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This study evaluated the performance of 23 models participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating snowfall variation across the Eurasian continent. The results show that the CMIP6 multi‐model ensemble (MME) can reasonably capture the climate means of snowfall indices for 1995–2014 period and has high pattern correlations with observations. However, most of CMIP6 models generally overestimate snowfall amounts, snowfall days and snowfall duration, and the overestimation is much clearer in spring. The performance of these models in simulating snowfall events with different grades (including light snowfall, moderate snowfall, heavy snowfall and snowstorm) becomes gradually poorer with higher snowfall levels. On the whole, the comprehensive model ranks implied that NorESM2‐MM, NorESM2‐LM and CESM2‐WACCM models showed the best performances. In addition, the CMIP6 MME outperforms individual models in terms of both spatial–temporal features and interannual variability; thus, the MME is used to project the snowfall change in the 21st century. Further evaluations show that by the end of this century, snowfall will decrease in most of Eurasia with an average value of 16.7% (31.3%) under the SSP2‐4.5 (SSP5‐8.5) scenarios, and snowfall days will decrease by 12.6 days (25.0 days); the snowfall duration will shorten further due to the first date of snowfall occurrence will postpone by 12.7 days (23.0 days) and the last date further advance by 15.0 days (26.7 days). Additionally, heavy snowfall, snowstorms and their number of days will increase over part of Northern Asia, the Tibetan Plateau and Central Asia, where the risk of snowfall extremes will increase. However, large inter‐model and scenario uncertainties also exist in the CMIP6 model projection of snowfall events, which requires further improvement. [ABSTRACT FROM AUTHOR]