SimScale is a research codebase for data-driven, non-reactive autonomous vehicle simulation and benchmarking, developed by OpenDriveLab. It provides a comprehensive pipeline for training and evaluating end-to-end driving policies on the nuPlan/OpenScene dataset, with support for synthetic data augmentation (SimScale) and multiple agent architectures including Transfuser, DiffusionDrive, and GTRS-Dense. The repository implements a Plan-Do-Measure (PDM) closed-loop scoring framework, metric caching, and a Hydra-based configuration system for flexible experiment management. While primarily a research platform, it includes production-like training scripts, evaluation pipelines, and submission tools for the NAVSIM v2 challenge. The codebase is heavily coupled to the nuPlan ecosystem and requires large-scale data downloads (>1TB), but offers reusable components such as abstract agent interfaces, feature/target builders, and batch IDM policies. It is actively maintained with recent commits and a growing community of extensions.