textTIGER-Lab/MMLU-Prollm-evalbenchmarkmmluquestion-answeringreasoningmultiple-choiceenglishmit-license
MMLU-Pro: Robust Multi-Task LLM Benchmark (12K Questions)
About this data
12K challenging multi-discipline multiple-choice questions for benchmarking LLM reasoning. MIT-licensed, parquet format, widely used for model evaluation and leaderboards.
Schema
| Name | Type | Description |
|---|---|---|
| question_id | BIGINT | Unique integer identifier for each question in the dataset |
| question | VARCHAR | Question prompt text, may include LaTeX mathematical notation |
| options | VARCHAR[] | Array of up to 10 candidate answer choice strings (A–J) |
| answer | VARCHAR | Correct answer as a single letter (A–J) |
| answer_index | BIGINT | Zero-based integer index of the correct option in the options array |
| cot_content | VARCHAR | Chain-of-thought reasoning trace or explanation (may be empty) |
| category | VARCHAR | Subject discipline: math, physics, chemistry, law, engineering, psychology, health, business, biology, philosophy, economics, history, or computer science |
| src | VARCHAR | Original source or dataset origin (e.g., cot_lib-abstract_algebra, MMLU, TheoremQA, SciBench) |
Sample Data
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# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "MMLU-Pro: Robust Multi-Task LL" })
// Found: b238a99d-d860-4b47-8ec6-9708ef72f5db
get_download_url({ dataset_id: "b238a99d-d860-4b47-8ec6-9708ef72f5db" }) // free — no API key neededVia REST API
# Free dataset — no API key required: curl https://api.databazaar.io/datasets/b238a99d-d860-4b47-8ec6-9708ef72f5db/download-url