Features and Roadmap#

Available Now#

  • Distributed Training - Ray-based infrastructure.

  • Environment Support and Isolation - Support for multi-environment training and dependency isolation between components.

  • Worker Isolation - Process isolation between RL Actors (no worries about global state).

  • Learning Algorithms - GRPO/GSPO/DAPO, SFT (with LoRA), DPO, and on-policy distillation.

  • Multi-Turn RL - Multi-turn generation and training for RL with tool use, games, etc.

  • Advanced Parallelism with DTensor - PyTorch FSDP2, TP, CP, and SP for efficient training (through NeMo AutoModel).

  • Larger Model Support with Longer Sequences - Performant parallelism with Megatron Core (TP/PP/CP/SP/EP/FSDP) through NeMo Megatron Bridge.

  • Sequence Packing - Sequence packing in both DTensor and Megatron Core for large training performance gains.

  • Fast Generation - vLLM backend for optimized inference.

  • Hugging Face Integration - Out-of-box support in the DTensor path, with checkpoint conversion available for the Megatron path through Megatron Bridge middleware.

  • End-to-End FP8 Low-Precision Training - Support for Megatron Core FP8 training and FP8 vLLM generation.

  • Vision Language Models (VLM) - Support SFT and GRPO on VLMs.

  • Megatron Inference - Megatron Inference for fast day-0 support for new Megatron models without weight conversion.

  • Async RL - Support for asynchronous rollouts and replay buffers for off-policy training, and enable a fully asynchronous GRPO.

  • NeMo-Gym Integration - RL environment integration.

  • GB200 - Container support for GB200.

Planned / In Progress#

  • Muon Optimizer - Emerging optimizer support for SFT/RL.

  • SGLang Inference - SGLang rollout support for optimized inference.

  • Improved Native Performance - Improved training time for native PyTorch models.

  • Improved Large MoE Performance - Improved Megatron Core training and generation performance.

  • New Models - Qwen3-Next and Nemotron-Super.

  • Expanded Algorithms - GDPO and broader LoRA coverage for GRPO and DPO.

  • Resiliency - Fault tolerance and auto-scaling support.

  • Speculative Decoding - Speculative decoding support for rollout acceleration.