SIGNPOST-Bench - Multimodal Conflict Robustness Score: leaderboard

Composite score of SIGNPOST-Bench (arXiv 2608.04244v1, Table 1), which tests image geolocation when scene text is kept, removed, or replaced by compatible, unrelated or conflicting place names. MCRS = 100 x C^0.4 x R^0.6 combines localization capability C with conflict robustness R; 0-100, higher is better.

Metric: MCRS (0-100; 100 x C^0.4 x R^0.6). Source: arxiv.org. Saturation forecast: Around March 2027. 20 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash72.7#103
2Gemini 3.1 Pro (Preview)72.23#64
3Gemini 2.5 Pro69.8#159
4Gemini 2.5 Flash64.31#255
5GPT-564.28#105
6Doubao-Seed-2.0-Pro-26021564.23#86
7Claude Opus 4.662.56#67
8Claude Sonnet 4.662.08#94
9Kimi K2.561.74#152
10Qwen 3 VL 30B A3B Instruct58.5#390
11GPT-4o57.16#357
12GPT-5.454.77#83
13Qwen 3 VL 235B A22B Instruct53.36#280
14GPT-4o Mini50.68#598
15Grok 444.05#189

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=signpost-bench-multimodal-conflict-robustness-score · How It Works · Data refreshed daily, snapshot 2026-11-05.