WeightBridge: An Efficient Weight Transfer Library for Reinforcement Learning

arXiv:2609.25442 · cs.DC, cs.LG, cs.NI · Submitted 2026-09-21 · Read on arXiv

cs.DC, cs.LG, cs.NI

Submitted: 2026-09-21

Updated: 2026-09-21

Comments: 25 pages, 16 figures

Code: https://github.com/PrimeIntellect-ai/prime-rl

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Reinforcement Learning — 18× in this paper · explained in 4 episodes
• Average GPU Stall Time — 6× in this paper
• Redundancy — 6× in this paper · explained in 2 episodes
• Quantization — 5× in this paper · explained in 12 episodes
• Sparsity — 4× in this paper · explained in 4 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Communication Overhead — 3× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 3× in this paper · explained in 25 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• GRPO — 2× in this paper · explained in 6 episodes
• Perplexity — 2× in this paper · explained in 3 episodes
• Ray Direct Transport — 2× in this paper
• Decode — 1× in this paper · explained in 2 episodes
• EMMA — 1× in this paper · explained in 2 episodes
• End-to-end Weight Transfer Time — 1× in this paper
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Mixture-of-Experts (MoE) — 1× in this paper · explained in 7 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

Sources

• DeepSpeed Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale
• Fast LLM Post-training via Decoupled and Fastest-of-N Speculation
• RollPacker: Mitigating Long-Tail Rollouts for Fast, Synchronous RL Post-Training
• Better & Faster Large Language Models via Multi-token Prediction
• AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training
• LoRA: Low-Rank Adaptation of Large Language Models
• Stabilizing Off-Policy Training for Long-Horizon LLM Agent via Turn-Level Importance Sampling and Clipping-Triggered Normalization
• StaleFlow: Staleness-Aware Data Management for Mitigating Data Skewness in Fully Disaggregated RL Post-Training
• Muon is Scalable for LLM Training
• Proximal Policy Optimization Algorithms
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
• NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment
• Kimi K2: Open Agentic Intelligence
• Kimi Linear: An Expressive, Efficient Attention Architecture
• Kimi K3: Open Frontier Intelligence
• Qwen3 Technical Report
• Learn Hard Problems During RL with Reference Guided Fine-tuning
• RLBoost: Harvesting Preemptible Resources for Cost-Efficient Reinforcement Learning on LLMs
• DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

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