AgentViSS - Interaction Management: leaderboard

AgentViSS (2026) evaluates visual social intelligence: multimodal agents play roles in 240 multi-party scenarios and must read expressions, posture and emotion from images while pursuing role goals, with each task labeled achieved, partial or not achieved by three judge models. This board is the 0 to 100 score for regulating the interaction and reaching visually grounded outcomes, averaged over two observation modes; higher is better.

Metric: Mean of the interaction-regulation and interaction-outcome task scores under both observation modes; normalized task score (0-100), each role-task instance labeled Achieved 2, Partially Achieved 0.5 or Not Achieved 0 by majority vote of three judges (Gemini 3.1 Pro Preview, GPT-5.4, Qwen3.5-27B), over 2,340 role-task instances in 240 multi-party social scenarios with group images and role portraits; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 7 models tracked.

Top models

#ModelScoreOverall rank
1Claude Sonnet 4.671.32#161
2Qwen 3.5 122B A10B61.98#331
3Qwen 3.5 27B60.94#359
4Qwen 3.5 9B55.95#803
5GPT-5.454.89#123
6GLM-4.6V52.81#701

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

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