Seeing What Matters - Strict-Clean VLM - Postcondition Success: 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
1Grok 4.3 (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)42.9
2Grok 4.6 (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)42.5
3Amazon Nova Pro (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)40.3
4Qwen3-VL-8B (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)39.4
5Gemma 3 27B (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)32.5
6Llama 4 Maverick (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)28.3
7Sonar Pro (Seeing What Matters Run: strict-clean;views=12;select=3;effort=unreported)26

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