Benchmark Almanac

MA-Bench

Not in model cards

Models do military mission analysis under the joint planning process on long-context scenarios, graded against expert rubrics.

Dataset created September 25th, 2026 under CC BY 4.0.

Released
October 2026
Kind
Other
Level
Expert
Scored
Graded by a model
Answers
Open-ended
Tasks
All public

In the authors’ words

How well can a language model turn a large, incomplete and partly contradictory body of documents into a plan when no single correct answer exists? We introduce Mission Analysis (MA)-Bench, built on mission analysis, the first step of military operational planning, in which a staff reads the full situation and states the problem before anyone proposes a solution. Its 10 expert-built scenarios pair synthetic packets of ten to twelve documents with 1,257 expert-written pass/fail requirements, each containing information on their source, question type, and importance level. A reasoning-model judge grades each brief against the requirements without seeing the documents; it grades like a fifth credentialed planner, leaving a four-planner panel's agreement unchanged (Fleiss κ 0.42 to 0.41), and a judge from a second provider reproduces the model ranking (Spearman 0.94). Across twenty frontier and open-weights models the best gets 62% of the rubric items right. Models are strongest on facts stated in the documents (58%) and weakest on judgments that must be inferred (33%), and six failures in ten are omissions rather than errors. MA-Bench grades the determinations, not the prose. We release the packets, rubrics, prompts, scorer and every graded brief with item-level verdicts.

Abstract of MA-Bench: Measuring Operational Planning in Language Models (arXiv:2610.19138, CC0)

No scores here yet

No lab, leaderboard or Epoch AI run has reported a score for MA-Bench yet.

No lab model card reports it yet

We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.

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