Miles
### TL;DR
Miles is an open-source reinforcement learning (RL) framework designed for large-scale model post-training, including agentic workloads. It integrates SGLang for high-throughput rollouts with Megatron-LM or FSDP2 for distributed training, providing a stable and efficient stack for frontier models.
Key Insights & Metrics
Key Features
- Native SGLang rollout with fully asynchronous scheduling
- Rollout Routing Replay (R3) for stable MoE training
- Token-in-Token-Out (TITO) data path for multi-turn agentic sessions
- Extensive hardware support including NVIDIA Blackwell/Hopper and AMD Instinct
- Support for diverse RL algorithms including GRPO, GSPO, PPO, and REINFORCE++
- Unified low-precision pipeline supporting FP8, MXFP8, and NVFP4
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