Recently, the MetaDecision structured decision-making model, crafted by the innovative Meta-Task Lab, has showcased remarkable prowess on the esteemed JevBench decision-making model evaluation leaderboard, securing a prestigious position among the top three. As of October 17th, amidst a competitive field of 129 open-source systems, its 31B iteration claims the third spot, while the 12B variant leads the pack among models of equivalent scale. GPU benchmark tests, meticulously conducted by the leaderboard, unveil that the median latency for a singular judgment by the 31B version is a mere fraction of a second—less than 0.2 seconds, to be precise (excluding network latency). Meta-Task Lab, a pioneer in Agent Infra and decision-making models, offers embeddable Agent operation platforms, coupled with comprehensive knowledge and model services, empowering users with cutting-edge solutions.