Data as of Aug 16, 2026 · Based on 3,131,739 AI responses across 10,525 prompts · See how Parse measures this
OpenRLHFopenrlhf.readthedocs.ioOpenRLHF is an open-source, production-ready framework for reinforcement learning from human feedback (RLHF). It combines a Ray + vLLM distributed architecture with a unified agent-based execution paradigm to enable scalable, extensible RLHF for very large models (70B+ parameters) and supports both single-turn and multi-turn interactions. It provides state-of-the-art RL algorithms (PPO, REINFORCE variants, GRPO, etc.), vision-language RLHF, async training with partial rollout, and production-grade features such as resumable checkpoints, logging, and multi-node deployment.
Sources
github.com shapes more of what AI says about OpenRLHF than any other source, at 33% of its citations.
arxiv.org · openrlhf.readthedocs.io · gocodeo.com · linkedin.com
The market map
RLHF Data Collection & Training Platforms →Where AI ranks OpenRLHF
Excerpts where OpenRLHF appeared in the AI's answer
OpenRLHF : A high-performance, production-ready framework that integrates Ray, vLLM, and DeepSpeed.
OpenRLHF : Widely regarded as a leading open-source framework for scalable RLHF, PPO, and DPO training
Excerpts where OpenRLHF appeared in the AI's answer
OpenRLHF: Widely regarded as the leading open-source framework for large-scale RLHF and training models past 70B parameters.
OpenRLHF: Exceptional if you are scaling up to massive models (hundreds of billions of parameters).
Excerpts where OpenRLHF appeared in the AI's answer
OpenRLHF : Built on top of Ray, vLLM, and DeepSpeed, this is the leading open-source framework for distributed PPO, DPO, and alternative training routines.
OpenRLHF: Built on Ray, DeepSpeed, and Hugging Face, this is the leading open-source framework for massive-scale distributed training.
