A likelihood ratio or Wald X² test formally tests the hypothesis of whether the model fits the data better than no model.
It is common to test whether the model fits the data better than the null model with no parameters.
A X2 test formally tests whether the reduction is statistically significant. The null hypothesis states that all the parameters for the covariates are zero against the alternative that at least one parameter is not equal to zero. When the p-value is small, you can reject the null hypothesis and conclude that at least one parameter is not zero.