As a relatively new computational fluid simulation method, the Lattice Boltzmann method (LBM) has recently garnered widespread attention in various engineering fields. The LBM-based large-eddy simulation (LBM-LES) model is commonly used to predict flows with high Reynolds numbers, and is considered to yield a prediction accuracy comparable to that of the traditional finite volume method (FVM-LES). Nonetheless, in the indoor environment, a detailed benchmark for the LBM-LES accuracy is currently underdeveloped, and its computational time has not been sufficiently compared with that of FVM-LES. In this study, simulations of an indoor isothermal-forced convection benchmark case were carried out in the forms of LBM-LES and FVM-LES, using different grid resolutions, relaxation time schemes, and discrete velocity schemes of the LBM, with the aim of verifying the prediction accuracy of LBM-LES and investigating its consistency with FVM-LES in indoor turbulent flow. Their computational speeds and parallel computational efficiencies were also compared. The results demonstrate that LBM-LES can achieve the same level of indoor-turbulent-flow prediction accuracy as FVM-LES; however, it requires a more refined grid system (in this study, its grid width was half of that of FVM-LES). Furthermore, the relaxation time and discrete velocity schemes of LBM barely influenced the accuracy of the indoor flow. For the same level of accuracy, their computational speeds approached the same level, even though the LBM-LES required an eight times larger mesh quantity than the FVM-LES; however, the LBM-LES computational speed can surpass that of the FVM-LES when more cores are utilized because of its outstanding parallel efficiency. (C) 2018 Elsevier Ltd. All rights reserved.