  Dust modeling is crucial to infer dust properties and budget for galaxy
studies. However, there are systematic disparities between dust grain models
that result in corresponding systematic differences in the inferred dust
properties of galaxies. Quantifying these systematics requires a consistent
fitting analysis. We compare the output dust parameters and assess the
differences between two dust grain models, Compiegne et al (2011), and THEMIS
(Jones et al 2013, Kohler et al 2015). In this study, we use a single fitting
method applied to all the models to extract a coherent and unique statistical
analysis. We fit the models to the dust emission seen by Spitzer and Herschel
in the Small and Large Magellanic Clouds (SMC and LMC). The observations cover
the infrared (IR) spectrum from a few microns to the sub-millimeter range. For
each fitted pixel, we calculate the full n-D likelihood, based on the method
described in Gordon et al (2014). The free parameters are both environmental
($U$, the interstellar radiation field strength; $\alpha_\mathrm{ISRF}$,
power-law coefficient for a multi-U environment; $\Omega^*$, the starlight
strength) and intrinsic to the model ($Y_\mathrm{i}$: abundances of the grain
species $i$; $\alpha_\mathrm{sCM20}$, coefficient in the small carbon grain
size distribution). Fractional residuals of 5 different sets of parameters show
that fitting THEMIS brings a more accurate reproduction of the observations
than the Compiegne model. However, independent variations of the dust species
show strong model-dependencies. We find that the abundance of silicates can
only be constrained to an upper-limit and the silicate/carbon ratio is
different than that seen in our Galaxy. In the LMC, our fits result in dust
masses slightly lower than those found in literature , by a factor lower than
2. In the SMC, we find dust masses in agreement with previous studies.
