Recent quantum runtime (dis)advantages

A robust definition of quantum runtime is essential for assessing the performance of quantum algorithms and claims of quantum advantage. While for most classical hardware the total runtime is well approximated by computation plus a weakly varying constant, on current quantum hardware a clean experimental separation between "pure computation" and "overhead" is often not justified. Consequently, conventional quantum runtime analyses excluding substantial system-level overheads can lead to biased performance assessments. In this work we introduce experimentally grounded, end-to-end definitions of quantum runtime for digital and analogue quantum computers, together with a methodology for selecting strong classical baselines for quantum-classical runtime comparisons. Within this framework, we evaluate recent claims of quantum advantage in annealing and gate-based algorithms. We examine three representative case studies. First, we revisit annealing for approximate QUBO problems PRL 134, 160601 (2025), which employs a well-motivated time-to-$ε$ metric but effectively uses annealing time as a proxy for runtime. Second, we analyze a restricted implementation of Simon's problem PRX 15, 021082 (2025), where the favorable scaling in oracle calls is undisputed; however, we show that the estimated runtime of the quantum experiment is approximately two orders of magnitude slower than a tuned classical baseline at the tested sizes. Finally, we find that the runtime advantage of the BF-DCQO hybrid algorithm arXiv:2505.08663 is not observed under more comprehensive benchmarking. Therefore, on current NISQ hardware, runtime-based quantum advantage has not yet been demonstrated under experimentally grounded performance metrics, and credible claims require careful time accounting, appropriate performance measures, and properly chosen classical reference implementations, as discussed in this work.