Gemini Report
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Credibility Rating
Good quality. Reputable source with community review or editorial standards, but less rigorous than peer-reviewed venues.
Rating inherited from publication venue: arXiv
Technical report introducing Gemini, a multimodal AI model family with capabilities across text, image, audio, and video. Relevant to AI safety research for understanding state-of-the-art model capabilities, potential risks, and evaluation methodologies for advanced AI systems.
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Abstract
This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.
Summary
Google introduces Gemini, a new family of multimodal models capable of understanding images, audio, video, and text. The family includes three sizes—Ultra, Pro, and Nano—designed for different computational requirements and use cases. Gemini Ultra achieves state-of-the-art performance on 30 of 32 benchmarks tested, including becoming the first model to match human-expert performance on MMLU and improving results across all 20 multimodal benchmarks evaluated. The report emphasizes responsible deployment through various services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| Google DeepMind | Organization | 37.0 |
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Conversion to HTML had a Fatal error and exited abruptly. This document may be truncated or damaged. [◄](https://ar5iv.labs.arxiv.org/html/2312.11804) [](https://ar5iv.labs.arxiv.org/) [Feeling\\ \\ lucky?](https://ar5iv.labs.arxiv.org/feeling_lucky) [Conversion\\ \\ report](https://ar5iv.labs.arxiv.org/log/2312.11805) [Report\\ \\ an issue](https://github.com/dginev/ar5iv/issues/new?template=improve-article--arxiv-id-.md&title=Improve+article+2312.11805) [View original\\ \\ on arXiv](https://arxiv.org/abs/2312.11805) [►](https://ar5iv.labs.arxiv.org/html/2312.11807)
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