Google Launches Gemini 3: Most Intelligent AI Model Yet

Introduction

On November 18, 2025, Google and Alphabet CEO Sundar Pichai, along with Google DeepMind CEO Demis Hassabis and CTO Koray Kavukcuoglu, announced Gemini 3, Google's most intelligent AI model to date. This release represents nearly two years of development since the launch of the Gemini era and demonstrates Google's continued commitment to advancing AI capabilities across reasoning, multimodality, and agentic behavior.

Gemini 3 arrives at a time when AI adoption has reached unprecedented scale: AI Overviews now serve 2 billion users monthly, the Gemini app surpasses 650 million users per month, 70% of Google Cloud customers use AI, and 13 million developers have built with Google's generative models. This new model builds on this foundation to deliver what Google describes as "a new era of intelligence" that helps users learn, build, and plan anything.

The announcement introduces not just an improved model, but a comprehensive ecosystem including Gemini 3 Deep Think mode for complex problem-solving, the new Google Antigravity agentic development platform, and enhanced agentic capabilities in the Gemini app. These innovations position Gemini 3 as both a powerful standalone model and a foundation for next-generation AI applications.

Introducing Gemini 3

Core Capabilities

Gemini 3 represents a significant leap forward in AI intelligence, with improvements across multiple dimensions:

Enhanced Reasoning: Superior performance on complex reasoning tasks, enabling better problem-solving and analytical thinking
Advanced Multimodality: Improved understanding and generation across text, images, audio, and video with leading multilingual performance
Exceptional Coding: Best-in-class coding and agentic capabilities, making it Google's strongest model for software development
Extended Context: 1 million-token context window for processing large documents, codebases, and long conversations
Improved Tool Use: More reliable and consistent tool usage for agentic applications

These capabilities make Gemini 3 suitable for a wide range of applications, from learning complex topics to building sophisticated applications to planning multi-step workflows.

Performance Benchmarks

Gemini 3 demonstrates exceptional performance across key benchmarks:

Coding and Development:

WebDev Arena: Scores an impressive 1487 Elo, topping the leaderboard
Terminal-Bench 2.0: Achieves 54.2% accuracy, testing tool use ability to operate a computer via terminal
SWE-bench Verified: Scores 76.2%, greatly outperforming Gemini 2.5 Pro on this benchmark that measures coding agents

Long-Horizon Planning:

Vending-Bench 2: Tops the leaderboard, demonstrating superior long-horizon planning capabilities
Maintains consistent tool usage and decision-making for a full simulated year of operation
Generates significantly higher returns compared to other frontier models

These benchmark results demonstrate Gemini 3's position as a leading model for both coding tasks and complex, multi-step agentic workflows.

Gemini 3 Deep Think Mode

Advanced Problem-Solving

Gemini 3 Deep Think represents an even more advanced mode that pushes the boundaries of intelligence for complex problems. This mode is designed for scenarios requiring deep reasoning, extensive analysis, and sophisticated problem-solving capabilities.

While Gemini 3 Pro is available immediately, Google is taking extra time for safety evaluations and input from safety testers before making Deep Think mode available to Google AI Ultra subscribers in the coming weeks. This careful approach reflects Google's commitment to responsible AI development, particularly for the most advanced capabilities.

Deep Think mode is expected to excel at:

Complex mathematical and scientific problems
Multi-step logical reasoning
Advanced coding challenges
Deep analysis of technical documents
Sophisticated planning tasks

Learn Anything

Multimodal Learning Capabilities

Gemini 3's enhanced multimodal capabilities enable powerful learning experiences that go beyond traditional text-based interactions. The model can process and understand diverse content types to create personalized learning materials.

Example Use Cases:

Preserving Family Traditions: Gemini 3 can decipher and translate handwritten recipes in different languages into a shareable family cookbook. This demonstrates the model's ability to understand handwritten text, translate between languages, and organize information in meaningful ways.

Academic Learning: Users can provide Gemini 3 with academic papers, long video lectures, or tutorials, and the model can generate code for interactive flashcards, visualizations, or other formats that help master the material. This transforms passive content consumption into active learning experiences.

Sports Analysis: Gemini 3 can analyze videos of activities like pickleball matches, identify areas for improvement, and generate training plans for overall form improvements. This showcases the model's ability to understand video content, extract meaningful insights, and create actionable recommendations.

AI Mode in Search

To help users make better sense of information on the web, AI Mode in Search now uses Gemini 3 to enable new generative UI experiences. These include immersive visual layouts and interactive tools and simulations, all generated completely on the fly based on user queries.

