Explore Gemini 3, Google’s new AI model that outperforms benchmarks across multimodal, reasoning, and agent tasks. Learn about its innovative features, such as Generative UI, Antigravity IDE, and its rapid adoption by millions of users.
Gemini 3 Has Arrived: Forget Chatting, Create a World with a Single Sentence (Includes Transcript of Communication with the Gemini Team)
Gemini 3 is here, and it’s extraordinary.
On November 18th, Google’s highly anticipated new AI model, Gemini 3, was officially launched. This release marks a return to Google's rhythm, and it’s a game-changer.
Dominating the Benchmarks
Gemini 3 has not only shattered records across various benchmarks, but it has also outperformed many specialized models, including reasoning and multimodal models.
Google describes Gemini 3 as a model with native multimodal, powerful reasoning, and agent capabilities—all integrated into a single system. This combination allows users to tap into all these features simultaneously.
Today, Gemini 3 has set new highs on evaluation lists that were previously dominated by specialized models. Here are some highlights:
- Multimodal Abilities: Gemini 3 has reached new heights in both understanding and reasoning. For instance, it set records with scores of 81% on MMMU-Pro and 87.6% on Video-MMMU.
Case Study: Gemini 3’s visual abilities integrate reasoning, solving ambiguities caused by inconsistent symbols, such as in OCR recognition of old handwritten tables, which even outperformed trained students.
- Reasoning Ability: Gemini 3 broke the LMArena leaderboard with a groundbreaking score of 1501. It also achieved an impressive 72.1% on SimpleQA Verified, a major leap in factual accuracy.
Case Study: In its "Deep Think" reasoning mode, Gemini 3 further excelled, achieving 41.0% on "Human’s Last Exam" and 93.8% on GPQA Diamond, surpassing its predecessors by a wide margin.
- Agent Capabilities: On the WebDev Arena leaderboard, Gemini 3 scored 1487 ELO, and it outperformed previous models on Terminal-Bench 2.0 and SWE-bench Verified, showcasing its ability to use computer tools and code intelligently.
One of the standout features is its ability to help you with real-world tasks. For example, it can search for and book a rental car within a specified budget, all while utilizing Google’s ecosystem to complete the task.
Full-Scale Generative UI Deployment
Google is going even further by changing how users interact with Gemini. The new Generative UI feature creates immersive, interactive experiences dynamically in response to a single prompt, revolutionizing the way users interact with AI.
Instead of a traditional Q&A format, Gemini 3 can generate entire web apps, games, or tools based on a single word or complex instruction. For example, asking about the "Three-Body Problem" will generate an interactive simulation that allows users to explore and adjust variables in real-time.
These new interfaces will be rolled out in Google’s search results, where a simple query can return an entire interactive app, offering an entirely new way to engage with information.
A New Paradigm for Software Development: Antigravity
Not content with just revolutionizing search and AI interactions, Google also introduced Antigravity, a new AI-powered IDE that allows agents to take control of software development.
In this new platform, agents can independently design, test, and refine applications, learning your coding style and preferences as they go. This promises to change the landscape of software engineering by allowing AI to handle complex development tasks while users focus on higher-level goals.
Massive Growth and Adoption
Google’s confidence in Gemini 3 is further validated by impressive user growth. From 450 million users last quarter, Gemini has now surpassed 650 million users, with 13 million developers leveraging Google’s models for their own projects.
The success of Gemini 3, combined with the viral popularity of Google’s Nano Banana, has helped Google solidify its AI dominance.
Transcript of Conversation with the Gemini Team
Q: Can you share some "Aha moments" during the development of this new model?
Gemini Team: One of the first moments for me was seeing how easily the model could generate complex games from a simple prompt. The ability to create 3D visualizations and play an actual game based on minimal input was astounding. Another "Aha moment" occurred when we used it to translate a Gujarati poem and observed how it not only translated but also creatively adapted the text, showcasing its deep linguistic understanding.
Q: How do you see Antigravity fitting into the current ecosystem?
Gemini Team: Antigravity represents a new era for IDEs. While other IDEs provide tools for developers, Antigravity positions the AI as an active collaborator, helping engineers solve real-world problems and providing a richer, more interactive experience.
Q: What are the expected consumer use cases for Gemini agents?
Gemini Team: For everyday users, Gemini can handle complex tasks like finding concert tickets or organizing your email inbox. It can also help you complete errands like booking a rental car or classifying emails automatically, saving you time and effort.
Q: Why has Gemini seen such rapid adoption?
Gemini Team: The viral success of Nano Banana, particularly in markets like Thailand and Indonesia, has played a significant role. Students have also been a key demographic, using Gemini for homework and academic tasks.
Q: Is Antigravity competing with Cursor?
Gemini Team: We’re actually collaborating with Cursor, as we recognize the potential of AI to revolutionize software development across industries. We’re focused on helping users where they are, and the AI ecosystem is still evolving.
Q: Can we expect further advancements in Gemini models?
Gemini Team: Absolutely. We’re always iterating and learning from user feedback. As we continue to develop, we’ll refine these models and build on the capabilities of Gemini 3. Flash and Flashlight will be part of that ongoing evolution.
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