SABER-Math - Statement-Statement: 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 gives queries and candidates as problem statements only, without solutions. Scored as nDCG@10 on a 0 to 100 scale; higher is better.

Metric: Overall 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, all 1000 queries, statement-statement setting (queries and documents are problem statements only, no solutions); higher is better. Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 43 models tracked.

Top models

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

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