The OpenEnv Challenge: SOTA Environments to
drive general intelligence
Sponsors: PyTorch team at Meta, Hugging Face, and Unsloth
Prizes:
-​ Prize pool: $10k in credits from HF
-​ An invitation to publish to the PyTorch.org blog about what you built

Description
As AI systems evolve from static predictors into fully agentic learners, high-quality general reinforcement
learning (RL) environments have become core infrastructure. They serve as the world in which agents
explore, reason, and acquire new skills. The OpenEnv Student Challenge invites participants to design
and build innovative, open-source RL environments that push the boundaries of what today’s agents can
learn.
Using OpenEnv, the emerging standard for environment creation and interoperability, students will
develop environments that are modular, reproducible, and seamlessly integrated with modern
PyTorch-native RL tooling like torchforge, TRL, and Unsloth
Participants will build production-ready environments that span coding tasks, interactive simulations,
robotics-inspired control problems, multi-agent dynamics, computer use, or entirely new categories of
agentic challenges. Submissions will be evaluated on creativity, clarity of design, scalability, and
alignment with OpenEnv’s standard API and hub ecosystem. Winning projects will contribute directly to
the broader open-source community, helping advance the tools and benchmarks that shape the future of
agentic AI research and post-training.
This challenge offers students hands-on experience with frontier AI development and the opportunity to
influence how the next generation of RL systems learn, adapt, and generalize.

Tasks & Deliverables
The goal of this competition is to create a real-worldRL environment and then attempt to solve it using
your favorite LLM. Examples of en
To enter the challenge:
1.​ Add your environment to the HF Hub
2.​ Publish training notebooks/scripts on Github (can be your own personal GitHub)
3.​ Write a blog on Huggingface

Evaluation Criteria
The main evaluation criteria will be based on the submission blog, we will have a judging panel that will
grade submissions based on:

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Creative and Robust use of OpenEnv
Technical Excellence
Story-telling
Open Source Demo
Green Agent wrapper for the environment

Resources & Getting Started
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Hello world tutorial:
https://colab.research.google.com/github/meta-pytorch/OpenEnv/blob/main/examples/OpenEnv_
Tutorial.ipynb
Github: https://github.com/meta-pytorch/OpenEnv
Docs: https://meta-pytorch.org/OpenEnv/
Environment hub: https://huggingface.co/openenv

Support
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Discord: https://discord.gg/ktH3zDxw