Question: what do aic values mean?
Answer: The Akaike information criterion (AIC) is an estimator of out-of-sample prediction error and thereby relative quality of statistical models for a given set of data. ... AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher the quality of that model.