Which model leads mmmu_pro_with_python?

Q: Which model leads mmmu_pro_with_python?

Gemini 3.1 Pro tops the board at 85.3

mmmu_pro_with_python Leaderboard — Model Scores

Pro Mode — raw scores, one benchmark under the lensthird-party eval harness

The field · 5 measured

77.385.3

5 models measured, most on the third-party eval harness. Gemini 3.1 Pro tops the board at 85.3.

5 measured·Lifecycle Updated Oct 8, 2026Score basis

#◆Vendor$/M in$/M out

Leader — ignites whiteField — fill cools with scoreIndependently verified only0 of 5Bars show 77.3–85.3 · ◆ solid = first-party or better · outlined = arm's-length

01Gemini 3.1 Pro+1 altGoogle85.3$2.0/M$12.0/M$0.082

02GPT-5.4OpenAI82.1$2.5/M$15.0/M$0.107

03Kimi K2.6Moonshot80.1$0.95/M$4.0/M$0.031

04Kimi K2.5Moonshot77.7$0.45/M$2.3/M$0.017

05Claude Opus 4.6Anthropic77.3$5.0/M$25.0/M$0.194

◆ solid = independently verified · aggregator attested · vendor attributed — outlined = cross-reference · source-attributed. Dimmed ◆ = confidence inferred. “+N alts” = alternate disclosures in the drawer with why-demoted. Prices per million tokens; $/point = input price ÷ score. Every row opens its model dossier.

Verification: 5 models scored · 0 independently verified · 3 vendor cross-reference · 2 vendor-reported · 0 with source disagreement. How these tiers are assigned