Beijing Academy of Artificial Intelligence (BAAI) · Self-Improving Agent Model

AREX-2

A 27B dense model from BAAI, uploaded 29 September and fine-tuned from Qwen3.8-27B, trained to improve a solution over several rounds by proposing, measuring, reflecting and revising. It learned on machine-learning and algorithmic coding tasks with verifiable feedback, and the authors say the skill carries over to deep research. BAAI reports 70.7 on Frontier-CS (Agent Track), 81.8 on MLE-Lite, 84.0 on BrowseComp, 92.2 on GAIA and 93.8 on DeepSearchQA, all self-reported in the model card. 262K-token context, Apache-2.0 weights and a companion paper (arXiv 2609.38288).