GeoMMBench - Remote Sensing: leaderboard

Metric: Micro-averaged accuracy (%) on the remote sensing discipline questions of the GeoMMBench test set (expert-written multimodal geoscience and remote sensing multiple-choice and numeric questions, zero-shot, LMMs-Eval, rule-based answer extraction, invalid outputs counted wrong); higher is better. Source: arxiv.org. Saturation forecast: Around 2029. 36 models tracked.

Top models

#ModelScore
1Gemini 1.5 Pro68.9
2Gemini 2.0 Flash67.5
3GPT-4o65.6
4O163.5
5Qwen 2.5 VL 7B60.6
6Qwen 2 VL 7B59.1
7Phi-4 Multimodal Instruct54
8Qwen 2 VL 2B48.2
9GPT-541.2

Interactive version: theaggregate.ai/benchmark?slug=geommbench-remote-sensing · How It Works · Data refreshed daily, snapshot 2026-10-07.