Table 21.

Comparison with foundation time-series models (prediction horizon: 96).

Model	Configuration	Parameters (M)	Pre-training Data	RMSE	MAE	MAPE (%)	R²	Zero-shot Capability
Proposed Framework	Domain-specific	2.3	None required	0.678	0.482	3.56	0.938	N/A (task-specific)
TimesFM	Zero-shot	200	100B time points	0.823	0.594	4.67	0.903	Yes
TimesFM	Fine-tuned	200	100B time points	0.734	0.528	4.02	0.923	Yes
Lag-Llama	Zero-shot	315	27 datasets	0.856	0.621	4.89	0.894	Yes
Lag-Llama	Fine-tuned	315	27 datasets	0.751	0.542	4.18	0.919	Yes
Chronos-T5 (Small)	Zero-shot	20	Public TS corpus	0.812	0.587	4.56	0.906	Yes
Chronos-T5 (Base)	Zero-shot	200	Public TS corpus	0.789	0.569	4.38	0.911	Yes
Chronos-T5 (Large)	Zero-shot	710	Public TS corpus	0.768	0.554	4.24	0.916	Yes
Chronos-T5 (Large)	Fine-tuned	710	Public TS corpus	0.721	0.518	3.89	0.926	Yes
MOIRAI (Small)	Zero-shot	14	LOTSA (27B obs)	0.801	0.578	4.48	0.908	Yes
MOIRAI (Base)	Zero-shot	91	LOTSA (27B obs)	0.776	0.559	4.31	0.914	Yes
MOIRAI (Large)	Zero-shot	311	LOTSA (27B obs)	0.756	0.545	4.19	0.918	Yes
Timer	Zero-shot	67	Unified TS corpus	0.794	0.573	4.42	0.910	Yes
Timer	Fine-tuned	67	Unified TS corpus	0.728	0.523	3.95	0.924	Yes