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This paper presents a comprehensive benchmark for electrical load forecasting across grid levels, evaluating ten methods and finding that Transformer-based approaches consistently outperform established methods, reducing forecast error by 6.6–10.7%. The standard Transformer achieves superior performance over a novel flexible architecture, and the foundation model Chronos-2 shows competitive zero-shot performance on some datasets.