Benchmarks / Knowledge & Science
MMLU-Pro
Harder, reasoning-focused successor to MMLU.
maintainer unknown · 245 observations on record
Versions
1 version
| Version | Tasks |
|---|---|
| MMLU-Pro current mmlu-pro | — |
Current leaderboard
MMLU-Pro · Accuracy · top 25 of 245 systems
| # | System | Accuracy % |
|---|---|---|
| 1 | Claude Fable 5max effort Anthropic | 91.5% |
| 2 | Gemini 3.1 Pro Previewhigh effort Google DeepMind | 91.0% |
| 3 | Gemini 3 Pro Previewhigh effort Google DeepMind | 90.1% |
| 4 | Claude Opus 4.7max effort Anthropic | 89.9% |
| 5 | Gemini 3 Pro Previewhigh effort Google DeepMind | 89.8% |
| 6 | Claude Opus 4.8max effort Anthropic | 89.6% |
| 7 | Gemini 3.5 Flashhigh effort Google DeepMind | 89.5% |
| 8 | Gemini 3 Pro Previewlow effort Google DeepMind | 89.5% |
| 9 | Claude Opus 4.5thinking Anthropic | 89.5% |
| 10 | Qwen3 7 Max Alibaba (Qwen) | 89.3% |
| 11 | Grok 4.5high effort xAI | 89.2% |
| 12 | Claude Opus 4.6max effort Anthropic | 89.1% |
| 13 | GPT 5.6 Solmax effort OpenAI | 89.1% |
| 14 | Gemini 3 Flash Previewthinking Google DeepMind | 89.0% |
| 15 | Claude Opus 4.5no reasoning Anthropic | 88.9% |
| 16 | Muse Spark 1.1xhigh effort Meta AI | 88.7% |
| 17 | Gemini 3 Flash Previewhigh effort Google DeepMind | 88.6% |
| 18 | Gemini 3 Flash Previewno reasoning Google DeepMind | 88.2% |
| 19 | GPT 5.5 (2026-04-22)xhigh effort OpenAI | 88.1% |
| 20 | Claude Opus 4.1 20250805thinking Anthropic | 87.9% |
| 21 | Qwen3 6 Plus Alibaba | 87.7% |
| 22 | Kimi K2 6 Moonshot AI | 87.6% |
| 23 | Claude Sonnet 5max effort Anthropic | 87.5% |
| 24 | Minimax M2 1 MiniMax | 87.5% |
| 25 | Claude 4.5 Sonnetthinking Anthropic | 87.5% |
One row per evaluated system — reasoning-effort variants rank separately.
Source agreement
where evaluating organizations agree — and don't
MMLU-ProArtificial Analysis vs Vals AI
overlap 27 systemsrank correlation 0.96mean |Δ| 2.17max |Δ| 14.67
most contested: Magistral Small 2509 (+14.67) · Magistral Medium 2509 (+12.84) · GPT OSS 20B (+3.16)
Possible reasons: run setting 'implementation' differs (artificial-analysis vs vals-ai).