For example, users can learn complex topics like how RNA polymerase works through generative UI in AI Mode, with interactive visualizations and explanations tailored to their query. This represents a significant advancement in how search engines can help users understand and explore information.

Build Anything

Exceptional Coding Capabilities

Building on the success of Gemini 2.5 Pro, Gemini 3 delivers on the promise of bringing any idea to life for developers. It's exceptional at zero-shot generation and handles complex prompts and instructions to render richer, more interactive web UI.

Key Coding Achievements:

Best Vibe Coding Model: Gemini 3 is the best vibe coding and agentic coding model Google has ever built
WebDev Arena Leader: Tops the leaderboard with 1487 Elo score
Terminal Operations: Achieves 54.2% on Terminal-Bench 2.0, demonstrating strong tool use capabilities
Coding Agents: Greatly outperforms 2.5 Pro on SWE-bench Verified (76.2%)

Development Platforms

Developers can now build with Gemini 3 across multiple platforms:

Google AI Studio: Web-based interface for prototyping and building with Gemini
Vertex AI: Enterprise-grade platform for production deployments
Gemini CLI: Command-line interface for developers
Google Antigravity: New agentic development platform (see below)
Third-Party Platforms: Available in Cursor, GitHub, JetBrains, Manus, Replit, and more

Creative Coding Examples

Gemini 3 enables developers to create rich, interactive experiences:

Retro 3D Spaceship Games: Code games with richer visualizations and improved interactivity
3D Voxel Art: Build, deconstruct, and remix detailed 3D voxel art using code
Sci-Fi Worlds: Create playable sci-fi worlds with shaders
Interactive Web UI: Vibe code richer, more interactive web UI and apps

These examples demonstrate Gemini 3's ability to understand complex creative requirements and generate sophisticated code that brings ideas to life.

Google Antigravity: Agentic Development Platform

A New Development Experience

As model intelligence accelerates with Gemini 3, Google has reimagined the entire developer experience with Google Antigravity, a new agentic development platform that enables developers to operate at a higher, task-oriented level.

Using Gemini 3's advanced reasoning, tool use, and agentic coding capabilities, Google Antigravity transforms AI assistance from a tool in a developer's toolkit into an active partner. While the core experience is a familiar AI IDE, Antigravity's agents have been elevated to a dedicated surface with direct access to the editor, terminal, and browser.

Key Features:

Autonomous Planning: Agents can autonomously plan complex, end-to-end software tasks
Simultaneous Execution: Agents execute multiple tasks simultaneously on your behalf
Self-Validation: Agents validate their own code to ensure correctness
Direct Access: Agents have direct access to editor, terminal, and browser
Task-Oriented: Developers work at a higher level, describing what they want rather than how to implement it

Integrated Models

Google Antigravity comes tightly coupled with multiple advanced models:

Gemini 3 Pro: Powers the core agentic workflow and reasoning
Gemini 2.5 Computer Use: Handles browser control and computer interaction
Nano Banana (Gemini 2.5 Image): Top-rated image editing model for visual tasks

This multi-model approach ensures that Antigravity can handle diverse development tasks, from coding to browser automation to image editing.

Example Workflow

In a demonstration, Google Antigravity uses Gemini 3 to drive an end-to-end agentic workflow for a flight tracker app. The agent independently:

Plans the application architecture
Codes the complete application
Validates execution through browser-based computer use

This demonstrates how Antigravity enables developers to describe high-level goals while agents handle the implementation details autonomously.

Plan Anything

Long-Horizon Planning Capabilities

Since introducing the agentic era with Gemini 2, Google has made significant progress in advancing Gemini's coding agent abilities and improving its ability to reliably plan ahead over longer horizons. Gemini 3 demonstrates this advancement by topping the leaderboard on Vending-Bench 2, which tests longer horizon planning by managing a simulated vending machine business.

Key Planning Improvements:

Consistent Tool Usage: Maintains consistent tool usage over extended periods
Long-Term Decision Making: Makes reliable decisions for a full simulated year of operation
Higher Returns: Drives significantly higher returns without drifting off task
Multi-Step Workflows: Handles complex, multi-step workflows from start to finish

Real-World Agentic Applications

Gemini 3's improved planning capabilities enable better assistance in everyday life. By combining deeper reasoning with improved, more consistent tool use, Gemini 3 can take action on your behalf by navigating complex, multi-step workflows:

Booking Services: Navigate complex booking processes for local services
Inbox Organization: Organize email inboxes with multi-step categorization and prioritization
Task Automation: Complete complex tasks that require multiple steps and decisions

All of this happens under user control and guidance, ensuring that agents remain helpful tools rather than autonomous systems operating without oversight.

