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A new era of intelligence with Gemini 3
Gemini 3 is our most intelligent model that helps you bring any idea to life.

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A note from Google and Alphabet CEO Sundar Pichai:

Nearly two years ago we kicked off the Gemini era, one of our biggest scientific and product endeavors ever undertaken as a company. Since then, it’s been incredible to see how much people love it. AI Overviews now have 2 billion users every month. The Gemini app surpasses 650 million users per month, more than 70% of our Cloud customers use our AI, 13 million developers have built with our generative models, and that is just a snippet of the impact we’re seeing.

And we’re able to get advanced capabilities to the world faster than ever, thanks to our differentiated full stack approach to AI innovation — from our leading infrastructure to our world-class research and models and tooling, to products that reach billions of people around the world.

Every generation of Gemini has built on the last, enabling you to do more. Gemini 1’s breakthroughs in native multimodality and long context window expanded the kinds of information that could be processed — and how much of it. Gemini 2 laid the foundation for agentic capabilities and pushed the frontiers on reasoning and thinking, helping with more complex tasks and ideas, leading to Gemini 2.5 Pro topping LMArena for over six months.

And now we’re introducing Gemini 3, our most intelligent model, that combines all of Gemini’s capabilities together so you can bring any idea to life.

It’s state-of-the-art in reasoning, built to grasp depth and nuance — whether it’s perceiving the subtle clues in a creative idea, or peeling apart the overlapping layers of a difficult problem. Gemini 3 is also much better at figuring out the context and intent behind your request, so you get what you need with less prompting. It’s amazing to think that in just two years, AI has evolved from simply reading text and images to reading the room.

And starting today, we’re shipping Gemini at the scale of Google. That includes Gemini 3 in AI Mode in Search with more complex reasoning and new dynamic experiences. This is the first time we are shipping Gemini in Search on day one. Gemini 3 is also coming today to the Gemini app, to developers in AI Studio and Vertex AI, and in our new agentic development platform, Google Antigravity — more below.

Like the generations before it, Gemini 3 is once again advancing the state of the art. In this new chapter, we’ll continue to push the frontiers of intelligence, agents, and personalization to make AI truly helpful for everyone.

We hope you like Gemini 3, we’ll keep improving it, and look forward to seeing what you build with it. Much more to come!

Introducing Gemini 3: our most intelligent model that helps you bring any idea to life

Demis Hassabis, CEO of Google DeepMind and Koray Kavukcuoglu, CTO of Google DeepMind and Chief AI Architect, Google, on behalf of the Gemini team

Today we’re taking another big step on the path toward AGI and releasing Gemini 3.

It’s the best model in the world for multimodal understanding and our most powerful agentic and vibe coding model yet, delivering richer visualizations and deeper interactivity — all built on a foundation of state-of-the-art reasoning.

We’re beginning the Gemini 3 era by releasing Gemini 3 Pro in preview and making it available today across a suite of Google products so you can use it in your daily life to learn, build and plan anything. We’re also introducing Gemini 3 Deep Think — our enhanced reasoning mode that pushes Gemini 3 performance even further — and giving access to safety testers before making it available to Google AI Ultra subscribers.

State-of-the-art reasoning with unprecedented depth and nuance

Gemini 3 Pro can bring any idea to life with its state-of-the-art reasoning and multimodal capabilities. It significantly outperforms 2.5 Pro on every major AI benchmark.

It tops the LMArena Leaderboard with a breakthrough score of 1501 Elo. It demonstrates PhD-level reasoning with top scores on Humanity’s Last Exam (37.5% without the usage of any tools) and GPQA Diamond (91.9%). It also sets a new standard for frontier models in mathematics, achieving a new state-of-the-art of 23.4% on MathArena Apex.

Beyond text, Gemini 3 Pro redefines multimodal reasoning with 81% on MMMU-Pro and 87.6% on Video-MMMU. It also scores a state-of-the-art 72.1% on SimpleQA Verified, showing great progress on factual accuracy. This means Gemini 3 Pro is highly capable at solving complex problems across a vast array of topics like science and mathematics with a high degree of reliability.

