Cosmos-RL is a flexible and scalable Reinforcement Learning framework specialized for Physical AI applications.
Cosmos-RL provides toolchain to enable large scale RL training workload with following features:
- Parallelism
- Tensor Parallelism
- Sequence Parallelism
- Context Parallelism
- FSDP Parallelism
- Pipeline Parallelism
- Fully asynchronous (replicas specialization)
- Policy (Consumer): Replicas of training instances
- Rollout (Producer): Replicas of generation engines
- Low-precision training (FP8) and rollout (FP8 & FP4) support
- Single-Controller Architecture
- Efficient messaging system (e.g.,
weight-sync
,rollout
,evaluate
) to coordinate policy and rollout replicas - Dynamic NCCL Process Groups for on-the-fly GPU [un]registration to enable fault-tolerant and elastic large-scale RL training
- Efficient messaging system (e.g.,
This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.
NVIDIA Cosmos source code is released under the Apache 2 License.
NVIDIA Cosmos models are released under the NVIDIA Open Model License. For a custom license, please contact cosmos-license@nvidia.com.