Alibaba Qwen Introduces QwenGyre: Elastic Reinforcement Learning RL for XLong-Horizon Agents
Alibaba Qwen introduced QwenGyre, elastic RL that speeds extreme long-horizon agent training.
Alibaba’s Qwen team introduced QwenGyre, an elastic reinforcement-learning framework for training coding agents on extreme long-horizon tasks through unmodified black-box harnesses. It moves idle GPUs between rollout and training and compresses branching agent histories into at most five trajectories per execution. On Qwen 3.6 122B and Qwen 3.8 2.4T, it was 1.21x to 1.85x faster than Colocate and up to 1.78x faster than Async at matched scores. A 48-step Qwen 3.8 2.4T run finished in 75.42 hours and lifted NL2RepoBench from 52.48% to 58.54%; the summary links no public code.
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