Computational sprinting activates dark silicon to improve responsiveness by briefly but intensely exceeding a system's sustainable power limit. This article focuses on the energy implications of sprinting. The authors observe that sprinting can save energy even while improving responsiveness by enabling execution in chip configurations that, though thermally unsustainable, improve energy efficiency. Surprisingly, this energy savings can translate to throughput improvements even for long-running computations. Repeatedly alternating between sprint and idle modes while maintaining sustainable average power can outperform steady-state computation at the platform's thermal limit.