Numerical models serve as critical reference bases for weather forecasting. Effective application of numerical models for forecasting first requires understanding the models’ forecasting performance, which is derived from verification. This study researches the forecasting capabilities of different numerical models in terms of precipitation associated with the Northeast Cold Vortex in Jilin Province. Utilising hourly precipitation observation data from 1436 stations in Jilin Province during the Northeast Cold Vortex period from May to September 2021-2023, a comparison analysis is conducted between the precipitation forecasting products of six numerical models, namely, EC, CMA-MESO, CMA-GFS, CMA-TYM, CMA-SH9, and CMA-BJ. The aim is to reveal the characteristic differences in forecasting capability and deviation contributions between three-hour-interval precipitation forecasts in plain and hilly areas using quantitative assessment, graded assessment, and diurnal variation forecast comparison. The results indicate that: (1) The observed precipitation associated with the Northeast Cold Vortex and the precipitation forecasting capability of numerical models are closely related to topographic distribution. In the plain group, both the precipitation amount and the number of observation stations are smaller, while the precipitation intensity is stronger, and the mean relative error (MRE) and mean absolute error (MAE) of the stations are larger. In contrast, the hill group shows opposite trends: larger precipitation amount, more station numbers, weaker intensity, and smaller MRE and MAE. (2) EC demonstrates the best performance in forecasting diurnal variations of precipitation in both plain and hilly groups; however, it lacks the ability to predict the peak of precipitation intensities, with a notable overestimation of precipitation frequency occurring around midday. In contrast, CMA-MESO and CMA-SH9 are more effective in capturing the diurnal peak or trend characteristics of precipitation frequency and intensities. (3) The weak precipitation forecasts under various models are overly frequent, while the forecasting capabilities for moderate and heavy precipitation are influenced by topographical differences, where the performance in hilly areas surpasses that in plain areas. Additionally, CMA-MESO and CMA-TYM outperform global models, with global models exhibiting significant dry deviations. (4) The forecasting skill clock plots indicate that the excessive forecast of frequency by EC around midday is mainly due to overforecasting weak precipitation, while the significant underforecast of strong precipitation throughout the day results from missed occurrences. Furthermore, CMA-MESO exhibits stronger forecasting capabilities for heavy precipitation compared to EC, successfully predicting evening peak values and the occurrence of heavy precipitation stations. Its errors arise from location deviation in the forecasts.