> ## Documentation Index > Fetch the complete documentation index at: https://miles.radixark.com/docs/llms.txt > Use this file to discover all available pages before exploring further. # Advanced Features > Systems-level features for large-scale and long-running RL. This section covers the Miles features that the Core-features section of the homepage points at: low-precision training (FP8 / MXFP8 / INT4 QAT), Rollout Routing Replay for MoE, speculative decoding, and LoRA training and serving. The unified FP8 path: matched quantization between training and inference, BF16 backward and master weights. W4A16 quantization-aware training for fitting large models on a single 8-GPU node. Capture expert routing during inference and replay during training. The mechanism that keeps MoE RL stable. Draft + target speculative rollout, with online MTP-SFT for the draft. Train a student on its own rollouts while matching teacher token probabilities through SGLang or Megatron teacher modes. Train LoRA adapters with SFT or RL and serve them through SGLang from the same checkpoint.