OpenAI reports the deployment of LifeSciBench, a specialized evaluation framework designed to quantify AI system performance within authentic scientific research environments. The benchmark comprises 750 tasks meticulously constructed by 173 researchers holding PhD credentials and industry experience in biotechnology or pharmaceuticals. These tasks span seven distinct biological domains and seven research workflow categories, prioritizing complex capabilities such as evidence integration, experimental design, and scientific reasoning over simple factual recall.

The dataset emphasizes rigorous analytical depth, with over 79% of tasks necessitating multi-step reasoning averaging four logical steps per query. To simulate real-world conditions, the benchmark incorporates 1,062 authentic research attachments, including academic papers, charts, sequence data, and structural files, thereby testing an AI's ability to process and synthesize diverse scientific evidence.