The Gemini 1.5 family of models, introduced by Google, represents a significant advancement in multimodal understanding and reasoning capabilities. The family includes two new models: Gemini 1.5 Pro, an updated version that outperforms its predecessor on most benchmarks, and Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal quality loss. These models can handle fine-grained information from millions of tokens of context, including long documents, video, and audio. Key highlights include: 1. **Performance Improvements**: Gemini 1.5 Pro and 1.5 Flash achieve near-perfect recall on long-context retrieval tasks across modalities, surpassing previous state-of-the-art models like Gemini 1.0 Ultra. 2. **Long-Context Capabilities**: The models can process extremely long contexts, up to 10 million tokens, with near-perfect recall in text, video, and audio modalities. 3. **Real-World Applications**: Gemini 1.5 models demonstrate real-world use cases, such as collaborating with professionals to save time on tasks and learning to translate new languages from limited resources. 4. **Core Capabilities**: The models excel in core capabilities like math, science, reasoning, multilinguality, video understanding, and code, outperforming previous versions by significant margins. 5. **Efficiency and Latency**: Gemini 1.5 models are designed for high efficiency and low latency, with Gemini 1.5 Flash achieving the fastest output generation among tested models. The report also details the architectural improvements, training infrastructure, and evaluation results, showcasing the models' capabilities in both synthetic and real-world tasks.The Gemini 1.5 family of models, introduced by Google, represents a significant advancement in multimodal understanding and reasoning capabilities. The family includes two new models: Gemini 1.5 Pro, an updated version that outperforms its predecessor on most benchmarks, and Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal quality loss. These models can handle fine-grained information from millions of tokens of context, including long documents, video, and audio. Key highlights include: 1. **Performance Improvements**: Gemini 1.5 Pro and 1.5 Flash achieve near-perfect recall on long-context retrieval tasks across modalities, surpassing previous state-of-the-art models like Gemini 1.0 Ultra. 2. **Long-Context Capabilities**: The models can process extremely long contexts, up to 10 million tokens, with near-perfect recall in text, video, and audio modalities. 3. **Real-World Applications**: Gemini 1.5 models demonstrate real-world use cases, such as collaborating with professionals to save time on tasks and learning to translate new languages from limited resources. 4. **Core Capabilities**: The models excel in core capabilities like math, science, reasoning, multilinguality, video understanding, and code, outperforming previous versions by significant margins. 5. **Efficiency and Latency**: Gemini 1.5 models are designed for high efficiency and low latency, with Gemini 1.5 Flash achieving the fastest output generation among tested models. The report also details the architectural improvements, training infrastructure, and evaluation results, showcasing the models' capabilities in both synthetic and real-world tasks.