Monitoring the mountain vegetation photosynthesis is essential to understanding global climate change. Currently, several long-term satellite-based product suites have generated various variables associated with photosynthesis, while little is known about the consistency and accuracy of multiple variables in the same product suite. Here, the performances of three typical product suites during 2000-2018, namely Moderateresolution Imaging Spectroradiometer (MODIS), Global LAnd Surface Satellite (GLASS), and Global Inventory Modeling and Mapping Studies (GIMMS), were assessed over global mountainous areas. Considering the limited in situ measurements over mountainous areas, high-quality solar-induced chlorophyll fluorescence (SIF) retrievals were adopted innovatively to evaluate multiple variables from different suites, and the consistencies of multiple variables in the same product suite were also assessed by investigating their concurrent extremes. Results illustrated that the combination of multiple variables from GLASS and MODIS tracked the dynamics of mountain vegetation photosynthesis well, with the relative root mean square error (rRMSE) of 41% and 44%, respectively. The concurrent extremes of GLASS matched better with the existing conclusions than those of MODIS, suggesting a better consistency of GLASS over mountainous areas. GLASS and MODIS presented a better ability (1) over flat areas than over mountainous areas (with a lower rRMSE of similar to 5%) and (2) in vegetation types with obvious leaf phenology. Results also showed that GLASS leaf area index (LAI) had a better ability to track the dynamics of photosynthesis than GIMMS LAI. This work can provide essential references in modeling mountain vegetation photosynthesis based on satellite-based product suites.