A variational quantum circuit (VQC) requires multiple measurements on real hardware to estimate expectation values, with each measurement corresponding to one circuit execution; therefore, the advantage in parameter efficiency mainly manifests as fewer trainable degrees of freedom and lower overfitting risk, while the advantages in end-to-end latency and energy consumption need to be evaluated in conjunction with specific hardware and batching strategies.