One of the most pliable and robust extensions of the classical FGM family of bivariate distributions is the Sarmanov family, which was proposed and used by Sarmanov (1974) as a new model of hydrological processes, inter alia. Despite the salient and almost unique features of this family, it is never used in the literature. The distribution theory of concomitants of record values from this family is investigated. Furthermore, the joint distribution of concomitants of record values for this family is studied. Besides, some aspects of information measures, namely, the Shannon entropy, inaccuracy measure, extropy, cumulative entropy, and Fisher information number are studied. Illustrative examples are provided, where numerical studies lend further support to the theoretical results.