# Granite Timeseries Ensemble

IBM Research released Granite Timeseries Ensemble, a default forecasting recipe that combines four open Granite time-series models with different architectures and returns median and quantile forecasts without retraining or fitting ensemble weights. Previously a user had to judge which single model suited a given series. Across 97 GIFT-Eval configurations the probabilistic ensemble reaches a MASE of 0.683 against 0.685 for the strongest member, PatchTST-FM-r2, a small margin whose main benefit is not having to pick a model in advance.

IBM Research released Granite Timeseries Ensemble, a default forecasting recipe that combines four open Granite time-series models with different architectures and returns median and quantile forecasts without retraining or fitting ensemble weights. Previously a user had to judge which single model suited a given series. Across 97 GIFT-Eval configurations the probabilistic ensemble reaches a MASE of 0.683 against 0.685 for the strongest member, PatchTST-FM-r2, a small margin whose main benefit is not having to pick a model in advance.