Gemini: We are the largest and most powerful AI model in terms of scale and capability.

Every technological revolution is an opportunity to advance scientific discovery, accelerate human progress, and improve people's lives. I believe the AI transformation we are currently witnessing will be the most profound change we experience in our lifetime, surpassing the transformations brought about by mobile technology or the internet. AI has the potential to create opportunities for people around the world, whether in daily life or in the pursuit of extraordinary achievements. It will usher in a new era of innovation and economic progress, driving the development of knowledge, learning, creativity, and productivity on an unprecedented scale.

The Next Generation Capabilities

Gemini is designed to be inherently multimodal, undergoing pretraining across different modalities from the outset. Subsequently, we fine-tune it using additional multimodal data to further enhance its effectiveness. This enables Gemini to smoothly comprehend and reason about various types of input from the initial stages, far surpassing existing multimodal models in virtually every domain.

  • Complex Reasoning

    Gemini 1.0 possesses sophisticated multimodal reasoning capabilities that aid in understanding complex written and visual information. This unique skill set empowers it to uncover discerning knowledge content within vast datasets.

  • Understanding Text, Images, Audio, and More

    Trained Gemini 1.0 can simultaneously recognize and comprehend text, images, audio, and more. Consequently, it excels in understanding nuanced information and answering questions related to intricate subjects. This makes it particularly adept at reasoning in complex subjects like mathematics and physics.

  • Advanced Coding Abilities

    Our first-generation Gemini can understand, interpret, and generate high-quality code in the world's most popular programming languages, such as Python, Java, C++, and Go. Its cross-language functionality and ability to reason about complex information make it one of the world's leading foundational models for coding.

Gemini reviews on the Internet

Information sourced from Twitter

  • Sundar PichaiTwitter users

    Introducing Gemini 1.0, our most capable and general AI model yet. Built natively to be multimodal, it’s the first step in our Gemini-era of models. Gemini is optimized in three sizes - Ultra, Pro, and Nano

  • 葉隠れTwitter users

    Gemini Ultra, the behemoth of large language models (LLMs) from Google AI, has shattered the existing performance paradigm across a diverse spectrum of cognitive tasks.

  • GoogleTwitter users

    We believe in making AI helpful for everyone. That’s why we’re launching Gemini, our most capable model that’s inspired by the way people understand and interact with the world.

Gemini's performance has shown significant improvement.

Gemini Ultra achieved a scoring rate of up to 90.0% on the MMLU (Massive Multitask Language Understanding dataset), surpassing human experts for the first time. Click on "Gemini Test Report" to learn more

Gemini tested at MMLU

Frequently Asked Questions

Answered all frequently asked questions. Can’t find the answer you’re looking for? feel free to contact us.

What is the motivation behind the development of Gemini 1.0, and how does it fit into Google's broader vision for AI?

This question seeks to understand the driving force behind Gemini 1.0 and its alignment with Google's overarching goals in the field of artificial intelligence.

How does Gemini 1.0 differ from traditional multimodal models, and what advantages does its native multimodal design offer in terms of performance and complexity of reasoning tasks?

This question aims to explore the unique features of Gemini 1.0, particularly its native multimodal design, and how this design contributes to enhanced performance and complex reasoning capabilities.

Can you elaborate on Gemini Ultra's performance, specifically in comparison to human experts, and how does it excel in the MMLU test covering various subjects?

This question delves into the specific performance metrics of Gemini Ultra, especially in comparison to human experts, and its success in the MMLU test covering a wide array of subjects.

In what ways does Gemini 1.0 showcase advanced capabilities in handling diverse information types such as text, code, audio, images, and videos?

This question seeks to understand how Gemini 1.0 demonstrates its proficiency in handling various types of information and its implications for diverse tasks involving text, code, audio, images, and videos.

How does Gemini 1.0 contribute to the field of coding, and what improvements does Gemini Ultra bring to the AlphaCode system in terms of solving competitive programming problems?

This question explores Gemini 1.0's impact on coding tasks, specifically its role in the AlphaCode system, and the advancements Gemini Ultra introduces for solving competitive programming problems.

What measures has Google taken to ensure the responsibility, safety, and security of Gemini 1.0, and how is Google addressing potential risks associated with its multimodal capabilities?

This question focuses on Google's commitment to responsible AI, safety, and security in the development and deployment of Gemini 1.0, including the steps taken to mitigate risks associated with its multimodal capabilities.