Nowadays, the higher peak capacity achievable by comprehensive two-dimensional liquid chromatography (LC×LC) for the analysis of vegetal samples is well-recognized. In addition, numerous compounds may be present in very different amounts. Cannabinoids and terpenes represent the main components of Cannabis sativa inflorescence samples, whose quantities are relevant for many application purposes. The analyses of both families are performed by different methods, at least two different separation methodologies, mainly according to their chemical characteristics and concentration levels. In this work, concentration differences and sample complexity issues were addressed using an LC×LC method that incorporates an optimized modulation strategy, namely smart active modulation, for the simultaneous analysis of cannabinoids and terpenes. The system was built by interposing an active flow splitter pump between both dimensions. This set up aimed to exploit the known advantages of LC×LC. In addition, here we proposed to use the splitter pump for online control over the splitting ratio to facilitate the selective dilution of different eluted fractions containing compounds with highly different concentrations.This work represents the first application and demonstration of smart active modulation (SAM) in LC×LC to simultaneously determine analytes with significant differences in concentration levels present in complex samples. The proposed method was tested with eight different strains, from which fingerprints were taken, and numerous cannabinoids and terpenes were identified in these samples. With this strategy, between 49 and 54 peaks were obtained in the LC×LC chromatograms corresponding to different strains. THCA-A was the main component in six strains, while CBDA was the main component in the other two strains. The main terpenes found were myrcene (in five strains), limonene (in two strains), and humulene (in one strain). Additionally, numerous other cannabinoids and terpenes were identified in these samples, providing valuable compositional information for growers, as well as medical and recreational users. The SAM strategy here proposed is simple and it can be extended to other complex matrices.