Policy-relevant results of Integrated Assessment Models (IAMs) are sensitive to a number of uncertain assumptions that govern model simulation of the climate, society, and the policy response to climate change. Uncertainties remain in understanding of the rate and magnitude of climate change, the nature and severity of climate impacts, and the ability to cope with those impacts. Methods for quantifying and comparing climate damages across different regions and different time periods are fiercely debated. This paper examines assumptions that are central to model estimates of the benefits of climate policy in three well-known IAMs, and discusses their consistency with current natural and social scientific research. Different IAMs take different approaches to dealing with these uncertainties, and understanding their assumptions is critical to interpreting their results, since those results can change dramatically when assumptions are varied.