Gemini 3 Pro also brings a new level of depth and nuance to every interaction. Its responses are smart, concise and direct, trading cliché and flattery for genuine insight — telling you what you need to hear, not just what you want to hear. It acts as a true thought partner that gives you new ways to understand information and express yourself, from translating dense scientific concepts by generating code for high-fidelity visualizations to creative brainstorming.

Gemini 3 can code a visualization of plasma flow in a tokamak and write a poem capturing the physics of fusion.

Gemini 3 Deep Think

Gemini 3 Deep Think mode pushes the boundaries of intelligence even further, delivering a step-change in Gemini 3’s reasoning and multimodal understanding capabilities to help you solve even more complex problems.

In testing, Gemini 3 Deep Think outperforms Gemini 3 Pro’s already impressive performance on Humanity’s Last Exam (41.0% without the use of tools) and GPQA Diamond (93.8%). It also achieves an unprecedented 45.1% on ARC-AGI-2 (with code execution, ARC Prize Verified), demonstrating its ability to solve novel challenges.

Gemini 3 Deep Think mode excels on some of the most challenging AI benchmarks. See details on our evaluation methodology.

Gemini 3 helps you learn, build and plan anything

Learn anything

Gemini was built from the start to seamlessly synthesize information about any topic across multiple modalities, including text, images, video, audio and code. Gemini 3 pushes the frontier of multimodal reasoning to help you learn in ways that make sense for you by combining its state-of-the-art reasoning, vision and spatial understanding, leading multilingual performance, and 1 million-token context window.

For example, if you want to learn how to cook in your family tradition, Gemini 3 can decipher and translate handwritten recipes in different languages into a shareable family cookbook. Or if you want to learn about a new topic, you can give it academic papers, long video lectures or tutorials and it can generate code for interactive flashcards, visualizations or other formats that will help you master the material. It can even analyze videos of your pickleball match, identify areas where you can improve and generate a training plan for overall form improvements.

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

Build anything

Building on the success of 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.

Gemini 3 is the best vibe coding and agentic coding model we’ve ever built – making our products more autonomous and boosting developer productivity. It tops the WebDev Arena leaderboard by scoring an impressive 1487 Elo. It also scores 54.2% on Terminal-Bench 2.0, which tests a model’s tool use ability to operate a computer via terminal and it greatly outperforms 2.5 Pro on SWE-bench Verified (76.2%), a benchmark that measures coding agents.

You can now build with Gemini 3 in Google AI Studio, Vertex AI, Gemini CLI and our new agentic development platform, Google Antigravity. It’s also available in third-party platforms like Cursor, GitHub, JetBrains, Manus, Replit and more.

Introducing a new agent-first development experience

As model intelligence accelerates with Gemini 3, we have the opportunity to reimagine the entire developer experience. Today we’re releasing Google Antigravity, our 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 of Google Antigravity is a familiar AI IDE experience, its agents have been elevated to a dedicated surface and given direct access to the editor, terminal and browser. Now, agents can autonomously plan and execute complex, end-to-end software tasks simultaneously on your behalf while validating their own code.

In addition to Gemini 3 Pro, Google Antigravity also comes tightly coupled with our latest Gemini 2.5 Computer Use model for browser control and our top-rated image editing model Nano Banana (Gemini 2.5 Image).

Google Antigravity uses Gemini 3 to drive an end-to-end agentic workflow for a flight tracker app. The agent independently plans, codes the application and validates its execution through browser-based computer use.

Plan anything

Since introducing the agentic era with Gemini 2, we’ve made a lot of progress, not only advancing Gemini’s coding agent abilities, but also improving its ability to reliably plan ahead over longer horizons. Gemini 3 demonstrates this by topping the leaderboard on Vending-Bench 2, which tests longer horizon planning by managing a simulated vending machine business. Gemini 3 Pro maintains consistent tool usage and decision-making for a full simulated year of operation, driving higher returns without drifting off task.

Gemini 3 Pro demonstrates better long-horizon planning to generate significantly higher returns compared to other frontier models.

