Neglecting the effect of thermal diffusion (Soret effect), we consider different formulations of multicom-ponent diffusion as proposed by Arias-Zugasti et al. (2016), for mixtures of dilute gases with large num-bers of components. In particular, we detail the practical implementation of Model 1 + M (loc.cit.) using the lowest order approximation. This is a simple and easy to implement approach, where the 1 + M main species can be chosen locally (see the example provided as supplementary material). These new formula-tions of multicomponent diffusion are compared to the formulation of Dixon-Lewis, used for instance in the Chemkin package, and also to the widely used mixture-averaged simplification. Steady flamelets are first considered for very different fuels (hydrogen, methane or dodecane) in order to show some differ-ences and limitations of the different formulations, and in order to compare computational costs when different numbers of species are involved. An unsteady auto-igniting counterflow diffusion flamelet of methane in a coflow of hot products is also considered. In this way, unsteady 1D calculations can be performed, still including all the challenges of multicomponent diffusion transport as would appear for instance in Direct Numerical Simulations (DNS) of turbulent flames. The different comparisons in terms of precision and cost show that Model 1 + M truncated to the lowest order can be more efficient than the mixture-averaged approach, while reproducing the results of Dixon-Lewis multicomponent diffusion. The efficiency of the proposed approach is mainly due to the evaluation of fewer binary diffusion coeffi-cients, therefore reducing significantly the number of time-consuming operations. Finally, we show that the definition of 1 + M main species can also be used to simplify the time-consuming evaluation of the mixture viscosity, leading to an important further reduction of CPU time that makes the lowest order Model 1 + M always more efficient than the mixture-averaged formulation.(C) 2020 The Combustion Institute. Published by Elsevier Inc. All rights reserved.