The SIF-based global GPP represents the global total primary productivity estimated according to the Mechanistic Light Reaction by using the solar-induced chlorophyll fluorescence (SIF) product from TROPOMI. The spatial distribution and temporal variation of GPP are closely related to global climate change, biodiversity and the dynamics of the carbon cycle. GPP provided by this product refers to the instantaneous GPP corresponding to SIF observations at the moment of the satellite's overpass. We modified the mechanistic light reaction (MLR) model proposed by Gu et al. (2019) to adapt it to canopy-scale applications, and then generated this dataset. The parameterization of qL  (the fraction of open photosystem II reaction centers) in the MLR framework is accomplished using a random forest model based on matched SIF-GPP observations across various flux sites. For continuous global mapping, we further composited the original CMLR GPP using an 8-day moving window and applied a 2D Gaussian function in 3 × 3 moving windows to fill in the gaps. Pixels with filled data were marked with flag = 1 in the quality control layer.