Precipitation plays a key role in shaping land surface processes in Himalaya. It is also the most challenging meteorological variable to model in climate change studies due to inadequate ground data. Gridded Precipitation Products (GPPs) are useful alternatives to ground data but require validation, especially in topographically complex and wet Eastern Himalaya. This study presents a fine-scaled ground validation of eleven GPPs, including five satellite-based (GPM-IMERGV06, TRMM-3B42V7, TRMM-3B42V7RT, CHIRPS-2.0 and PERSIANN-CCS), four reanalysis model-based (ERA5, ERA5-Land, AgERA5, and WRF) and two gauge-interpolated (IMD-0.25° and APHRODITE-2V18) GPPs in Eastern Himalaya. Hourly precipitation data from 27 rain gauges (Gauges) from Sikkim, representing the Eastern Himalayan climatology, is used to statistically validate the GPPs and assess their ability to capture diurnal and seasonal patterns, and extreme events.Overall, GPM-IMERG, WRF, and IMD-0.25° outperformed the other satellite, model, and interpolated GPPs, respectively, in comparison to Gauges. Near real-time TRMM-3B42RTV7 performed better than TRMM-3B42V7 for high-intensity precipitation and large storms, but not in overall performance. CHIRPS-2.0 and PERSIANN-CCS showed the least detectability and highest errors; however, PERSIANN-CCS was better at reproducing known spatial patterns in ground precipitation. The GPPs underestimated (overestimated) precipitation frequencies and volumes below (above) 3000 masl, and high (low) intensities. The highest detectability and lowest errors were observed at mid-elevation (1000-2000 masl), and in monsoon (JJASO) and summer (MAM), whereas winter (NDJF) precipitation was overestimated with high false hits. Strong diurnal cycles in precipitation were observed in Gauges with peaks around late-night-early morning (2300–0300 h) in monsoon and afternoon-evening (1600–1900 h) in summer. Satellite GPPs captured the diurnal cycle in Gauges, albeit with subdued amplitudes, whereas model GPPs failed. Owing to their superior performance and fine spatiotemporal resolutions, GPM-IMERG and WRF are recommended for hydrological studies in Eastern Himalaya. The three ERA5-based products (ERA5, ERA5-Land, AGERA5), along with TRMM-3B42RTV7 and IMD-0.25°, showed the lowest bias in tracking large storms (longer than 5 days) and are advocated for understanding extreme events and in geohazard applications. IMD-0.25° is recommended for precipitation trend and variability analysis, albeit with suitable bias-correction to address the negative biase at high elevations and the positive bias in trans-Himalayan regions. The study improves our understanding of remotely-sensed and spatially-gridded precipitation in the world's highest mountain range, where ground observations are likely to be inadequate for years to come.