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This paper introduces BAGEN, a framework for evaluating budget awareness in LLM agents, defining budget estimation as internal and external budgets and formalizing progressive interval estimation. Experiments show that strong agents lack budget awareness, are over-optimistic, and that early stopping can save tokens while training improves alerting behavior.