You will find unending debates on the question. There is no good answer on that question. Generally, people tend to prefer BIC rather than AIC. BIC selects more parcimonious models because the penalty for the number of parameters is higher.

If you are more interested in predictions, you might use other performance criterion. Especially root mean square error (RMSE).

I think you will find many interesting debates on this question on stackexchange

You will find unending debates on the question. There is no good answer on that question. Generally, people tend to prefer BIC rather than AIC. BIC selects more parcimonious models because the penalty for the number of parameters is higher.

If you are more interested in predictions, you might use other performance criterion. Especially root mean square error (RMSE).

I think you will find many interesting debates on this question on CrossValidated.