MMLUBrowse 296

MMLU

Can the model produce useful work in a professional knowledge-work setting?

Version not specifiedExact reported variant
Knowledge Work10 ranked models14 reported values1 reportsHigher is better

Top rankings

One row per model, using its best reported score across effort settings.

10
RankModelBest scoreBest reported setting
1Gemini 3.1 ProGoogle91.0%high effortDeepSeek report1 value · 1 reportApr 26, 2026 · source
2Claude Opus 4.6Anthropic89.1%max effortDeepSeek report1 value · 1 reportApr 26, 2026 · source
3DeepSeek V4 ProDeepSeek87.5%max effortDeepSeek report3 values · 1 reportApr 26, 2026 · source
4GPT-5.4OpenAI87.5%xhigh effortDeepSeek report1 value · 1 reportApr 26, 2026 · source
5Kimi K2.6Moonshot AI87.1%Reported configurationDeepSeek report1 value · 1 reportApr 26, 2026 · source
6DeepSeek-V4-FlashDeepSeek86.4%high effortDeepSeek report3 values · 1 reportApr 26, 2026 · source
7GLM-5.1Z.ai86.0%Reported configurationDeepSeek report1 value · 1 reportApr 26, 2026 · source
8DeepSeek-V4-Pro-BaseDeepSeek73.5%Reported configurationDeepSeek report1 value · 1 reportApr 26, 2026 · source
9DeepSeek-V4-Flash-BaseDeepSeek68.3%Reported configurationDeepSeek report1 value · 1 reportApr 26, 2026 · source
10DeepSeek-V3.2-BaseDeepSeek65.5%Reported configurationDeepSeek report1 value · 1 reportApr 26, 2026 · source

Effort curve

Every sourced cost-linked effort value for this exact version. Lines connect complete sweeps only.

0
No cost-linked effort sweep for this version.
Definition and comparison boundarypublic methodology

Can the model produce useful work in a professional knowledge-work setting?

Professional analysis, document, finance, office, or domain-specific tasks. Higher is better. The value is the percentage reported in this lab's table.

Harness, tools, prompts, attempt count, and benchmark version can materially change the result. Compare within one reporting context.

Base and mode tables are 5-shot EM; frontier comparison preserves the source's named effort settings.

Method / source