PredicateLongBench - Clustered Near-Sorted Decoys (Synthetic): leaderboard

PredicateLongBench asks a model to find the run of words in a very long list that satisfies a stated predicate, such as a lexicographically sorted sequence. This board covers the same near-sorted decoys clustered next to the target in a synthetic word list. Answers are exact-match and outputs that exceed the generation budget count as wrong, so the score reflects both search and output discipline.

Metric: Accuracy (%; share of the 100 synthetic word lists of about 128K tokens whose answer is exactly the one word sequence satisfying the predicate, locate the sorted run with 8 near-sorted decoys clustered next to it; up to 16K output tokens including reasoning, an answer past the cap counts as wrong). Source: arxiv.org. Saturation forecast: Estimated already saturated. 9 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 4.6 (Thinking)98#102 (Claude Opus 4.6)
2GPT-5.4 (High)70#123 (GPT-5.4)
3Gemini 3.1 Pro (Preview) (High)64#94 (Gemini 3.1 Pro (Preview))
4Claude Opus 4.630#102
5MiniMax-M2.710#518
6GPT-5.4 (Non-reasoning)5#123 (GPT-5.4)
7Gemini 3.1 Pro (Preview) (Low)5#94 (Gemini 3.1 Pro (Preview))
8GLM-5.12#179
9Qwen 3.5 397B A17B0#246

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=predicatelongbench-clustered-near-sorted-decoys-synthetic · How It Works · Data refreshed daily, snapshot 2026-11-13.