The NMO Benchmark introduces a new framework to extend generative molecular design beyond drug discovery by integrating machine learning with quantum materials research, enabling optimization for scientifically grounded targets outside traditional pharmaceutical domains. This benchmark addresses limitations of existing proxies by focusing on structural diversity and real-world application in nanotechnology. The approach leverages pretrained models while emphasizing transferability to structurally distinct areas. The work aims to drive discovery in quantum materials through targeted molecular optimization.