This means Gemini 3 can better help you get things done in everyday life. By combining deeper reasoning with improved, more consistent tool use, Gemini 3 can take action on your behalf by navigating more complex, multi-step workflows from start to finish — like booking local services or organizing your inbox — all while under your control and guidance.

Google AI Ultra subscribers can try these agentic capabilities in the Gemini app with Gemini Agent today. We’ve learned a lot improving Gemini’s agentic capabilities, and we’re excited to see how you use it as we expand to more Google products soon.

Building Gemini 3 responsibly

Gemini 3 is our 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, increased resistance to prompt injections and improved protection against misuse via cyberattacks.

In addition to our in-house testing for the critical domains in our Frontier Safety Framework, we’ve also partnered on evaluations with world-leading subject matter experts, provided early access to bodies like the UK AISI, and obtained independent assessments from industry experts like Apollo, Vaultis, Dreadnode and more. For more information, see the Gemini 3 model card.
The next era of Gemini

This is just the start of the Gemini 3 era. As of today, Gemini 3 starts rolling out:

For everyone in the Gemini app and for Google AI Pro and Ultra subscribers in AI Mode in Search

For developers in the Gemini API in AI Studio, our new agentic development platform, Google Antigravity; and Gemini CLI

For enterprises in Vertex AI and Gemini Enterprise

For Gemini 3 Deep Think mode, we’re taking extra time for safety evaluations and input from safety testers before making it available to Google AI Ultra subscribers in the coming weeks.

We plan to release additional models to the Gemini 3 series soon so you can do more with AI. We look forward to getting your feedback and seeing what you learn, build and plan with Gemini.
Collection

Introducing Gemini 3

Gemini 3, our most intelligent model, combines all of Gemini’s capabilities together so you can bring any idea to life.

See more
November 18, 2025
Introducing Google Antigravity
Every advancement in model intelligence for coding has encouraged us to rethink how development should be done. The Integrated Development Environment (IDE) of today is a far cry from the IDE of just a few years ago. Gemini 3, our most intelligent model, represents a step-change for agentic coding, and requires us to think about what the next step-change of an IDE should be.

Today, we are introducing Google Antigravity, our new agentic development platform. While the core is a familiar AI-powered IDE experience with the best of Google’s models, Antigravity is evolving the IDE towards an agent-first future with browser control capabilities, asynchronous interaction patterns, and an agent-first product form factor that together, enable agents to autonomously plan and execute complex, end-to-end software tasks.

Why we built Antigravity

We want Antigravity to be the home base for software development in the era of agents. Our vision is to ultimately enable anyone with an idea to experience liftoff and build that idea into reality. From today, Google Antigravity is available in public preview at no charge, with generous rate limits on Gemini 3 Pro usage.

With models like Gemini 3, we have started hitting the point in agentic intelligence where models are capable of running for longer periods of time without intervention across multiple surfaces. Not yet for days at a time without intervention, but we’re getting closer to a world where we interface with agents at higher abstractions over individual prompts and tool calls. In this world, the product surface that enables communication between the agent and user should look and feel different — and Antigravity is our answer to this.

Core tenets

Antigravity is our first product that brings four key tenets of collaborative development together: trust, autonomy, feedback, and self-improvement.

Trust

Most products today live in one of two extremes: either they show the user every single action and tool call the agent has made or they only show the final code change with no context on how the agent got there, and with no easy way to verify the work. Neither engenders user trust in the work that the agent undertook. Antigravity provides context on agentic work at a more natural task-level abstraction, with the necessary and sufficient set of artifacts and verification results, for the user to gain that trust. There is a concerted emphasis for the agent to thoroughly think through verification of its work, not just the work itself.

In a conversation with an agent in Antigravity, the user sees tool calls grouped within tasks, monitoring high-level summaries and progress along that task. As the agent works, it produces Artifacts, tangible deliverables in formats that are easier for users to validate than raw tool calls, such as task lists, implementation plans, walkthroughs, screenshots, and browser recordings. Agents in Antigravity use Artifacts to communicate to the user that it understands what it is doing and that it is thoroughly verifying its work.

