Abstract The sensitivity of glacier mass balance (MB) in response to climatic perturbations has made it an important parameter of study from hydrological, climatological and glaciological point of view. To monitor the health of any glacier system, long-term MB observations are required. These observations among Himalayan glaciers are not available consistently and large glaciers are not often monitored for mass balance due to logistical challenges. One such glacier is the Gangotri, situated in the western Himalaya. In the present study an attempt is made to model the MB over the Gangotri glacier, the biggest glacier in the Ganga basin and also the point of origin of the River Ganges. The mass balance of the Gangotri glacier is estimated during the time period 1985–2014 using two different methods: ice-flow velocity; and energy balance modelling using regional model (REMO) outputs and in situ automatic weather station (AWS) data. The geodetic method is used for the nearby Dokriani glacier, where field-based MB measurements are available. MB of Gangotri glacier estimated for 2001–14 using the ice-flow velocity method is −0.92 ± 0.36 m w.e. a −1 ; for 2006–07, MB using AWS and Tropical Rainfall Monitoring Mission (TRMM) data with the energy balance modelling approach is −0.82 m w.e. a −1 ; and for 1985–2005, MB using REMO data with the energy balance modelling approach is −0.98 ± 0.23 m w.e. a −1 . Using the surface velocity method, it is estimated that the glacier lost 9% of its volume during the period 2001–14. The glacier vacated an area of 0.152 km 2 from the snout region, and retreated by 200 m in the last 14 years. MB values estimated for the Gangotri glacier from different methodologies are remarkably close, suggesting them to be suitable methods of MB estimation. TRMM, High Asia Refined (HAR-10) and Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APHRODITE) data are used to estimate the precipitation over the glacier. The study suggests that the glacier-wide estimation of weather parameters needs to be improved for more accurate estimation of glacier mass balance.