NarrativeBench - DP recall (%): leaderboard

NarrativeBench v1,4800cases perconfiguration,1333articles,460queries,23publication/24query languages. Three articles perselected narrative. Document-ID citations measure instruction-following coverage: NI target-only F1,NE target-exclusion F1,MNI omitted-narrative recall,BP/DP all-narrative recall. Wrong-language responses zero;low-confidence language detection passes. Source parentheses are SE,not scores. ExactAPI/checkpoint,budget andthinking settings retained;9BBase distinct. Five native0–100 metrics,not agreement or signed bias/gap diagnostics.

Metric: DP recall (%). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 15 models tracked.

Top models

#ModelScoreOverall rank
1gemini-2.5-pro (NarrativeBench Run: thinking-budget=128;output=3000)74.9
2gemini-3.8-flash (NarrativeBench Run: low;output=3000)68.7
3gemini-2.5-flash (NarrativeBench Run: thinking-budget=0;output=3000)65.9
4gemma-4-26B-A4B-it (NarrativeBench Run: disabled;output=3000)61.2
5gpt-oss-120b (NarrativeBench Run: low;output=3000)56.6
6gpt-5.4-mini-2026-03-17 (NarrativeBench Run: reasoning=none;output=3000)55.4
7Qwen3.5-9B (NarrativeBench Run: disabled;output=3000)52.5
8kimi-k2.6 (NarrativeBench Run: disabled;output=3000)51.1
9gpt-oss-20b (NarrativeBench Run: medium;output=16384)50.8
10DeepSeek-V4-Flash (NarrativeBench Run: disabled;output=3000)50.4

Interactive version: theaggregate.ai/benchmark?slug=narrativebench-dp-recall · How It Works · Data refreshed daily, snapshot 2026-11-12.