VSysBench - Constraint Satisfaction: leaderboard

VSysBench (2026) pairs MM-Vet v2 image questions with system messages that impose a constraint, from output format and persona to vision-grounded rules, and in half of the cases adds a user message that tries to override it; a GPT-5-mini judge scores the answer and the compliance. Score is the share of responses that satisfy the system constraint, over both halves, in percent; higher is better.

Metric: Constraint satisfaction rate (%; share of responses whose judged constraint score reaches 0.8, both halves; VSysBench: 2,258 verified MM-Vet v2 image questions, each under a system-message constraint from 22 sub-categories in 5 categories, once with an aligned and once with a conflicting user message (4,516 instances); default inference settings; GPT-5-mini judge at temperature 0). Source: arxiv.org. Saturation forecast: Around February 2027. 16 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.483.4#123
2Claude Opus 4.777.2#79
3GPT-5.4 Mini71.9#389
4Claude Sonnet 4.669.7#161
5GPT-5.4 Nano63.2#635
6Claude Haiku 4.559.1#568
7GPT-4o41.4#741
8Phi-4 Multimodal Instruct19#3882

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=vsysbench-constraint-satisfaction · How It Works · Data refreshed daily, snapshot 2026-11-13.