NeMo Gym provides infrastructure to develop environments for AI agents, run scalable evaluation and training, and access a collection of benchmark environments. An environment comprises a dataset of tasks, an agent harness defining model-world interaction, a verifier for scoring task completion, and per-task execution state. It supports transitioning between evaluation, agent optimization, and training workflows at scale.