ReasonTabQA - English: leaderboard

ReasonTabQA accuracy on its English-language industrial tables: the model writes pandas code that reads the table files (multi-sheet directories, nested headers, very large tables) and prints an answer, which an LLM judge compares with the gold answer; percent, higher is better. TeleAI (China Telecom), 2026.

Metric: Answer Accuracy (%; LLM judge against gold answers, program-aided). Source: arxiv.org. Saturation forecast: Around February 2027. 33 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Pro (Preview)68.44#111
2Claude Opus 4.5 (Thinking)66.84#152 (Claude Opus 4.5)
3GPT-5.2 (Non-reasoning)61.29#172 (GPT-5.2)
4Claude Sonnet 4 (Thinking)60#397 (Claude Sonnet 4)
5Doubao-1.5-Thinking-Pro59.5#236
6Qwen 3 32B (Thinking)56.77#960 (Qwen 3 32B)
7QwQ-32B55.48#909
8DeepSeek R155.11#467
9DeepSeek R1 Distill Qwen 32B54.84#1780
10DeepSeek V354.81#705
11GPT-4o54.25#741
12Kimi K254.19#435
13Qwen 2.5 72B Instruct53.55#1093
14Qwen 3 30B A3B (Thinking)52#1124 (Qwen 3 30B A3B)
15Qwen 3 32B (Non-reasoning)49.03#960 (Qwen 3 32B)

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

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