Benchmark Almanac

Meta BioKnowledge Proxy

Only in system cards

Models answer tacit knowledge and troubleshooting questions on wet-lab workflows for proxy biological agents. Has 200 single-answer and 100 multiple-answer questions.

In-house Meta evaluation. The tasks are not public.

Made by Meta with Frontier Design Group Released Oct 2025 Hazardous knowledge Tasks kept private Last in a system card Oct 2025 Last model added Oct 2025
Level
Expert Specialists with years of training, often over hours of work
Scored
Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
Answers
Multiple choice
1
System card reports it, from 1 lab

No scores here yet

No lab, leaderboard or Epoch AI run has reported a score for Meta BioKnowledge Proxy yet.

Labs report it only in system cards

We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark. Some system cards do, below.

One system card reports it

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
8 Oct 2025 Code World Model (CWM) technical report Meta BioKnowledge Proxy, no overall score: MCQA single response 69.5, multiple response 28.7 (Table 10) Bio and chem risk

More in Biology and chemistry

All 96 in Biology and chemistry
  • SUPERChem In use Models solve 500 expert-written chemistry reasoning problems, offered in multimodal and text-only forms. Expert solution paths also allow a reasoning path score. Tencent Hy4 preview 66.4%
  • GeneBench Pro In use Agents analyze messy simulated genomics and biology datasets to estimate a decision-relevant quantity across 129 problems. Scored automatically against known answers. GPT-6 Astra 37.1%
  • LifeSciBench In use Models complete 750 expert-written life science research tasks, often with attached figures, tables, or sequence files. Graded against expert rubrics as score and pass rate. GPT-6 Astra 60.3%
  • MolecularIQ In use Models answer questions about molecular graphs, such as counting, indexing and constrained generation, and a symbolic checker verifies each answer. Intern-S2-397B 62.4%
  • TOMG-Bench In use Models generate molecules from natural language requests in three tasks: molecule editing, molecule optimization and customized generation. Each output is checked for validity and for meeting the requested properties. Intern-S2-397B 66.8%
  • BABE Fading Models reason from experimental results in peer-reviewed biology papers to draw conclusions, with causal and cross-scale inference. Seed2.0 Lite (0428) 57.9%