SIGNPOST-Bench - Original Image Localization: leaderboard

Geolocation of unedited images with their native scene text in SIGNPOST-Bench (arXiv 2608.04244v1, Table 1). Weighted localization accuracy scores each prediction as exp(-0.005 x geodesic error in km), macro-averaged over IM2GPS3K, YFCC4K, GoogleSV and BaiduSV, in percent; higher is better.

Metric: Weighted localization accuracy (%; exp(-0.005 x geodesic km), four-dataset macro average). Source: arxiv.org. Saturation forecast: Around March 2027. 20 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)64.01#64
2Gemini 3 Flash63.94#103
3Doubao-Seed-2.0-Pro-26021561.03#86
4Gemini 2.5 Pro58.16#159
5GPT-555.73#105
6Kimi K2.555.73#152
7Gemini 2.5 Flash53.49#255
8Claude Sonnet 4.652.39#94
9Claude Opus 4.651.06#67
10GPT-4o47.01#357
11Qwen 3 VL 235B A22B Instruct42.78#280
12GPT-5.440.25#83
13Qwen 3 VL 30B A3B Instruct38.88#390
14Grok 438.15#189
15GPT-4o Mini35.37#598

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-original-image-localization · How It Works · Data refreshed daily, snapshot 2026-11-05.