OpenAI introduces BioBasicsBench, a 100-task test of AI agents on wet-lab data

AIOpenAI introduced BioBasicsBench, built with enzyme-design company Ligo, to test whether AI agents correctly read raw lab data such as gel photos and microscope videos. The 100 tasks give partial credit for spotting errors or saying evidence cannot support a conclusion. The post reports GPT-6 Astra scored 66.7% of available credit against 43.8% for GPT-5.6 Sol, and that Astra used about half the older model's output tokens per task at the xhigh setting.

AIOpenAI introduces BioBasicsBench, a benchmark for measuring how AI agents handle routine wet-lab science analyses. Developed with biotech company Ligo, it draws on 100 tasks from real experiments to test whether agents can interpret raw lab data, identify errors, and recognize when evidence does not support a conclusion.