ST-Bench (Image Input) - Spatial Correlation Reasoning: leaderboard

Spatial correlation reasoning task of ST-Bench (Ni, Wang, He, Jin and Jin, STReasoner paper, 2026): given the multivariate time series of a node graph, the model answers four-option questions about direct and multi-hop propagation between nodes. The model sees the node series rendered as plot images with the graph structure in text; scenarios are synthetic network simulations and Claude-4.5-Sonnet wrote the questions. Accuracy in percent on 1,592 held-out questions; higher is better.

Metric: Accuracy (%; 1,592 four-option questions). Source: arxiv.org. Saturation forecast: Around February 2027. 5 models tracked.

Top models

#ModelScoreOverall rank
1Claude Sonnet 4.576.04#244
2GPT-5.265.08#172
3Qwen 3 VL 8B Instruct53.52#982

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=st-bench-image-input-spatial-correlation-reasoning · How It Works · Data refreshed daily, snapshot 2026-11-12.