Gemini: A Family of Highly Capable Multimodal Models

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. 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.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 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.
• 2 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.
• 3 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.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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