tools
RL Swarm
RL Swarm is an open-source framework for distributed reinforcement learning, where models learn through peer-to-peer collaboration.
RL Swarm lets researchers and developers run nodes that connect local language models into a distributed reinforcement-learning environment. Agents solve tasks, exchange answers and critiques, receive rewards, and update their policies from collective feedback.
Its current environment is CodeZero, where Proposers create coding challenges, Solvers attempt them, and Evaluators score submissions. RL Swarm runs on Windows through WSL 2, Linux, and macOS, but Gensyn says there are currently no official swarms running and Gensyn-hosted nodes are paused. No official pricing page was found.
Features
- Runs peer-to-peer distributed reinforcement-learning nodes
- Supports multi-agent, multi-stage training environments
- Coordinates node identity and communication across the swarm
- Uses CodeZero for cooperative coding tasks
- Provides Proposer, Solver, and Evaluator roles
- Shares rollouts and feedback between participating nodes
- Open source under the MIT Licence
Use cases
- Run a local node to participate in distributed model training
- Build custom multi-agent reinforcement-learning environments
- Train models collaboratively on coding challenges
- Study peer-to-peer coordination and reward sharing
- Track node participation and training activity on the testnet