Interpretation of variants identified during genetic testing is a significant clinical challenge. In this study, we developed a high-throughput CDKN2A functional assay and characterized all possible CDKN2A missense variants. We found that 40% of all missense variants were functionally deleterious. We also used our functional classification to assess the performance of in silico models that predict the effect of variants, including recently reported models based on machine learning. Notably, we found that all in silico models similarly when compared to our functional classifications with accuracies of 54.6 - 70.9%. Furthermore, while we found that functionally deleterious variants were enriched within ankyrin repeats, rarely were all missense variants at a single residue functionally deleterious. Our functional classifications are a resource to aid the interpretation of CDKN2A variants and have important implications for the application of variant interpretation guidelines, particularly the use of in silico models for clinical variant interpretation.