MultivationBench: leaderboard
Metric: Exact-match accuracy (%, predicted option set equals the gold set) of multi-label motivation predictions for visually grounded character behaviors in sequential visual narratives, reasoning over the accumulated story images and text (Maslow 8-level needs and Reiss 16 basic desires, definition and practical-motivation tasks), zero-shot at temperature 0; multimodal input, common subset of 14,180 tasks from 1,000 stories that every model answered; higher is better. Source: arxiv.org. Saturation forecast: Around 2034. 8 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Phi-4 Multimodal Instruct | 39.22 |
| 2 | Gemini 3 Flash | 36.09 |
| 3 | Llama 4 Scout | 33.48 |
| 4 | Grok 4.1 Fast | 32.53 |
| 5 | Llama 4 Maverick | 30.28 |
| 6 | O4 Mini | 27.29 |
| 7 | Nemotron Nano 12B v2 VL | 8.58 |
Interactive version: theaggregate.ai/benchmark?slug=multivationbench · How It Works · Data refreshed daily, snapshot 2026-09-29.