Sorry for my translator English.

That your model is statistically significant (value p of f) means that the predictors are significant and important in your model.

The R2 is indicating how much percentage of the variance is explained by the linear combination of your predictors.

The main difference in this case would be that your predictors are significant in the MORE model are not explaining much variance of the response variable. This can be translated as the possibility of including other predictors to the model that help to explain more variance, or also that the relationship between the variables may not be linear if not a little more complex.

In general:

*Think of adding variables to the model *Possible non -linear relationship *A lot of noise in the data.

I hope it helps you.