SFI-Bench - Global and Conditional Counting: leaderboard

Metric: Accuracy (%) on the global and conditional counting questions, four-option multiple choice on egocentric indoor videos (ARKitScenes and ScanNet++ scans), zero-shot with the same prompt templates, models at their default configurations; answered directly with no tools; higher is better. Source: arxiv.org. Saturation forecast: Around December 2027. 25 models tracked.

Top models

#ModelScore
1Gemini 3.1 Pro (Preview)59.1
2GPT-558.4
3GPT-5.4 (High)58.4
4Gemini 3.1 Flash Lite55
5GPT-5.454.5
6Gemini 2.5 Pro54.4
7Qwen 3 VL 235B A22B (Thinking)53.8
8Qwen 3 VL 235B A22B Instruct52.3
9O4 Mini51
10Qwen 3 VL 32B Instruct50
11Qwen 3 VL 32B (Thinking)49.5
12Qwen 3 VL 8B (Thinking)42.6
13Qwen 3 VL 30B A3B Instruct42.1
14Gemini 2.5 Flash41.5
15Qwen 3 VL 8B Instruct41.5

Interactive version: theaggregate.ai/benchmark?slug=sfi-bench-global-and-conditional-counting · How It Works · Data refreshed daily, snapshot 2026-10-07.