MMMU-Pro Cost Efficiency

X = Artificial Analysis reported cost per task (log). Y = MMMU-Pro score. Each line connects one model's published reasoning-effort levels from the shared configuration dataset; models with one available level remain standalone points. Color = provider.

X-axis

AA cost per task Completion time (est.)

This chart is part of the MMMU-Pro benchmark page, which adds the model table, sources and how to read each view.

More / ExperimentalMMMU-Pro vs Effective CostX = effective cost (log). Y = MMMU-Pro score. Color = provider.Data: Artificial Analysis, ARC Prize, Vals Index v2 Cost per Test +2 moreOpen chart IQ BenchmarksMMMU-Pro Benchmark ScoresEach model's MMMU-Pro score. Color = provider.Data: Artificial Analysis, Artificial Analysis Intelligence Index v4.3.2Open chart More / ExperimentalSWE-Bench Verified Benchmark ScoresHistorical data. Vals archived cohort; retired from default Software Engineering domain. Each model's SWE-Bench Verified score. Color = provider.Data: Vals.ai, LLM StatsOpen chart More / ExperimentalTerminal-Bench 2.0 Benchmark ScoresHistorical data. Superseded by 2.1 and 4.0. Legacy Terminal-Bench 2.0 scores retained for historical comparison. Color = provider.Data: Terminal-BenchOpen chart More / ExperimentalTerminal-Bench 2.1 Benchmark ScoresHistorical data. Superseded in Programmatic Reasoning by Terminal-Bench 4.0. Each model's Terminal-Bench 2.1 pass@1 score, using Artificial Analysis as canonical and Vals.ai as fallback. Color = provider.Data: Artificial Analysis Terminal-Bench v2.1, Vals.ai Terminal-Bench 2.1, Artificial Analysis Intelligence Index v4.3.1Open chart More / ExperimentalTerminal-Bench Hard Benchmark ScoresHistorical data. Historical hard subset; not a Terminal-Bench 4.0 result. Each model's Terminal-Bench Hard score. Color = provider.Data: Artificial AnalysisOpen chart

MMMU-Pro Cost Efficiency

How To Read This Chart

This chart uses derived AI IQ fields and source-backed benchmark data from the public AI IQ dataset.