DriveSpatial-mini - Understanding RMSE: leaderboard
Metric: Root mean squared error of numeric answers (distances, counts and other spatial measurements) on the spatial-understanding tasks on DriveSpatial-mini (a stratified 1,000-question subset, 50 per task), where the paper evaluates the proprietary VLMs and humans; lower is better. Source: arxiv.org. Saturation forecast: Around November 2027. 3 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-5 | 10.41 |
| 2 | GPT-4o | 12.71 |
Interactive version: theaggregate.ai/benchmark?slug=drivespatial-mini-understanding-rmse · How It Works · Data refreshed daily, snapshot 2026-10-07.