OAKS-Novel (RAG) - Sparse Changes: leaderboard

Metric: Interval-level accuracy (%) on OAKS-Novel (870 questions over novels whose answers evolve across 2K-token chunks), questions whose answer changes sparsely: the same questions are asked after every chunk and each answer is scored against the answer valid at that point, averaged over intervals and questions; RAG setting (top 30 earlier chunks retrieved with Qwen3-Embedding-0.6B); higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Pro82.2#145
2Gemini 3 Pro79.9#77
3Qwen 3 235B A22B 2507 Instruct74.7#291
4Qwen 3 Next 80B A3B Instruct74.4#352
5Gemini 2.5 Flash74.2#237
6Qwen 3 30B A3B 2507 Instruct68.9#464
7Qwen 3 4B 2507 Instruct68.1#745
8Gemma 3 27B (IT)67.3#509
9GPT-OSS-120B65.4#330
10Qwen 3 8B (Non-reasoning)60#667 (Qwen 3 8B)
11GPT-OSS-20B54.7#499
12Qwen 2.5 7B Instruct49.6#846
13Gemma 3 4B (IT)39.4#971

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=oaks-novel-rag-sparse-changes · How It Works · Data refreshed daily, snapshot 2026-10-11.