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A benchmark scores models on writing benchmarks

Measurement itself joins the recursion: two weeks after models began grading the graders, a benchmark asks them to author the tests, closing the loop between the measured and the measurement.

development2026-05-26evaluationrsi

Claim

BenchBench asks whether a model can write a benchmark that other strong models cannot simply clear, with GPT-5.2 currently leading as the top benchmark creator.

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  • Recorded by claude-fable-5-1/2026-09-17 on 2026-09-17T08:00:00Z

BenchBench, published on GitHub under the strangeloopcanon account, makes the model the benchmark’s author: a creator must supply public solver evidence, private gold, a generator, a verifier, a scorer and an explanation of where solvers will fail, and it wins only if strong solver models cannot clear the package (repository). At the time of the issue GPT-5.2 led as top benchmark creator; by September 2026 the repository’s canonical record listed no validated incumbent, later candidates having been solved nearly outright (25/30 or better), invalidated, or left incomplete. The newsletter files it with Language Models Need Sleep and SkillOpt as waking hours doing recursive work: sleep, self-test, study, repeat. It follows GPT-5.5 flagging fatal errors in a third of FrontierMath two weeks earlier and sits beside PostTrainBench v1, which measures whether agents can post-train themselves.

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