# BioBasicsBench: everyday wet-lab science (BioBasicsBench)

> OpenAI and Ligo's benchmark of how well AI agents interpret raw wet-lab evidence, such as gel and blot images, colony plates, microscopy, sequencing files and instrument exports, spot experimental errors and recognize when the data cannot support a conclusion.

Canonical page: https://benchlm.ai/benchmarks/biobasicsbench

- Category: [Reasoning](/reasoning)
- Last updated: November 6, 2026

## About BioBasicsBench

- Year: 2026
- Tasks: 100 routine wet-lab analysis tasks (88 multimodal) across five domains
- Format: Mean reward (% of rubric credit), five attempts per task
- Difficulty: Routine wet-lab data interpretation
- Paper: [Measuring how AI agents handle everyday wet-lab science](https://openai.com/index/measuring-how-ai-agents-handle-wet-lab-science/)

Ligo scientists wrote the 100 tasks from their own experiments across protein methods, imaging and cytometry, quantification and assays, nucleic acid methods and molecular cloning; each task has an expert-written rubric and went through two internal reviews and one external PhD-level review. Agents return a structured answer and earn partial credit per rubric criterion; the score is mean reward (percent of available credit) over five attempts per task, with 95% whole-task bootstrap intervals. OpenAI ran every published result and has not released the tasks, so BenchLM shows the scores display-only and keeps them out of weighted rankings. BenchLM stores each model's highest published reasoning effort: max for GPT-6 Astra, GPT-6.1 Sol, GPT-5.6 Sol and GPT-6 Luna, xhigh for GPT-5.2, GPT-5.4 and GPT-5.5.

BioBasicsBench is currently displayed on BenchLM for reference, but it is excluded from the weighted scoring formula.

## Leaderboard (7 models)

| Rank | Model | Creator | Score |
|------|-------|---------|-------|
| 1 | [GPT-6 Astra](/models/gpt-6-astra) | OpenAI | 67.0% |
| 2 | [GPT-6.1 Sol](/models/gpt-6-1-sol) | OpenAI | 62.6% |
| 3 | [GPT-5.6 Sol](/models/gpt-5-6-sol) | OpenAI | 45.6% |
| 4 | [GPT-6 Luna](/models/gpt-6-luna) | OpenAI | 37.6% |
| 5 | [GPT-5.5](/models/gpt-5-5) | OpenAI | 35.4% |
| 6 | [GPT-5.4](/models/gpt-5-4) | OpenAI | 33.2% |
| 7 | [GPT-5.2](/models/gpt-5-2) | OpenAI | 31.2% |

## FAQ

### What does BioBasicsBench measure?

OpenAI and Ligo's benchmark of how well AI agents interpret raw wet-lab evidence, such as gel and blot images, colony plates, microscopy, sequencing files and instrument exports, spot experimental errors and recognize when the data cannot support a conclusion.

### Which model scores highest on BioBasicsBench?

GPT-6 Astra by OpenAI currently leads with a score of 67.0% on BioBasicsBench.

### How many models are evaluated on BioBasicsBench?

7 AI models have published results on BioBasicsBench in the BenchLM catalog.

### Does BioBasicsBench affect BenchLM's overall score?

Not directly. BioBasicsBench is still displayed on BenchLM for reference, but it is excluded from the weighted scoring formula.

## Compare Top Models on BioBasicsBench

- [GPT-6 Astra vs GPT-6.1 Sol](/compare/gpt-6-1-sol-vs-gpt-6-astra)
- [GPT-6.1 Sol vs GPT-5.6 Sol](/compare/gpt-5-6-sol-vs-gpt-6-1-sol)
- [GPT-5.6 Sol vs GPT-6 Luna](/compare/gpt-5-6-sol-vs-gpt-6-luna)
- [GPT-6 Luna vs GPT-5.5](/compare/gpt-5-5-vs-gpt-6-luna)