EnvGeoBench: A Benchmark and MM Adapter for QM-Region Geometry Generation

In multiscale molecular simulations of complex chemical systems, the geometry of a chemically active quantum-mechanical (QM) region is shaped by its surrounding environment, typically represented using molecular mechanics (MM). Existing geometry-generation methods largely treat the QM system in isolation, without a systematic approach to incorporating information from surrounding MM regions. This motivates a benchmark beyond isolated-molecule geometry generation that evaluates both structural accuracy and the benefit of environmental information. In this work, we introduce EnvGeoBench, a benchmark for environment-conditioned QM geometry generation from QM/MM simulation records. It defines four tasks for generating QM conformations with decreasing amounts of available QM-side information: reaction endpoint conformations and a requested path stage, reaction endpoint conformations alone, a reaction coordinate value alone, or no per-record QM-side input. For each task, we specify model inputs, hold out groups of related simulation records, and evaluate generated geometries against their reference structures. For systematic incorporation of MM information and performance evaluation, we introduce a reusable MM adapter that injects a compact representation of the local environment into the QM geometry model, with implementations for a conditional flow model and direct coordinate predictors. We compare four MM conditions to assess the benefit of including the spatial organization and record correspondence of the MM environment: the correct corresponding environment (matched-MM), no environment information (no-MM), randomized atomic directions (shuffled-MM), and an environment from another record (mismatched-MM). Across the four tasks, matched-MM lowers the reference models' reconstruction error relative to no-MM, with a median relative reduction of 14.3%. In the Window-Coordinate and Environment-Only tasks, it also outperforms shuffled-MM and mismatched-MM. We further evaluate the adapter with flow and diffusion generators to assess its transferability across generative-model families; matched-MM again yields the lowest mean reconstruction error among the four conditions for both families. EnvGeoBench enables systematic quantification of how molecular environments improve QM geometry generation, and its reusable adapter provides a general mechanism for integrating MM context into existing geometry generators.