BehaviorBench - Cross-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 first-move distributions when predicting across games; lower is better.

Metric: Given the first-round moves of each subject in other games, predict the first-round moves in a target game, 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: Around February 2027. 18 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)10.3#94
2DeepSeek V3.212.3#406
3GPT-5.4 (High)14#123 (GPT-5.4)
4Llama 3.3 70B Instruct14.9#1357
5GPT-4.116.3#495
6Claude Haiku 4.517.3#568
7Gemini 3.1 Flash Lite (Preview)17.3#418
8GPT-5.4 Mini (High)18#389 (GPT-5.4 Mini)
9Claude Sonnet 4.619.3#161
10Claude Opus 4.620.1#102
11Qwen 3 4B20.1#2281

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

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