EuraGovExam - Engineering: leaderboard
Metric: Accuracy (%) on the engineering questions across the five regions; image-only: the model sees one scanned multiple-choice civil-service exam question in its original language and layout, with a fixed answer-format instruction and no OCR or tools; greedy decoding, one run; answers not in the required final-line format count as wrong; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 28 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5 | 88.81 | #91 |
| 2 | Gemini 2.5 Pro | 86.19 | #145 |
| 3 | O3 | 84.16 | #121 |
| 4 | O4 Mini | 81.98 | #172 |
| 5 | GPT-5.2 | 75 | #105 |
| 6 | Gemini 3 Flash (Preview) | 72.38 | #78 |
| 7 | GPT-5 Nano | 68.17 | #415 |
| 8 | Gemini 2.5 Flash | 64.83 | #237 |
| 9 | Claude Sonnet 4 | 56.4 | #194 |
| 10 | Gemini 3 Pro (Preview) | 55.23 | #64 |
| 11 | GPT-4.1 Mini | 51.16 | #346 |
| 12 | GPT-4.1 | 50 | #240 |
| 13 | GPT-4o | 33.72 | #333 |
| 14 | Qwen 2.5 VL 7B Instruct | 26.02 | #643 |
| 15 | Qwen 2 VL 7B Instruct | 20.93 | #816 |
No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.
Interactive version: theaggregate.ai/benchmark?slug=euragovexam-engineering · How It Works · Data refreshed daily, snapshot 2026-10-11.