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Abstract The unprecedented medium-resolution (R_λ∼ 1500–3500) near- and mid-infrared (1–18μm) spectrum provided by JWST for the young (140 ± 20 Myr) low-mass (12–20M_Jup) L–T transition (L7) companion VHS 1256 b gives access to a catalog of molecular absorptions. In this study, we present a comprehensive analysis of this data set utilizing a forward-modeling approach applying our Bayesian framework,ForMoSA. We explore five distinct atmospheric models to assess their performance in estimating key atmospheric parameters:T_eff, log(g), [M/H], C/O,γ,f_sed, andR. Our findings reveal that each parameter’s estimate is significantly influenced by factors such as the wavelength range considered and the model chosen for the fit. This is attributed to systematic errors in the models and their challenges in accurately replicating the complex atmospheric structure of VHS 1256 b, notably the complexity of its clouds and dust distribution. To propagate the impact of these systematic uncertainties on our atmospheric property estimates, we introduce innovative fitting methodologies based on independent fits performed on different spectral windows. We finally derived aT_effconsistent with the spectral type of the target, considering its young age, which is confirmed by our estimate of log(g). Despite the exceptional data quality, attaining robust estimates for chemical abundances [M/H] and C/O, often employed as indicators of formation history, remains challenging. Nevertheless, the pioneering case of JWST’s data for VHS 1256 b has paved the way for future acquisitions of substellar spectra that will be systematically analyzed to directly compare the properties of these objects and correct the systematics in the models.