SABER-Math - Calculus and Analysis: leaderboard

SABER-Math (2026) tests retrieval models on finding mathematically related competition problems: each query problem reranks a pool of 150 candidate problems whose graded relevance comes from pairwise LLM judgments. This board covers the calculus and analysis queries, with the query given as a problem statement and each candidate as a problem with its solution. Scored as nDCG@10 on a 0 to 100 scale; higher is better.

Metric: nDCG@10 (0-100) with exponential gain, printed 0 to 1 and scaled by 100: each competition or olympiad problem query reranks its own pool of 150 candidate problems, graded 0 to 5 by Bradley-Terry fits of GPT-OSS-120B pairwise relevance judgments over a 20-round Swiss tournament; every system at its default configuration and task instruction, statement-full setting (the query is a problem statement, each document a problem with its solution), the queries of the calculus and analysis domain; higher is better. Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 43 models tracked.

Top models

#ModelScoreOverall rank
1ReasonReranker-Qwen3-32B71.2
2Diver-GroupRank-32B69.6
3ReasonEmbed-Qwen3-8B68.2
4Qwen3-Reranker-4B67.1
5RaDeR-7B66.6
6RaDeR-14B66.5
7ReasonEmbed-Llama-3.1-8B65
8Diver-4B64.5
9Qwen3-Reranker-8B63.9
10Qwen3-Reranker-0.6B63.4

Interactive version: theaggregate.ai/benchmark?slug=saber-math-calculus-and-analysis · How It Works · Data refreshed daily, snapshot 2026-11-13.