MQ
MODELQUEST
choose the right AI for the quest
Gemini 3.1 Pro · API · High thinking
Evidenceacceptedvendor_reported

MMMU-Pro

Google DeepMind model card — Gemini 3.1 Pro · MMMU-Pro (no tools)

ev_2026_07_gem31pro_mmmu_vendor

Result
Configuration

How it was measured

Exact model
gemini-3.1-pro-preview
Reasoning
high
Agent harness
none
Tool access
none (no tools)
Prompting
vendor MMMU-Pro

Secondary multimodal — vendor MMMU-Pro (no tools). Prefer AA primary.

Caveats

Known limitations

  • Vendor-reported; cannot receive confidence S.
  • Prefer independent AA MMMU-Pro (ev_2026_07_gem31pro_aa_mmmu) as primary.
Weighting

Evidence weight factors

The engine weights each evidence row by these factors (0–1) when fusing scores — higher is more trusted.

relevance0.90
quality0.55
recency0.85
health0.85
comparability0.80
reliability0.70
Benchmark

MMMU-Pro

Multimodal understanding and reasoning: college-level questions that require interpreting images (diagrams, charts, photos, figures) alongside text. MMMU-Pro is a harder, cleaner follow-on to MMMU that reduces shortcut strategies. Primary ModelQuest signal for visual / UI-relevant understanding when formal design rubrics are unavailable.

Benchmark source →