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AI CURATED HOT STORY · 11/7/2026

OpenAI Releases BioBasicsBench to Test AI Agents on Raw Wet-Lab Data

1 reports archived1 independent sourcesupdated 11/7/2026, 03:54:08
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OpenAI, working with enzyme-design firm Ligo, introduced BioBasicsBench, a 100-task benchmark built from real gels, colony plates, microscopy videos and sequencing reads that tests whether AI agents can interpret raw lab data, spot errors and recognize when evidence is insufficient. GPT-6 Astra scored 66.7% of available credit versus 43.8% for GPT-5.6 Sol, while using roughly half the output tokens at the xhigh setting, indicating the gain is not driven by longer reasoning.

LATEST/OpenAI, working with enzyme-design firm Ligo, introduced BioBasicsBench, a 100-task benchmark built from real gels, colony plates, microscopy videos and sequencing reads that tests whether AI agents can interpret raw lab data, spot errors and recognize when evidence is insufficient. GPT-6 Astra scored 66.7% of available credit versus 43.8% for GPT-5.6 Sol, while using roughly half the output tokens at the xhigh setting, indicating the gain is not driven by longer reasoning.

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Total 1 reports · Latest first
  1. Rohan Paul (@rohanpaul_ai)T2·72 pts

    OpenAI Releases BioBasicsBench to Test AI Agents on Raw Wet-Lab Data

    • BioBasicsBench was co-built by OpenAI and Ligo, with 100 tasks drawn from real gels, colony plates, microscopy, sequencing reads and bench videos
    • Rubrics award partial credit, including for spotting errors or stating that evidence cannot support a conclusion
    • GPT-6 Astra scored 66.7% versus 43.8% for GPT-5.6 Sol, while using about half the output tokens per task