Measuring how AI agents handle everyday wet-lab science

Summary

OpenAI introduced BioBasicsBench, a 100-task benchmark developed with Ligo that measures how well AI agents interpret raw wet-lab experimental data, including gel images, colony plates, microscopy and instrument readouts. At the 'xhigh' reasoning setting, GPT-6 Astra earned an average of 66.7% of available credit, compared with 43.8% for GPT-5.6 Sol. The results show progress on routine lab analysis but leave room for improvement in image interpretation, control checking and applying experimental context.

Topics

• AI agents

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