Audience
Users interested in a powerful AI language model
About Gemini Ultra
Gemini Ultra is a powerful new language model from Google DeepMind. It is the largest and most capable model in the Gemini family, which also includes Gemini Pro and Gemini Nano. Gemini Ultra is designed for highly complex tasks, such as natural language processing, machine translation, and code generation. It is also the first language model to outperform human experts on the Massive Multitask Language Understanding (MMLU) test, obtaining a score of 90%.
Popular Alternatives
Gemma
Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. Developed by Google DeepMind and other teams across Google, Gemma is inspired by Gemini, and the name reflects the Latin gemma, meaning “precious stone.” Accompanying our model weights, we’re also releasing tools to support developer innovation, foster collaboration, and guide the responsible use of Gemma models. Gemma models share technical and infrastructure components with Gemini, our largest and most capable AI model widely available today. This enables Gemma 2B and 7B to achieve best-in-class performance for their sizes compared to other open models. And Gemma models are capable of running directly on a developer laptop or desktop computer. Notably, Gemma surpasses significantly larger models on key benchmarks while adhering to our rigorous standards for safe and responsible outputs.
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Gemini
Gemini was created from the ground up to be multimodal, highly efficient at tool and API integrations and built to enable future innovations, like memory and planning. While still early, we’re already seeing impressive multimodal capabilities not seen in prior models.
Gemini is also our most flexible model yet — able to efficiently run on everything from data centers to mobile devices. Its state-of-the-art capabilities will significantly enhance the way developers and enterprise customers build and scale with AI.
We’ve optimized Gemini 1.0, our first version, for three different sizes:
Gemini Ultra — our largest and most capable model for highly complex tasks.
Gemini Pro — our best model for scaling across a wide range of tasks.
Gemini Nano — our most efficient model for on-device tasks.
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Gopher
Language, and its role in demonstrating and facilitating comprehension - or intelligence - is a fundamental part of being human. It gives people the ability to communicate thoughts and concepts, express ideas, create memories, and build mutual understanding. These are foundational parts of social intelligence. It’s why our teams at DeepMind study aspects of language processing and communication, both in artificial agents and in humans. As part of a broader portfolio of AI research, we believe the development and study of more powerful language models – systems that predict and generate text – have tremendous potential for building advanced AI systems that can be used safely and efficiently to summarise information, provide expert advice and follow instructions via natural language. Developing beneficial language models requires research into their potential impacts, including the risks they pose.
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ESMFold
ESMFold shows how AI can give us new tools to understand the natural world, much like the microscope, which enabled us to see into the world at an infinitesimal scale and opened up a whole new understanding of life. AI can help us understand the immense scope of natural diversity, and see biology in a new way. Much of AI research has focused on helping computers understand the world in a way similar to how humans do. The language of proteins is one that is beyond human comprehension and has eluded even the most powerful computational tools. AI has the potential to open up this language to our understanding. Studying AI in new domains such as biology can also give insight into artificial intelligence more broadly. Our work reveals connections across domains: large language models that are behind advances in machine translation, natural language understanding, speech recognition, and image generation are also able to learn deep information about biology.
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Integrations
Company Information
Google
Founded: 1998
United States
gemini.google.com
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Product Details
Platforms Supported
SaaS
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