Uncertainty propagation and quantification, when applied to the field of nuclear fuel cycle scenario studies, usually only considers a set of easily quantifiable input parameters, leaving out the effects of the modelling approaches. In order to extend the validity of these analyses, two different codes, ANICCA and TR_EVOL (developed respectively by SCK-CEN and CIEMAT), have been benchmarked through a study of an advanced and realistic nuclear fuel cycle scenario with the aim of assessing the impact of the use of different tools in the fuel cycle scenario uncertainty quantification. Additionally, a classical uncertainty propagation analysis was done following the total Monte Carlo and sensitivity approaches in order to compare the system uncertainties with the dissimilarities due the simulators. Results shows that the impact of the fuel cycle simulators cannot be neglected for certain observables, and that their effects become relevant as the scenarios extends over time due their cumulative effect. (C) 2019 Elsevier Ltd. All rights reserved.