High RMSE and MAE and low MAPE
The reason is the wider range of your output variable. Consider the following two cases,


Real value was 99, prediction is 101
Real value was 5520, prediction is 5522


In both cases, the absolute error is 2, but relative error in first case is much larger (2% - 2/101) than second case (0.035% 2/5520). Absolute and relative metrics are measuring different aspects of the prediction. So one model is not better than the other in absolute sense (pun intended).

Which metric to value depends on your application. When the outcome range is wide (probably your case) and skewed, relative error measurements are better than absolute error measurements.