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# NeMo Gym

> NeMo Gym is a library for evaluating and improving models and agents using environments.

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

![NeMo Gym Product Overview](https://files.buildwithfern.com/nvidia-gym.docs.buildwithfern.com/nemo/gym/1f21af95c3aa75bf8425dab33fad469b4b724f6cdb434d53cdeaaf53e8c88ec9/assets/images/product_overview.png)

## 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.

## Next Steps

Install NeMo Gym and run your first evaluation.

Browse available environments for evaluation and training.

Explore available agent harnesses and learn how to integrate your own agent.

Improve your agent or model with RL or fine-tuning.

Create your own evaluation or training environments.