In the months leading up to the 2024 U.S. presidential election, a team of researchers at MIT CSAIL, MIT Sloan, MIT LIDS, set out to answer a question no one had fully explored: how do large language models (LLMs) respond to questions about the election? Over four months, from July through November, the team ran nearly daily queries across 12 state-of-the-art models on more than 12,000 carefully constructed prompts, generating a dataset with over 16 million responses from LLMs, to help answer this question.