PlanBench-V - Spatial Relationship Reasoning: leaderboard

PlanBench-V (2026) tests vision-language models on interpreting Chinese territorial spatial planning maps with questions curated by professional planners; a GPT-4o-mini judge scores each answer from 0 to 2 against reference answers with annotated critical points. This board is the mean score on topological, sequential and metric relations between map elements; higher is better.

Metric: Mean score (out of 2) on topological, ordinal and metric spatial relationship reasoning, reasoning level; answers to expert-curated questions on Chinese territorial spatial planning maps are scored 0 to 2 by a GPT-4o-mini judge (temperature 0) against structured reference answers with annotated critical points; objective items use exact match or semantic similarity; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 17 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3.6 Plus1.67#222
2Gemini 2.5 Pro1.44#266
3Kimi K2.61.41#178
4GPT-5.41.38#123
5Qwen 3.6 Flash1.35#424
6GPT-4o1.31#741
7Claude Opus 4.71.3#79
8Qwen 2.5 VL 7B Instruct0.87#1833
9InternVL3-8B0.8#1688
10InternVL3-14B0.79#1182
11GPT-4o Mini0.79#1623
12Qwen 2 VL 7B0.72#2261
13Qwen 2 VL 2B0.5#6284

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

Interactive version: theaggregate.ai/benchmark?slug=planbench-v-spatial-relationship-reasoning · How It Works · Data refreshed daily, snapshot 2026-11-13.