Gemini Agent in the App

Google AI Ultra subscribers can try these agentic capabilities in the Gemini app with Gemini Agent today. This feature demonstrates Google's progress in improving Gemini's agentic capabilities and provides a preview of how AI agents can assist with everyday tasks.

Google has learned a lot from improving Gemini's agentic capabilities and is excited to see how users leverage these features as they expand to more Google products soon.

Building Gemini 3 Responsibly

Comprehensive Safety Evaluations

Gemini 3 is Google's most secure model yet and has undergone the most comprehensive set of safety evaluations of any Google AI model to date. The model shows:

Reduced Sycophancy: Less tendency to agree with users regardless of accuracy
Increased Resistance to Prompt Injections: Better protection against malicious prompt manipulation
Improved Cyberattack Protection: Enhanced safeguards against misuse via cyberattacks

Safety Framework

In addition to Google's in-house testing for critical domains in the Frontier Safety Framework, the company has:

Partnered with Experts: Worked with world-leading subject matter experts on evaluations
Early Access to Regulators: Provided early access to bodies like the UK AISI (AI Safety Institute)
Independent Assessments: Obtained independent assessments from industry experts including Apollo, Vaultis, Dreadnode, and more

This comprehensive approach to safety evaluation reflects Google's commitment to responsible AI development, particularly for models as advanced as Gemini 3.

Model Card

For more detailed information about Gemini 3's safety features, capabilities, and limitations, Google has published a comprehensive model card that provides transparency about the model's development, evaluation, and deployment considerations.

Availability and Rollout

Current Availability

As of November 18, 2025, Gemini 3 is rolling out across multiple platforms:

For Everyone:

Gemini app (available to all users)

For Google AI Pro and Ultra Subscribers:

AI Mode in Search (enhanced search experiences with Gemini 3)

For Developers:

Gemini API in AI Studio
Google Antigravity (new agentic development platform)
Gemini CLI

For Enterprises:

Vertex AI (enterprise-grade deployment)
Gemini Enterprise

Third-Party Platforms:

Cursor
GitHub
JetBrains
Manus
Replit
And more

Coming Soon

Gemini 3 Deep Think Mode:

Currently undergoing additional safety evaluations
Will be available to Google AI Ultra subscribers in the coming weeks
Represents the most advanced reasoning capabilities

Additional Models:

Google plans to release additional models to the Gemini 3 series soon
These will expand the capabilities available to users and developers

Strategic Implications

Full-Stack AI Approach

Gemini 3's launch reinforces Google's differentiated full-stack approach to AI innovation, which spans:

Leading Infrastructure: Purpose-built AI infrastructure optimized for Gemini
World-Class Research: Innovations from Google DeepMind
Advanced Models: The Gemini 3 family of models
Comprehensive Tooling: Development platforms and APIs
Global Products: Integration into products reaching billions of users

This full-stack approach enables Google to get advanced capabilities to the world faster than ever, as demonstrated by the rapid adoption of previous Gemini versions.

Market Position

Gemini 3's benchmark performance and new capabilities position Google strongly in the competitive AI landscape:

Coding Leadership: Top performance on coding benchmarks
Agentic Capabilities: Advanced agentic features for autonomous task completion
Multimodal Excellence: Leading multimodal understanding and generation
Enterprise Ready: Comprehensive platform for enterprise deployment

The introduction of Google Antigravity also demonstrates Google's commitment to not just providing models, but creating complete development experiences that enable developers to build sophisticated AI applications.

Developer Ecosystem

With 13 million developers already building with Google's generative models, Gemini 3 and Google Antigravity represent significant investments in the developer ecosystem. The availability across multiple platforms, from Google's own tools to third-party IDEs, ensures developers can work in their preferred environments while leveraging Gemini 3's capabilities.

Use Cases and Applications

Learning and Education

Gemini 3's multimodal capabilities enable powerful learning experiences:

Interactive Learning Materials: Generate flashcards, visualizations, and interactive guides from academic content
Multilingual Translation: Translate and preserve handwritten documents and recipes
Video Analysis: Analyze instructional videos and generate personalized learning plans
Complex Topic Explanation: Break down complex topics with interactive visualizations

Software Development

Developers can leverage Gemini 3 for:

Code Generation: Generate complete applications from high-level descriptions
Interactive UI Development: Create rich, interactive web interfaces
Game Development: Build games with advanced graphics and gameplay
Agentic Development: Use Google Antigravity for autonomous software development

Business Automation

Enterprises can use Gemini 3 for:

