Long-term and large-scale remotely sensed and reanalysis soil moisture products of the Tibetan Plateau are very important for understanding the land–atmosphere interactions in this area and their impacts on the weather and climate in the Asian continent. However, it is of great importance to assess the reliability of these products before using them. In the study, in-situ soil moisture measurements from three networks which represent different climatic and vegetation conditions over the Tibetan Plateau are used to evaluate the skill of seven remotely sensed soil moisture products and one reanalysis soil moisture product in the period of 2002–2012. The remotely sensed soil moisture products include three widely used products derived from the Advanced Microwave Scanning Radiometer — Earth Observing System (AMSR-E): the National Aeronautics and Space Administration (NASA) soil moisture product, the Land Parameter Retrieval Model (LPRM) soil moisture product, and the Japan Aerospace Exploration Agency (JAXA) soil moisture product; the remaining products are the JAXA AMSR2 soil moisture product, the Soil Moisture and Ocean Salinity (SMOS) soil moisture product, the Advanced Scatterometer (ASCAT) soil moisture product, and the Essential Climate Variable (ECV) soil moisture product which is a new merged product using both active and passive soil moisture products. The reanalysis product is the latest ERA-Interim product produced by the European Centre for Medium Range Weather Forecasts (ECMWF). The results show that all these products can generally capture the soil moisture dynamics well except for the NASA product which significantly underestimates the soil moisture and also lacks temporal dynamics. The JAXA AMSR-E and AMSR2 products underestimate the ground measurements at most of the time, whereas the LPRM product gives much larger seasonal amplitude than the in-situ observations with a large positive bias. It seems that the SMOS observations are severely affected by the well-known radio-frequency interference (RFI) which leads to a big noise and bias in the SMOS product. The ASCAT product overestimates the ground measurements, but it correlates with in-situ soil moisture very well and is also less influenced by vegetation cover. In general, the ECV and ERA products outperform other products. Though the ECV product underestimates the soil moisture, it shows the best correlation with ground measurements and captures the variation of in-situ soil moisture very well while the ERA product is closest to the absolute values of soil moisture observations. Overall, most of the products give reasonable results in terms of correlation in sparsely vegetated areas. We expect that the validation results can be used as a feedback to the algorithm developers to further enhance the accuracy of soil moisture retrievals over the Tibetan Plateau.