The way a decoder constructs translation hypotheses is directly related to the weights for different model features in a SMT system, which are usually optimized for a given set of models with minimum error rate training (MERT) (Och, 2003) to achieve better translation performance.
the weights obtained for a model do not necessarily apply to another model.