LogiScope-VQA - Fine-Grained Perception (Cross-Instance): leaderboard
LogiScope-VQA Industrial Element Perception task on fine-grained perception across instances (FP-C), asked over real logistics-park images and videos with human-validated answers (LogiScope-VQA, arXiv 2609.09790v1, Table 1). Micro-averaged accuracy converted from fractions to percent; higher is better; the paper's random-choice baseline scores 22.
Metric: Micro-averaged accuracy (%). Source: arxiv.org. Saturation forecast: Around March 2027. 20 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Gemini 3.1 Pro (Preview) | 70 | #64 |
| 2 | GPT-5.5 | 68 | #33 |
| 3 | Qwen 3.5 Plus | 65 | #133 |
| 4 | Claude Sonnet 4.6 | 64 | #94 |
| 5 | Qwen 3.7 Plus | 64 | #98 |
| 6 | Claude Opus 4.7 | 61 | #51 |
| 7 | Kimi K2.6 | 60 | #113 |
| 8 | Qwen 3 VL 235B A22B | 59 | #251 |
| 9 | GPT-5.4 | 58 | #83 |
| 10 | Kimi K2 (Thinking) | 54 | #252 (Kimi K2) |
| 11 | MiniMax-M2.5 | 54 | #316 |
| 12 | MiniMax-M2.1 | 49 | #299 |
| 13 | GLM-5.2 | 45 | #80 |
| 14 | GLM-4.7 | 41 | #202 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=logiscope-vqa-fine-grained-perception-cross-instance · How It Works · Data refreshed daily, snapshot 2026-11-05.