LIT-RAGBench (English): leaderboard

Metric: Mean accuracy (%) over the Integration, Reasoning, Logic and Table categories (Main) on the English translation of the 54 questions (translated with GPT-5), judged correct or incorrect against the reference answer by GPT-4.1 (2025-04-14); the generator receives the question with relevant and irrelevant documents of about 512 tokens each, temperature 0 where supported and the maximum reasoning length for reasoning models; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 15 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Flash87#237
2O385.2#121
3GPT-4.1 Mini84.1#346
4O4 Mini83.9#172
5GPT-4.183.6#240
6GPT-582.8#91
7Qwen 3 235B A22B 2507 (Thinking)81.5#253 (Qwen 3 235B A22B 2507)
8Qwen 3 235B A22B 2507 Instruct80.6#291
9Gemini 2.5 Pro78.4#145
10GPT-5 Mini78#176
11GPT-5 Nano73.7#415
12Gemma 3 27B (IT)68#509
13Claude Sonnet 465#194
14Llama 3.3 70B Instruct61.8#520
15Llama 3.1 8B Instruct39.6#1018

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

Interactive version: theaggregate.ai/benchmark?slug=lit-ragbench-english · How It Works · Data refreshed daily, snapshot 2026-10-11.