Google's PaLM 2 is the successor to the original PaLM and represents the next generation of large language models. The model appears to excel in advanced reasoning tasks, such as code and math, classification and question answering, multilingual translation, and natural language generation. PaLM 2's capabilities extend beyond those exhibited by previous state-of-the-art language models, achieved through compute-optimal scaling, an upgraded dataset mixture, and model architecture enhancements. PaLM 2's development adheres to Google's responsible AI practices, subjected to rigorous assessment to limit potential harms, biases, and to determine its applications in products and research. Furthermore, PaLM 2 is pre-trained on a wide array of texts, making it proficient at tasks like coding and multilingual translation. Coding capabilities range from popular programming languages, such as Python and JavaScript, to more specialized code, such as Prolog, Fortran, and Verilog. The improvements from PaLM to PaLM 2 come as a result of the use of compute-optimal scaling, enhanced dataset mixture, and an improved model architecture. The architecture enhancements of PaLM 2 include training on a diverse set of tasks to learn various aspects of language. The model's evaluation has revealed higher performance levels in reasoning benchmark tasks and superior multilingual results compared to previous models.