Seeing What Matters - Strict-Clean VLM - Wrong-command Evidence: leaderboard

Seeing What Matters v1, strict-clean full-candidate VLM stress test: 12 frozen RGB candidate views, exactly 3 unique ranked view identifiers, 1500 evaluator episodes per VLM; simulator postconditions hidden from selector. These results are not the sequential active-acquisition policy. Source-native model/endpoint labels retained; effort and exact served snapshot unreported.

Metric: Score (%). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 7 models tracked.

Top models

#ModelScoreOverall rank
1Amazon Nova Pro (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)20.3
2Qwen3-VL-8B (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)20.7
3Grok 4.6 (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)27.8
4Gemma 3 27B (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)28.1
5Grok 4.3 (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)28.2
6Llama 4 Maverick (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)32.3
7Sonar Pro (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)34.4

Interactive version: theaggregate.ai/benchmark?slug=seeing-what-matters-strict-clean-vlm-wrong-command-evidence · How It Works · Data refreshed daily, snapshot 2026-11-12.