torchforge: PyTorch-Native Agentic RL Library

torchforge is Meta's PyTorch-native RL library that separates infrastructure concerns from algorithm concerns. It enables rapid RL research by letting you focus on algorithms while handling distributed training, inference, and weight sync automatically.

When to Use torchforge

Choose torchforge when you need:

• Clean separation between RL algorithms and infrastructure
• PyTorch-native abstractions (no Ray dependency)
• Easy algorithm experimentation (GRPO, DAPO, SAPO in ~100 lines)
• Scalable training with Monarch actor system
• Integration with TorchTitan for model parallelism

Consider alternatives when:

• You need production-ready stability → use miles or verl
• You want Megatron-native training → use slime
• torchforge is experimental and APIs may change

Key Features