he accurate description of noble metal hydrides remains a fundamental challenge for electronic structure theory, especially in systems involving heavy elements where relativistic effects and electron correlation are significant. In this study, we present a high-accuracy potential energy surface (PES) for the AgAuH− anion, constructed from 3,595 UCCSD(T)-F12a energy points and fitted using a feedforward neural network with a root mean square error of 0.21 meV. The PES captures the entire configuration space, including linear and bent minima, transition-state-like structures, and dissociation pathways. Quantum vibrational bound states were computed using time-independent quantum dynamics, enabling detailed mode assignments. The high-fidelity PES and vibrational dataset were used to benchmark some widely employed density functional theory (DFT) methods, B3LYP, ωB97XD, XYG3, and XYGJ-OS. Among these, XYGJ-OS provided the best agreement with the reference data in terms of equilibrium geometries and vibrational frequencies. This study provides a robust benchmark for method development and validation in metal-containing systems and highlights the importance of using high-level reference data when modeling complex coinage-metal hydrides.