TFB provides a fair and comprehensive evaluation platform for time series forecasting methods across multiple datasets and characteristics. The framework includes tools for computing time series properties such as trend, seasonality, stationarity, and shifting, enabling analysis of when different forecasting methods perform best. It has published results comparing multiple algorithms and has expanded to related benchmarks for time series anomaly detection (TAB) and foundation model evaluation (TSFM-Bench).