View the Agent’s task list,review the implementation plan post-research and pre-implementation,or scan the walkthrough at completion.

Autonomy

Today, the most intuitive product form factor is working synchronously with an agent embedded within a surface (such as an editor, browser, or terminal). That is why Antigravity’s primary “Editor view” is a state-of-the-art AI-powered IDE experience, with Tab completions, in-line Commands, and a fully functioning agent in the side panel.

That being said, we are transitioning to an era, with models like Gemini 3, when agents can operate across all of these surfaces simultaneously and autonomously:

Autonomously,an Antigravity Agent writes code for a new frontend feature,uses the terminal to launch localhost,and actuates the browser to test that the new feature works.

We also believe agents deserve a form factor that exposes this autonomy optimally and allows users to interact with them more asynchronously. So, in addition to the IDE-like Editor surface, we are introducing an agent-first Manager surface, which flips the paradigm of agents being embedded within surfaces to one where the surfaces are embedded into the agent. You can think of it like a mission control for spawning, orchestrating, and observing multiple agents across multiple workspaces in parallel.

User spawned an Agent to do background research in a different workspace while focusing on a more involved task in the foreground,using the Inbox and side panel in the Agent Manager to be notified of progress.

We decided not to try to squeeze both the asynchronous Manager experience and the synchronous Editor experience into a single window, rather optimizing for instantaneous handoffs between the Manager and Editor. Antigravity is designed to be forward-looking, intuitively bringing development to the asynchronous era as models like Gemini continue to rapidly get smarter.

Feedback

A core failing of a remote-only form factor is the inability to iterate easily with the agent. Agentic intelligence has indeed improved significantly, but it is still not perfect. An agent being able to complete 80% of the work should be useful, but if there is no easy way to provide feedback, then it becomes more work than benefit to resolve the remaining 20%. User feedback allows us to not treat an agent as a black-or-white system that either is perfect or unhelpful. Antigravity is starting with local operation, allowing intuitive async user feedback across every surface and Artifact, whether it be Google-doc-style comments on text Artifacts or select-and-comment feedback on screenshots. This feedback is automatically incorporated into the agent’s execution without requiring you to stop the agent’s process.

An example of feedback on textual Artifacts such as an implementation plan and an example of feedback on a visual Artifact such as a screenshot taken by the Agent.

Self-improvement

Antigravity treats learning as a core primitive, with agent actions both retrieving from and contributing to a knowledge base. This knowledge management allows the agent to learn from past work. This could be important explicit information such as useful snippets of code or derived architecture, but could also be more abstract, such as the series of steps taken to successfully complete a particular subtask.

Agent learning from work and feedback to generate and leverage knowledge items,viewable from the Agent Manager.

Try Antigravity today

We believe Antigravity’s product form factor represents the next fundamental step function in agent-assisted development. Thus, our goal is to channel it into the best product offering possible for end users. Today’s public preview includes the following features:
- Google Antigravity for individuals at no charge
- Compatibility with macOS, Linux, and Windows
- Access to Google’s Gemini 3, Anthropic’s Claude Sonnet 4.5 models, and OpenAI’s GPT-OSS within the agent, offering developers model optionality ¹
Learn more about the features of Antigravity in our docs and read more about how Antigravity can assist you by browsing various use cases. New features drop frequently, so keep up-to-date with this blog and socials at X, LinkedIn, and YouTube.

Experience liftoff in 3… 2… 1…
[1] We provide access to models to the degree we have capacity, with rate limits to prevent abuse and that are refreshed every five hours. Under the hood, the rate limits are correlated with the amount of work done by the agent, which can differ from prompt to prompt. Thus, you may get many more prompts if your tasks are more straightforward and the agent can complete the work quickly, and the opposite is also true. Our modeling suggests that a very small fraction of power users ever hit the per-five-hour rate limit, so our hope is that this is something that you won’t have to worry about, and you feel unrestrained in your usage of Antigravity. ↩
November 18, 2025