TableVista - Noise: leaderboard
Metric: Accuracy (%) on the 3,000 TableVista questions under the Noise rendering (Gaussian speckle, downsampling, tilt and watermarks on the Web tables), direct-output prompt with thinking disabled (reasoning effort none for the GPT models), exact match with a GPT-5-mini semantic-equivalence check on exact-match failures; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 29 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-5.4 (Non-reasoning) | 70.8 |
| 2 | Gemma 4 31B (IT) | 54.3 |
| 3 | Llama 4 Maverick Instruct FP8 | 53.5 |
| 4 | Qwen 2.5 VL 72B Instruct | 51.1 |
| 5 | GPT-5.4 Mini (Non-reasoning) | 49.5 |
| 6 | Qwen 2.5 VL 32B Instruct | 49.3 |
| 7 | Qwen 3.5 27B (Non-reasoning) | 49.2 |
| 8 | Qwen 3.5 122B A10B (Non-reasoning) | 49 |
| 9 | Llama 4 Scout Instruct | 47.5 |
| 10 | Gemma 4 26B A4B (IT) | 43.2 |
| 11 | Qwen 3 VL 30B A3B Instruct | 43 |
| 12 | Qwen 2.5 VL 7B Instruct | 42.5 |
| 13 | Qwen 3.6 35B A3B (Non-reasoning) | 41.6 |
| 14 | Qwen 3 VL 8B Instruct | 41.4 |
| 15 | Gemma 3 27B (IT) | 40.1 |
Interactive version: theaggregate.ai/benchmark?slug=tablevista-noise · How It Works · Data refreshed daily, snapshot 2026-10-07.