The paper "Better than classical? The subtle art of benchmarking quantum machine learning models" by Joseph Bowles, Shahnawaz Ahmed, and Maria Schuld explores the effectiveness of classical machine learning models compared to quantum models in various classification tasks. The authors develop an open-source package based on the PennyLane software framework to conduct a large-scale study, testing 12 popular quantum machine learning models on 6 binary classification tasks, resulting in 160 individual datasets. Their findings suggest that classical machine learning models outperform quantum classifiers, and removing entanglement from quantum models often results in as good or better performance, indicating that "quantumness" may not be a crucial factor for small learning tasks. The study also highlights the need for more robust and critical benchmarking practices in quantum machine learning, emphasizing the importance of scientific rigor and the potential pitfalls of benchmarking. The authors identify five key questions for future research on quantum model design, based on their findings.The paper "Better than classical? The subtle art of benchmarking quantum machine learning models" by Joseph Bowles, Shahnawaz Ahmed, and Maria Schuld explores the effectiveness of classical machine learning models compared to quantum models in various classification tasks. The authors develop an open-source package based on the PennyLane software framework to conduct a large-scale study, testing 12 popular quantum machine learning models on 6 binary classification tasks, resulting in 160 individual datasets. Their findings suggest that classical machine learning models outperform quantum classifiers, and removing entanglement from quantum models often results in as good or better performance, indicating that "quantumness" may not be a crucial factor for small learning tasks. The study also highlights the need for more robust and critical benchmarking practices in quantum machine learning, emphasizing the importance of scientific rigor and the potential pitfalls of benchmarking. The authors identify five key questions for future research on quantum model design, based on their findings.