NarrativeBench - BP 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: BP 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)70.6
2gemini-2.5-flash (NarrativeBench Run: thinking-budget=0;output=3000)60.5
3gemini-3.8-flash (NarrativeBench Run: low;output=3000)57.8
4gemma-4-26B-A4B-it (NarrativeBench Run: disabled;output=3000)55.8
5gpt-oss-120b (NarrativeBench Run: low;output=3000)51.4
6Qwen3.5-9B (NarrativeBench Run: disabled;output=3000)48.9
7kimi-k2.6 (NarrativeBench Run: disabled;output=3000)48.3
8gpt-oss-20b (NarrativeBench Run: medium;output=16384)45.8
9gpt-5.4-mini-2026-03-17 (NarrativeBench Run: reasoning=none;output=3000)45.5
10DeepSeek-V4-Flash (NarrativeBench Run: disabled;output=3000)45.5

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