Problem specific ~1000 systems (~10 6 In this work, we aim to address the following questions: (1) How generalizable are these problem-specific models? Can pre-trained problem-specific models be used on different datasets or different adsorbates? (2) Can unified models trained on larger datasets accurately predict E ad for smaller datasets? (3) Can unified models obviate the need for generating problem-specific catalyst datasets, allowing these large models to serve as screening tools for DFT calculations? In this work, we attempt to answer these important questions by systematically developing new models or utilizing the existing ones for catalyst application. This work also paves the way for carrying out such generalizability studies for other domain tasks beyond catalysis. The data and tools used in this work will be made publicly available at 1) GitHub (), 2) JARVIS-Leaderboard (.