MMTU - Table Matching: leaderboard
The "Table Matching" subtask of MMTU. Massive Multi-Task Table Understanding benchmark with real-world table reasoning tasks including joins, transformations, cleaning, and question answering.
Metric: Accuracy (%). Source: huggingface.co. Saturation forecast: Estimated already saturated. 26 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5 | 91.63 | #98 |
| 2 | O3 | 91.08 | #124 |
| 3 | GPT-5 Mini | 89.48 | #186 |
| 4 | Gemini 2.5 Flash | 88.87 | #245 |
| 5 | Grok 3 Mini | 88.82 | #281 |
| 6 | Gemini 2.5 Pro | 88.44 | #152 |
| 7 | GPT-5 Chat | 87.37 | #241 |
| 8 | DeepSeek R1 0528 | 86.04 | #222 |
| 9 | GPT-4o (2024-11-20) | 84.71 | #381 |
| 10 | Qwen 3 32B | 83.91 | #443 |
| 11 | Qwen 3 235B A22B 2507 Instruct | 83.68 | #300 |
| 12 | Mistral Large 2 (Nov) Instruct (2411) | 82.97 | #465 |
| 13 | Qwen 3 235B A22B 2507 (Thinking) | 82.88 | #260 (Qwen 3 235B A22B 2507) |
| 14 | Qwen 3 8B | 82.03 | #674 |
| 15 | Llama 4 Maverick Instruct FP8 | 81.45 | #414 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=mmtu-table-matching · How It Works · Data refreshed daily, snapshot 2026-10-20.