The compartmentalization of chromatin reflects its underlying biological activities. Inferring chromatin sub-compartments using Hi-C data is challenged by data resolution constraints. Consequently, comprehensive characterizations of sub-compartments have been limited to a select number of Hi-C experiments, with systematic comparisons across a wide range of tissues and conditions still lacking. Our original Calder algorithm marked a significant advancement in this field, enabling the identification of multi-scale sub-compartments at various data resolutions and facilitating the inference and comparison of chromatin architecture in over 100 datasets. Building on this foundation, we introduce Calder2, an updated version of Calder that brings notable improvements. These include expanded support for a wider array of genomes and organisms, an optimized bin size selection approach for more accurate chromatin compartment detection, and extended support for input and output formats. Calder2 thus stands as a refined analysis tool, significantly advancing genome-wide studies of 3D chromatin architecture and its functional implications.