Use MLflow Models to log the performance metrics of each model as metrics in an MLflow Run, and compare the models based on the logged metrics.

Manually record the performance metrics of each model in a spreadsheet and compare them visually.

Use the MLflow UI to create a custom dashboard to visualize the performance of different models over time.

Use the MLflow Client API to programmatically retrieve the performance metrics of each model and compare them using statistical analysis.