Density is a fundamental property of porous media such as snow. A wide range of snow properties and physical processes are linked to density, but few studies have addressed the uncertainty in snow density measurements. No study has yet quantitatively considered the recent advances in snow measurement methods such as micro-computed tomography (μCT) in alpine snow. During the MicroSnow Davos 2014 workshop, different approaches to measure snow density were applied in a controlled laboratory environment and in the field. Overall, the agreement between μCT and gravimetric methods (density cutters) was 5 to 9%, with a bias of −5 to 2%, expressed as percentage of the mean μCT density. In the field, density cutters overestimate (1 to 6%) densities below and underestimate (1 to 6%) densities above a threshold between 296 to 350kgm−3, dependent on cutter type. Using the mean density per layer of all measurement methods applied in the field (μCT, box, wedge, and cylinder cutters) and ignoring ice layers, the variation between the methods was 2 to 5% with a bias of −1 to 1%. In general, our result suggests that snow densities measured by different methods agree within 9%. However, the density profiles resolved by the measurement methods differed considerably. In particular, the millimeter-scale density variations revealed by the high-resolution μCT contrasted the thick layers with sharp boundaries introduced by the observer. In this respect, the unresolved variation, i.e., the density variation within a layer which is lost by lower resolution sampling or layer aggregation, is critical when snow density measurements are used in numerical simulations.