MMLU: Computer Science (subcategory)

The computer science subcategory of MMLU: a rollup of four subjects, used by publishers that report MMLU at a coarser grain than all 57 subjects.

unassessed

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Categoryknowledge
Subcategorycomputer science
Page statusactive
Metricaccuracy
Directionhigher_is_better
Unit%
Dataset size412
Dataset licenceMIT
PublisherUC Berkeley (original); Center for AI Safety (current host)

What it measures

This id does not correspond to a single dataset config in the Hugging Face mirror of MMLU. It corresponds to the "computer science" subcategory the benchmark's authors define in the repository's categories.py, which pools four subjects: College Computer Science (algorithms and computability at undergraduate level), High School Computer Science (introductory programming concepts), Computer Security (cryptography and systems security) and Machine Learning. Some publishers report MMLU broken down by this kind of subcategory rather than by all 57 individual subjects; this id captures scores reported at that grain.

Task format

Four-option multiple-choice questions pooled from four underlying MMLU subjects, graded on the single correct labelled option. How a given publisher averages the four subjects into one number -- an unweighted mean of per-subject accuracy, or a single accuracy over the pooled question set -- is not documented and not established here.

Models reporting this benchmark

These figures come from the model cards, which carry one collection date per card and no per-score attribution. They are shown as reported, not as verified evidence.
ModelProviderScoreCard as of
Claude Opus 4Anthropic88.82026-04
Claude Opus 4.6Anthropic88.82026-04
GPT-4.1OpenAI88.22026-04
Gemini 2.5 ProGoogle DeepMind87.82026-04
GPT-4oOpenAI87.52026-04
GPT-4o (2024-05-13)OpenAI87.52026-04
GPT-4o (2024-08-06)OpenAI87.52026-04
GPT-4o (2024-11-20)OpenAI87.52026-04
GPT-4o miniOpenAI87.52026-04
Claude Sonnet 4Anthropic86.22026-04
Claude Sonnet 4.5Anthropic86.22026-04
Claude Sonnet 4.5 (latest)Anthropic86.22026-04
DeepSeek R1DeepSeek85.52026-04
DeepSeek R1 0528DeepSeek85.52026-04
DeepSeek R1 0528 NVFP4 v2NVIDIA85.52026-04
DeepSeek R1 0528 Qwen3 8BDeepSeek85.52026-04
DeepSeek R1 Distill Llama 70BDeepSeek85.52026-04
DeepSeek R1 Distill Llama 8BDeepSeek85.52026-04
DeepSeek R1 Distill Qwen 1.5BDeepSeek85.52026-04
DeepSeek R1 Distill Qwen 14BDeepSeek85.52026-04
DeepSeek R1 Distill Qwen 32BDeepSeek85.52026-04
DeepSeek R1 Distill Qwen 7BDeepSeek85.52026-04
DeepSeek ReasonerDeepSeek85.52026-04
Qwen 3 235B InstructCerebras84.52026-04
Qwen3 235B-A22BAlibaba / Qwen Team84.52026-04
Gemma 4 31BGoogle DeepMind82.52026-04
gemma 4 31B itGoogle DeepMind82.52026-04
gemma 4 31B it GGUFUnsloth82.52026-04
Gemma 4 31B IT NVFP4NVIDIA82.52026-04
Mistral Large (latest)Mistral AI82.22026-04
Mistral Large 2.1Mistral AI82.22026-04
Mistral Large 3Mistral AI82.22026-04
Gemma 4 26BGoogle DeepMind81.22026-04
Llama 3.3 70B Instruct NVFP4NVIDIA80.52026-04
Llama-3.3-70B-InstructMeta80.52026-04
Llama 3.1 70BMeta79.82026-04
Llama 3.1 70B InstructMeta79.82026-04
phi 4Microsoft78.52026-04
Phi 4 mini instructMicrosoft78.52026-04
Phi 4 multimodal instructMicrosoft78.52026-04

Data

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