VLRS-Bench - Spatiotemporal Evolution Reasoning: leaderboard

Metric: Score (%) on the 125 Spatiotemporal Evolution Reasoning (two images) questions of VLRS-Bench remote-sensing reasoning questions built from 11 public optical, multi-temporal and change-detection datasets with DSM, NIR, mask and metadata priors, drafted by GPT-5-chat and reviewed by models and nine RS experts; single-choice (5 options) and true/false items score 1 when correct, 8-option multiple-choice and fill-in-the-blank items score 1 when fully correct and 0.5 when partially correct (blanks matched by embedding similarity above 0.8); zero-shot with a standardized prompt; mean item score times 100; higher is better. Source: arxiv.org. Saturation forecast: Around 2029. 20 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)46#54
2GPT-5.443.6#76
3GPT-4o (2024-11-20)40#369
4GPT-5 Chat38#233
5GPT-4o Mini35.2#588
6Claude Opus 4.633.6#60
7Llama 3.2 90B30#575
8Qwen 2.5 VL 32B Instruct25.6#443
9Qwen 2.5 VL 7B Instruct24.8#643
10Claude 3.5 Haiku23.2#553
11Qwen 2.5 VL 72B Instruct21.6#364
12Gemini 2.5 Flash11.6#237
13GLM-4.5V8.4#339

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=vlrs-bench-spatiotemporal-evolution-reasoning · How It Works · Data refreshed daily, snapshot 2026-10-11.