NeMo Gym

NeMo Gym is a library for evaluating and improving models and agents using environments. NeMo Gym provides infrastructure to develop environments, scalably run evaluation and training, and a collection of popular benchmarks and training environments.

When to Use NeMo Gym

• You need to evaluate models or agents in stateful environments (for example, code execution, tool calling, sandboxes).
• You want reproducible evaluation across teams using shared environments and verifiers.
• You need to use environments at scale — multiple repeats per task, or thousands of concurrent requests for training.
• You want to seamlessly transition between evaluation, agent optimization, and training.

If you are scoring model outputs with a stateless check and do not need scale or training, a script is probably sufficient.

What NeMo Gym Provides

• Modular, extensible interfaces for agents, environments, tasks, and verifiers
• Environment hub of popular benchmarks and training environments
• Use your own agents or choose from built-in harnesses
• Scale to thousands of concurrent environments
• Train with the RL framework of your choice
• Battle-tested in production Nemotron training

Integrations

NeMo Gym integrates with the broader agentic ecosystem:

• Environment libraries: Seamlessly combine environments and benchmarks from other libraries alongside NeMo Gym environments.
• Training framework libraries: Use environments for SFT and RL training.
• Agent harnesses: Popular agent harnesses for evaluation and training available out of the box.
• Agent framework libraries: Use your custom agent built with agent frameworks in NeMo Gym environments.
• Sandboxes: Isolate agent runtime execution.