  Molecular clouds (MC) are structures of dense gas in the interstellar medium
(ISM), that extend from ten to a few hundred parsecs and form the main gas
reservoir available for star formation. Hydrodynamical simulations of varying
complexity are a promising way to investigate MC evolution and their
properties. However, each simulation typically has a limited range in
resolution and different cloud extraction algorithms are used, which
complicates the comparison between simulations. In this work, we aim to extract
clouds from different simulations covering a wide range of spatial scales. We
compare their properties, such as size, shape, mass, internal velocity
dispersion and virial state. We apply the Hop cloud detection algorithm on
(M)HD numerical simulations of stratified ISM boxes and isolated galactic disk
simulations that were produced using Flash Ramses and Arepo We find that the
extracted clouds are complex in shape ranging from round objects to complex
filamentary networks in all setups. Despite the wide range of scales,
resolution, and sub-grid physics, we observe surprisingly robust trends in the
investigated metrics. The mass spectrum matches in the overlap between
simulations without rescaling and with a high-mass slope of $\mathrm{d}
N/\mathrm{d}\ln M\propto-1$ in accordance with theoretical predictions. The
internal velocity dispersion scales with the size of the cloud as
$\sigma\propto R^{0.75}$ for large clouds ($R\gtrsim3\,\mathrm{pc}$). For small
clouds we find larger sigma compared to the power-law scaling, as seen in
observations, which is due to supernova-driven turbulence. Almost all clouds
are gravitationally unbound with the virial parameter scaling as
$\alpha_\mathrm{vir}\propto M^{-0.4}$, which is slightly flatter compared to
observed scaling, but in agreement given the large scatter.
