ABSTARCTAlphaFold has revolutionized the decades-old issue of precisely predicting protein structures. However, its high accuracy relies on a computationally intensive step that involves searching vast databases for homologous sequences as the query protein of interest. Additionally, predicting the quaternary structure of protein complexes requires prior knowledge of subunit counts, a prerequisite rarely met. To address these limitations, we introduce FlashFold - a fast, user-friendly tool for protein structure prediction. It accelerates homology searches using a compact built-in database, enabling structure predictions up to 3-fold faster than AlphaFold3, with sacrificing little or no accuracy. Unlike others, FlashFold features adaptable built-in databases that allow users to easily incorporate their own privately sequenced data - an option that can positively influence the prediction accuracy. Moreover, it allows users to estimate stoichiometry of protein complexes directly from sequence information. To support high-throughput workflows and streamline downstream decision-making, it generates interactive and filterable summary reports, enabling users to efficiently visualize protein structures, and interpret large volumes of prediction results. FlashFold runs locally on Linux and Mac, eliminating reliance on third-party servers. FlashFold is available at https://github.com/chayan7/flashfold.