Workflow Automation: Automate complex, multi-step business processes
Customer Service: Deploy advanced conversational agents
Data Analysis: Analyze large datasets and generate insights
Content Creation: Generate marketing materials, documentation, and creative content

Personal Assistance

Individual users can benefit from:

Task Planning: Plan and execute complex personal workflows
Email Management: Organize and prioritize inboxes
Learning Support: Get help understanding complex topics
Creative Projects: Generate code for creative coding projects

Technical Architecture

Model Improvements

While Google hasn't disclosed specific architectural details, Gemini 3's performance improvements suggest several technical advancements:

Enhanced Reasoning Architecture: Improved ability to handle complex reasoning tasks
Better Multimodal Integration: More sophisticated processing of text, images, audio, and video
Advanced Tool Use: More reliable integration with external tools and APIs
Extended Context Processing: Efficient handling of 1 million-token context windows
Optimized Inference: Better performance-to-cost ratio

Training and Development

Gemini 3 builds on Google DeepMind's research advances and lessons learned from previous Gemini versions. The model likely incorporates:

Improved Training Data: Higher quality and more diverse training datasets
Advanced Training Techniques: State-of-the-art training methodologies
Safety-First Development: Comprehensive safety evaluations throughout development
Efficiency Optimizations: Better performance per parameter

Challenges and Considerations

Safety and Alignment

While Gemini 3 has undergone comprehensive safety evaluations, deploying such advanced AI capabilities requires ongoing attention to:

Misuse Prevention: Ensuring the model isn't used for harmful purposes
Bias Mitigation: Addressing potential biases in model outputs
Accuracy: Maintaining high accuracy while enabling advanced capabilities
Transparency: Providing clear information about model capabilities and limitations

Integration Complexity

Organizations adopting Gemini 3 may face challenges in:

Workflow Integration: Integrating agentic capabilities into existing business processes
Change Management: Training teams to work effectively with AI agents
Governance: Establishing policies and controls for AI agent usage
Cost Management: Understanding and optimizing costs for advanced AI capabilities

Developer Adoption

While Google Antigravity represents an innovative development experience, developers will need to:

Learn New Workflows: Adapt to agentic development paradigms
Trust Agent Autonomy: Develop confidence in agents handling complex tasks
Maintain Control: Balance agent autonomy with developer oversight
Optimize Prompts: Learn to effectively describe desired outcomes

Future Developments

Additional Gemini 3 Models

Google has announced plans to release additional models to the Gemini 3 series soon. These will likely include:

Specialized Variants: Models optimized for specific use cases
Efficiency Models: More cost-effective options for common tasks
Domain-Specific Models: Models fine-tuned for particular industries or applications

Platform Expansion

Google plans to expand Gemini 3 availability to more products and services:

More Google Products: Integration into additional Google services
Enhanced Agent Capabilities: Continued improvement of agentic features
Developer Tools: Additional tools and platforms for developers
Enterprise Features: More enterprise-specific capabilities

Research Directions

Gemini 3's launch represents ongoing research in several areas:

Agentic AI: Advancing autonomous agent capabilities
Multimodal Understanding: Improving cross-modal reasoning
Long-Horizon Planning: Enhancing planning over extended timeframes
Safety and Alignment: Developing safer, more aligned AI systems

Conclusion

The launch of Gemini 3 represents a significant milestone in Google's AI journey and the broader AI industry. With enhanced reasoning, exceptional coding capabilities, advanced multimodal understanding, and sophisticated agentic features, Gemini 3 positions Google as a leader in the next generation of AI systems.

The introduction of Google Antigravity demonstrates Google's commitment to not just providing powerful models, but creating complete development experiences that enable developers to build sophisticated AI applications more easily. The platform's agentic approach represents a shift toward higher-level, task-oriented development that could transform how software is built.

Gemini 3's comprehensive safety evaluations and responsible development approach reflect Google's understanding that advanced AI capabilities must be developed and deployed carefully. The model's availability across multiple platforms, from consumer apps to enterprise tools, ensures that these capabilities can benefit a wide range of users.

As Google continues to release additional Gemini 3 models and expand platform capabilities, the impact of this release will likely extend far beyond the initial announcement. The combination of powerful models, innovative development platforms, and comprehensive safety measures positions Gemini 3 as a foundation for the next era of AI applications.

For users, developers, and enterprises, Gemini 3 offers new possibilities for learning, building, and planning. Whether you're preserving family recipes, building interactive applications, or automating complex business workflows, Gemini 3 provides the intelligence and capabilities to bring ideas to life.

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