Abstract The metabolism of the causative agent of TB, Mycobacterium tuberculosis (Mtb) has recently re-emerged as an attractive drug target. A powerful approach to study Mtb metabolism is to use a systems biology framework, such as a Genome-Scale Metabolic Network (GSMN) that allows the dynamic interactions of the many individual components of metabolism to be interrogated together. Several GSMNs networks have been constructed for Mtb and used to study the complex relationship between Mtb genotype and phenotype. However, their utility is hampered by the existence of multiple models of varying properties and performances. Here we systematically evaluate eight recently published metabolic models of Mtb-H37Rv to facilitate model choice. The best performing models, sMtb2018 and iEK1011, were refined and improved for use in future studies by the TB research community.