In recent years, decarbonization is a term that has become a part of our collective vocabulary. As cities begin to put forth legislation mandating decarbonization through a reduction in greenhouse gas emissions, there has been a renewed conversation on how those reductions are to be achieved. A crucial step towards decarbonization of the built environment is city-wide building energy performance improvements and electrification. Traditionally, these performance targets are established using a multitude of energy models built from scratch representing different building typologies and manually calibrated to building energy data from across the region. This is typically time and labor intensive and often not practical for the scale of the task at hand. This study explores an alternate more efficient approach that reimagines the large-scale modeling effort that is commonly undertaken. The primary objective is to generate benchmarks that help establish meaningful targets for the urban context. The intent of the approach is not to try to answer a question about urban energy use by building detailed building-level energy models but to make approximations of building-level energy use to arrive at a city or district scale model. This is more mindful of the scale of the question and urgency of the climate crisis, and better suited to frame policy recommendations around.