling reason to try or adopt the service.
On the development front, Gemini 3 is available through Google AI Studio and Google Cloud , making it easy for technical teams in Spain and other European countries to incorporate the model into their own solutions. From corporate chatbots to internal data analysis assistants, the model can become a key component of new digital products.
Google insists that Gemini 3 requires less input than previous models to bring users' ideas to life, relying on its cutting-edge reasoning and fully multimodal capabilities . This combination of deep integration, improved reasoning, and support for text, images, audio, video, and code is central to the company's strategy.
Competitive impact: pressure on OpenAI and the race for leadership
Gemini 3 's performance has not only technical implications, but is also reshaping the competitive landscape of generative AI. For the first two years after ChatGPT's arrival, OpenAI maintained a clear advantage in perceived model quality and public presence. Now, the field is much tighter.
OpenAI's reaction has been particularly striking. According to reports published by several media outlets, Sam Altman, the company's CEO, declared an internal "code red" following the launch of Gemini 3. In a memo to staff, he reportedly demanded that efforts be focused on improving ChatGPT and that other strategic initiatives be paused, interpreting Google's advance as a serious threat.
This "code red" means redirecting resources and postponing projects that were previously considered priorities, including specialized agents in areas such as healthcare and commerce, an advanced personal assistant, and advertising monetization plans. The message is clear: the absolute priority is to strengthen ChatGPT and maintain its competitive edge against models like Gemini 3 and Deep Think.
Industry analysts point out that Google has a head start in computing power and distribution channels , thanks to its network of data centers and the direct integration of Gemini into mainstream products like its search engine, Android, and Workspace, although other players like Alibaba are strengthening their cloud offerings with AI . OpenAI, for its part, relies heavily on the monetization of its models and the support of partners like Microsoft to sustain its infrastructure investment.
Even so, the battle is far from over. While some forecasts suggest that Google could maintain its dominant model in the short term , it's also emphasized that OpenAI boasts a very large user base and a strong capacity for innovation. Altman himself has hinted that a new reasoning model is on the horizon, specifically designed to regain ground against Gemini 3.
With the accelerated rollout of Gemini 3, the arrival of Deep Think, and the integration of these tools into everyday digital life , Google has managed to regain some lost ground and shift the conversation around its AI ecosystem. The combination of strong benchmark results, high search traction, and a focus heavily on Europe and Spain points to a new phase of intense competition, in which both Google and OpenAI are vying not only for the title of "best model" but also for a dominant position in the next generation of digital services.
