Tool-augmented MMMU-Pro variant that allows Python assistance during multimodal reasoning.
BenchLM mirrors the published score view for MMMU-Pro w/ Python. GPT-5.4 mini leads the public snapshot at 78% , followed by GPT-5.4 nano (69.5%). BenchLM does not use these results to rank models overall.
GPT-5.4 mini
OpenAI
GPT-5.4 nano
OpenAI
Year
2026
Tasks
Multimodal academic reasoning
Format
Image + text question answering with Python
Difficulty
Frontier multimodal
Useful for measuring multimodal reasoning when the model can combine visual understanding with computation.
Version
MMMU-Pro w/ Python 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
Tool-augmented MMMU-Pro variant that allows Python assistance during multimodal reasoning.
GPT-5.4 mini by OpenAI currently leads with a score of 78% on MMMU-Pro w/ Python.
2 AI models have been evaluated on MMMU-Pro w/ Python on BenchLM.
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