Snow water equivalent (SWE) is a critical hydrological variable for water resource management in mountainous regions, where seasonal snowpacks function as natural reservoirs regulating streamflow and water supply. While high-resolution, observation-constrained regional or national snow products provide reliable daily SWE estimates at fine spatial resolution (less than 1 km), their limited temporal coverage often restricts their use for long-term hydro-climatological studies. Large-scale land-surface products, in which SWE is derived from land-surface model simulations driven by atmospheric reanalyses or regional dynamical downscaling systems, provide multi-decadal coverage, but their reliability may be affected by biases in meteorological forcing, limited topographic representation, and simplified snow process parameterisation, requiring rigorous regional evaluation. This study evaluates the SWE estimates of three large-scale land-surface products, i.e., the global ERA5-Land, the European CERRA-Land, and the Italian VHR-REA_IT, against the national reference dataset IT-SNOW across Italy. The analysis combines grid-scale bias assessment of mean annual SWE and snow cover duration with temporal correlation analysis of daily SWE series, and is complemented by an evaluation of precipitation and temperature biases in each product, providing insight into how each product represents the atmospheric conditions governing snow accumulation and ablation and thereby supporting the interpretation of the identified SWE discrepancies. The results show clear regional differences in product performance, with no single product performing best across all metrics. ERA5-Land shows the strongest temporal correlation with IT-SNOW, but tends to overestimate mean annual SWE and snow cover duration in the Alps. CERRA-Land shows more moderate biases than ERA5-Land in the Italian Alps, but generally underestimates mean annual SWE across most subregions, where autumn and winter precipitation deficits in the forcing limit snow accumulation. Across the Apennines, both ERA5-Land and CERRA-Land tend to underestimate SWE and snow cover duration, particularly in the northern sectors. VHR-REA_IT shows widespread underestimation and the weakest temporal correspondence with IT-SNOW: this may be due to its fully coupled atmosphere–land architecture with no assimilation of meteorological observations. Overall, the results suggest that forcing biases explain a substantial part of the observed SWE discrepancies, although not all of them. This study provides useful insights for the use of SWE estimates from large-scale land-surface products in long-term hydro-climatological assessments over Italy and helps to understand whether the products can be used to evaluate snow dynamics in mountainous regions lacking high-quality benchmark estimates.