---
title: aime_2024
canonical_url: "https://www.modelscope.cn/datasets/AI-ModelScope/AIME_2024"
md_url: "https://www.modelscope.cn/datasets/AI-ModelScope/AIME_2024.md"
repository: AI-ModelScope/AIME_2024
chinese_name: aime_2024
last_updated: 2025-02-18
license: "Apache License 2.0"
storage_size: "41 KB"
downloads: 4832
stars: 2
---

# aime_2024

> AIME_2024 - AI-ModelScope 在 ModelScope 开源的数据集。This dataset contains problems from the American Invitational Mathematics Examination (AIME) 2024. AIME is a prestigious high school mathematics competition known for its challenging mathematical problems.

AI-ModelScope/AIME_2024 是 ModelScope 魔搭社区上的数据集，存储大小 41 KB，采用 Apache License 2.0 许可。

- **Repository**: AI-ModelScope/AIME_2024
- **License**: Apache License 2.0
- **Storage size**: 41 KB
- **Downloads**: 4832
- **Stars**: 2
- **Last updated**: 2025-02-18

Source: https://www.modelscope.cn/datasets/AI-ModelScope/AIME_2024

---

# AIME 2024 Dataset

## Dataset Description

This dataset contains problems from the American Invitational Mathematics Examination (AIME) 2024. AIME is a prestigious high school mathematics competition known for its challenging mathematical problems.

## Dataset Details

- **Format**: JSONL
- **Size**: 30 records
- **Source**: AIME 2024 I & II
- **Language**: English

### Data Fields

Each record contains the following fields:
- `ID`: Problem identifier (e.g., "2024-I-1" represents Problem 1 from 2024 Contest I)
- `Problem`: Problem statement
- `Solution`: Detailed solution process
- `Answer`: Final numerical answer

## Purpose

This dataset is primarily used for:
1. Evaluating Large Language Models' (LLMs) mathematical reasoning capabilities
2. Testing models' problem-solving abilities on complex mathematical problems
3. Researching AI performance on structured mathematical tasks

## Features

- Covers various mathematical domains (geometry, algebra, number theory, etc.)
- Includes detailed solution processes for each problem
- All problems have specific numerical answers
- High difficulty level, suitable for testing advanced reasoning capabilities
- Problems require multi-step reasoning and mathematical insight

## Dataset Structure

The dataset is organized in JSONL format, where each line represents a complete problem with its solution. Example:

```json
{
"ID": "2024-I-1",
"Problem": "Problem statement...",
"Solution": "Detailed solution...",
"Answer": "Numerical answer"
}
```