PlanBench-V - Classification: 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 classifying planning maps by type; higher is better.

Metric: Mean score (out of 2) on classifying planning maps by type within the statutory planning system, 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 Pro1.66#266
3GPT-5.41.56#123
4GPT-4o1.41#741
5Kimi K2.61.34#178
6Claude Opus 4.71.32#79
7Qwen 3.6 Flash1.3#424
8InternVL3-14B1.18#1182
9Qwen 2.5 VL 7B Instruct1.09#1833
10Qwen 2 VL 7B1.03#2261
11InternVL3-8B1.03#1688
12GPT-4o Mini1.02#1623
13Qwen 2 VL 2B0.95#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-classification · How It Works · Data refreshed daily, snapshot 2026-11-13.