Among the six fundamental parameters in the heat balance model of human thermal comfort, metabolic rate is arguably the most influential, yet remains one of the least precisely assessed in both research and practice. Current methodologies typically rely on population-average, static values from activity diaries (e.g., 1.2 met for sitting office work). This approach overlooks the inherent inter-individual differences and intra-individual temporal fluctuations of human metabolic rates. Such inaccuracies can affect both the prediction of occupant thermal comfort and the estimation of internal heat gains in buildings, an essential factor in sizing systems and forecasting building energy performance. This study investigates these impacts by combining dynamic building energy simulations with metabolic rate data measured via indirect calorimetry during an 8-hour workday. First, we quantified the thermal discomfort in a four-person office under a standard control strategy (assuming a constant 1.2 mets rate), revealing significant comfort inequality: the Low met occupant experienced persistent cool sensation in 7 months a year, while the High met occupant was consistently warm in summer (monthly average PMV up to +0.86). Even occupants with near-standard metabolisms felt slightly cool in winter and slightly warm in summer due to metabolic fluctuations. Second, we evaluated the energy consumption of an idealized, personalized dynamic control strategy for homogeneous groups (high, mid, and low met). The results revealed a strong energy-metabolism link: ensuring comfort for a Low met group increased annual heating demand by 89.2%, while a High met group reduced it by 53.2% compared to a standard 1.2 met case. We conclude that a one-size-fitsall approach is fundamentally inequitable and that while personalized control can resolve this, it presents a significant energy trade-off directly dependent on the occupants’ metabolic characteristics.