QML Benchmarks is a research-driven repository implementing and benchmarking fundamental quantum algorithms and quantum machine learning models including QCNN, QFT, Grover, Shor, HHL, VQE, and QAOA. The project analyzes algorithm scalability, optimization behavior, and robustness under realistic NISQ noise simulations through structured experiments