BehaviorBench - Multi-Round Game Prediction (Distribution): leaderboard

BehaviorBench (University of Michigan, 2026) evaluates foundation models on behavioral science tasks at the individual and population levels, using economic-game records, Big Five personality surveys and research literature. This board is the Wasserstein distance (0-100) between predicted and observed next-move distributions in multi-round games, with choices normalized to 0-100; lower is better.

Metric: Given the game rules and the earlier rounds of each subject, predict the next moves, on MobLab economic-game records of human players (dictator, ultimatum, trust, public goods, bomb risk, beauty contest and push/pull games): Wasserstein distance (0-100) between the model-predicted and the observed human choice distributions, with choices normalized to 0-100 and averaged over games; lower is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 18 models tracked.

Top models

#ModelScoreOverall rank
1GPT-4.16.9#495
2DeepSeek V3.210.1#406
3Claude Sonnet 4.610.6#161
4Claude Opus 4.611.7#102
5Gemini 3.1 Pro (Preview)12.5#94
6Claude Haiku 4.512.5#568
7Qwen 3 4B13.1#2281
8GPT-5.4 (High)15.2#123 (GPT-5.4)
9Llama 3.3 70B Instruct15.3#1357
10GPT-5.4 Mini (High)17.6#389 (GPT-5.4 Mini)
11Gemini 3.1 Flash Lite (Preview)18.6#418

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

Interactive version: theaggregate.ai/benchmark?slug=behaviorbench-multi-round-game-prediction-distribution · How It Works · Data refreshed daily, snapshot 2026-11-13.