A 3-Billion Parameter Agent Model Is Outperforming Giants on SWE-bench — Meet ROME

Chinese researchers released ROME, a 3B-parameter model that achieves state-of-the-art agentic performance on SWE-bench using a novel chunk-level reinforcement learning approach, challenging the assumption that capable agents require massive models.