LIT-RAGBench (English) - Logic: leaderboard

Metric: Accuracy (%) on the 30 Logic questions (resolving logical and lexical mismatches between question and documents) among 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
1GPT-590#91
2O390#121
3O4 Mini90#172
4GPT-5 Mini86.7#176
5Qwen 3 235B A22B 2507 Instruct86.7#291
6Qwen 3 235B A22B 2507 (Thinking)86.7#253 (Qwen 3 235B A22B 2507)
7Gemini 2.5 Pro83.3#145
8Gemini 2.5 Flash83.3#237
9GPT-4.1 Mini83.3#346
10GPT-5 Nano83.3#415
11GPT-4.180#240
12Gemma 3 27B (IT)73.3#509
13Llama 3.3 70B Instruct70#520
14Claude Sonnet 460#194
15Llama 3.1 8B Instruct50#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-logic · How It Works · Data refreshed daily, snapshot 2026-10-11.