TimeSpot - Daylight Phase: leaderboard

Metric: Accuracy (%) of the predicted daylight phase (such as sunrise, midday, sunset or night) on TimeSpot's 1,455 ground-level photographs from 80 countries, each answered zero-shot in a structured multi-field schema from the image alone; a Gemini-2.5-Flash judge normalizes each field (synonyms, abbreviations) and marks it correct or not; higher is better. Source: arxiv.org. Saturation forecast: Not forecast. 27 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 2.5 VL 7B Instruct64.09#643
2O4 Mini51.79#172
3GLM-4.1V-9B (Thinking)47.76#457 (GLM-4.1V-9B)
4GPT-5 Mini44.6#176
5Qwen 2.5 VL 32B Instruct44.54#443
6Llama 3.2 11B Instruct43.57#1112
7GLM-4.5V42.45#339
8Gemini 2.5 Flash (Non-reasoning)41.92#237 (Gemini 2.5 Flash)
9Qwen 3 VL 235B A22B Instruct41.91#264
10GPT-5.241.66#105
11Qwen 2.5 VL 72B Instruct36.84#364
12Gemini 2.5 Flash (Thinking)36.56#237 (Gemini 2.5 Flash)
13Mistral Medium 3.136.01#400
14InternVL3-78B34.91#345
15Llama 3.2 90B Vision Instruct33.88#611

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=timespot-daylight-phase · How It Works · Data refreshed daily, snapshot 2026-10-11.