Introducing Gemini 2.0: our new AI model for the agentic era

Introducing Gemini 2.0: our new AI model for the agentic era

A note from Google and Alphabet CEO Sundar Pichai:

Information is at the core of human progress. It’s why we’ve focused for more than 26 years on our mission to organize the world’s information and make it accessible and useful. And it’s why we continue to push the frontiers of AI to organize that information across every input and make it accessible via any output, so that it can be truly useful for you.

That was our vision when we introduced Gemini 1.0 last December. The first model built to be natively multimodal, Gemini 1.0 and 1.5 drove big advances with multimodality and long context to understand information across text, video, images, audio and code, and process a lot more of it.

Now millions of developers are building with Gemini. And it’s helping us reimagine all of our products — including all 7 of them with 2 billion users — and to create new ones. NotebookLM is a great example of what multimodality and long context can enable for people, and why it’s loved by so many.

Over the last year, we have been investing in developing more agentic models, meaning they can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision.

Today we’re excited to launch our next era of models built for this new agentic era: introducing Gemini 2.0, our most capable model yet. With new advances in multimodality — like native image and audio output — and native tool use, it will enable us to build new AI agents that bring us closer to our vision of a universal assistant.

We’re getting 2.0 into the hands of developers and trusted testers today. And we’re working quickly to get it into our products, leading with Gemini and Search. Starting today our Gemini 2.0 Flash experimental model will be available to all Gemini users. We're also launching a new feature called Deep Research, which uses advanced reasoning and long context capabilities to act as a research assistant, exploring complex topics and compiling reports on your behalf. It's available in Gemini Advanced today, and you can learn more on our website.

No product has been transformed more by AI than Search. Our AI Overviews now reach 1 billion people, enabling them to ask entirely new types of questions — quickly becoming one of our most popular Search features ever. As a next step, we’re bringing the advanced reasoning capabilities of Gemini 2.0 to AI Overviews to tackle more complex topics and multi-step questions, including advanced math equations, multimodal queries and coding. We started limited testing this week and will be rolling it out more broadly early next year. And we’ll continue to bring AI Overviews to more countries and languages over the next year.

2.0’s advances are underpinned by decade-long investments in our differentiated full-stack approach to AI innovation. It’s built on custom hardware like Trillium, our sixth-generation TPUs. TPUs powered 100% of Gemini 2.0 training and inference, and today Trillium is generally available to customers so they can build with it too.

If Gemini 1.0 was about organizing and understanding information, Gemini 2.0 is about making it much more useful. I can’t wait to see what this next era brings.

-Sundar

Introducing Gemini 2.0: our new AI model for the agentic era

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

Over the past year, we have continued to make incredible progress in artificial intelligence. Today, we are releasing the first model in the Gemini 2.0 family of models: an experimental version of Gemini 2.0 Flash. It’s our workhorse model with low latency and enhanced performance at the cutting edge of our technology, at scale.

We are also sharing the frontiers of our agentic research by showcasing prototypes enabled by Gemini 2.0’s native multimodal capabilities.

Gemini 2.0 Flash

Gemini 2.0 Flash builds on the success of 1.5 Flash, our most popular model yet for developers, with enhanced performance at similarly fast response times. Notably, 2.0 Flash even outperforms 1.5 Pro on key benchmarks, at twice the speed. 2.0 Flash also comes with new capabilities. In addition to supporting multimodal inputs like images, video and audio, 2.0 Flash now supports multimodal output like natively generated images mixed with text and steerable text-to-speech (TTS) multilingual audio. It can also natively call tools like Google Search, code execution as well as third-party user-defined functions.

Our goal is to get our models into people’s hands safely and quickly. Over the past month, we’ve been sharing early, experimental versions of Gemini 2.0, getting great feedback from developers.

Gemini 2.0 Flash is available now as an experimental model to developers via the Gemini API in Google AI Studio and Vertex AI with multimodal input and text output available to all developers, and text-to-speech and native image generation available to early-access partners. General availability will follow in January, along with more model sizes.

To help developers build dynamic and interactive applications, we’re also releasing a new Multimodal Live API that has real-time audio, video-streaming input and the ability to use multiple, combined tools. More information about 2.0 Flash and the Multimodal Live API can be found in our developer blog.

Gemini 2.0 available in Gemini app, our AI assistant

Also starting today, Gemini users globally can access a chat optimized version of 2.0 Flash experimental by selecting it in the model drop-down on desktop and mobile web and it will be available in the Gemini mobile app soon. With this new model, users can experience an even more helpful Gemini assistant.

Early next year, we’ll expand Gemini 2.0 to more Google products.

Unlocking agentic experiences with Gemini 2.0

Gemini 2.0 Flash’s native user interface action-capabilities, along with other improvements like multimodal reasoning, long context understanding, complex instruction following and planning, compositional function-calling, native tool use and improved latency, all work in concert to enable a new class of agentic experiences.

The practical application of AI agents is a research area full of exciting possibilities. We’re exploring this new frontier with a series of prototypes that can help people accomplish tasks and get things done. These include an update to Project Astra, our research prototype exploring future capabilities of a universal AI assistant; the new Project Mariner, which explores the future of human-agent interaction, starting with your browser; and Jules, an AI-powered code agent that can help developers.

We’re still in the early stages of development, but we’re excited to see how trusted testers use these new capabilities and what lessons we can learn, so we can make them more widely available in products in the future.

Project Astra: agents using multimodal understanding in the real world

Since we introduced Project Astra at I/O, we’ve been learning from trusted testers using it on Android phones. Their valuable feedback has helped us better understand how a universal AI assistant could work in practice, including implications for safety and ethics. Improvements in the latest version built with Gemini 2.0 include:

**Better dialogue:**Project Astra now has the ability to converse in multiple languages and in mixed languages, with a better understanding of accents and uncommon words.**New tool use:**With Gemini 2.0, Project Astra can use Google Search, Lens and Maps, making it more useful as an assistant in your everyday life.**Better memory:**We’ve improved Project Astra’s ability to remember things while keeping you in control. It now has up to 10 minutes of in-session memory and can remember more conversations you had with it in the past, so it is better personalized to you.**Improved latency:**With new strea