Gemini: A Family of Highly Capable Multimodal Models

The Gemini technical report (December 2023) is the first product of the Google DeepMind merger — a multimodal foundation model family (Ultra, Pro, Nano) designed to understand and reason across text, images, audio, video, and code natively. Hassabis describes Gemini as a departure from treating language as the primary modality: the world doesn't come in text form, and an AI that can only process text will always be limited in how it can understand physical reality. The Ultra model achieves human-expert performance on the MMLU benchmark across 57 academic subjects — the first model to do so — and significantly outperforms GPT-4 on most multimodal benchmarks at the time of publication. The report also describes Gemini's 'long context' window (up to 1 million tokens in later versions), which Hassabis positions as the mechanism for keeping entire codebases, scientific papers, or video sequences in working memory. For the scientific discovery mission: Gemini serves as the reasoning layer that AlphaFold-style specialized models can call when they need general-purpose language understanding or multi-step inference.