datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MATH-500
Dataset Card for MATH-500
This dataset contains a subset of 500 problems from the MATH benchmark that OpenAI created in their Let's Verify Step by Step paper. See their GitHub repo for the source file: https://github.com/openai/prm800k/tree/main?tab=readme-ov-file#math-splits
hendrycks_math
Dataset Summary
MATH dataset from https://github.com/hendrycks/math
Citation Information
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks and Collin Burns and Saurav Kadavath and Akul Arora and Steven Basart and Eric Tang and Dawn Song and Jacob Steinhardt},
journal={NeurIPS},
year={2021}
}
OpenR1-Math-220k
OpenR1-Math-220k
Dataset description
OpenR1-Math-220k is a large-scale dataset for mathematical reasoning. It consists of 220k math problems with two to four reasoning traces generated by DeepSeek R1 for problems from NuminaMath 1.5.
The traces were verified using Math Verify for most samples and Llama-3.3-70B-Instruct as a judge for 12% of the samples, and each problem contains at least one reasoning trace with a correct answer.
The dataset consists of two… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/OpenR1-Math-220k.MetaMathQAView the project page:
https://meta-math.github.io/
see our paper at https://arxiv.org/abs/2309.12284
Note
All MetaMathQA data are augmented from the training sets of GSM8K and MATH.
None of the augmented data is from the testing set.
You can check the original_question in meta-math/MetaMathQA, each item is from the GSM8K or MATH train set.
Model Details
MetaMath-Mistral-7B is fully fine-tuned on the MetaMathQA datasets and based on the powerful Mistral-7B model. It is… See the full description on the dataset page: https://huggingface.co/datasets/meta-math/MetaMathQA.aime25
AIME 25
American Invitational Mathematics Examination (AIME) 2025
Citation
If you use the AIME25 dataset in your research, please consider citing it as follows:
@misc{aime25,
title={American Invitational Mathematics Examination (AIME) 2025},
author={Zhang, Yifan and Math-AI, Team},
year={2025},
}
MathNet
Quick Start · Overview · Tasks · Comparison · Dataset Stats · Data Sources · Pipeline · Schema · License · Citation
This is the official MathNet v0. A larger version v1 will be uploaded soon (more countires, problems and richer metadata). Schema is stable but field values may be revised in v1.
Quick start
from datasets import load_dataset
# Default: all problems
ds = load_dataset("ShadenA/MathNet", split="train")
# Or a specific country / competition-body config… See the full description on the dataset page: https://huggingface.co/datasets/ShadenA/MathNet.MATH-lighteval
Dataset Card for Mathematics Aptitude Test of Heuristics (MATH) dataset in lighteval format
Dataset Summary
The Mathematics Aptitude Test of Heuristics (MATH) dataset consists of problems
from mathematics competitions, including the AMC 10, AMC 12, AIME, and more.
Each problem in MATH has a full step-by-step solution, which can be used to teach
models to generate answer derivations and explanations. This version of the dataset
contains appropriate builder configs s.t. it… See the full description on the dataset page: https://huggingface.co/datasets/DigitalLearningGmbH/MATH-lighteval.UltraData-Math
UltraData-Math
🤗 Dataset | 💻 Source Code | 🇨🇳 中文 README
UltraData-Math is a large-scale, high-quality mathematical pre-training dataset totaling 290B+ tokens across three progressive tiers—L1 (170.5B tokens web corpus), L2 (33.7B tokens quality-selected), and L3 (88B tokens multi-format refined)—designed to systematically enhance mathematical reasoning in LLMs. It has been applied to the mathematical pre-training of the MiniCPM Series models.
It was introduced in… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraData-Math.aime_2026
Homepage and repository
Homepage: https://matharena.ai/
Repository: https://github.com/eth-sri/matharena
Dataset Summary
This dataset contains the questions from AIME 2026 used for the MathArena Leaderboard
Data Fields
The dataset contains the following fields:
problem_idx (int64): Problem index within the corresponding MathArena benchmark.
answer (int64): Gold final answer.
problem (string): Problem statement, usually stored as LaTeX source.
Source… See the full description on the dataset page: https://huggingface.co/datasets/MathArena/aime_2026.open-web-math
Keiran Paster*, Marco Dos Santos*, Zhangir Azerbayev, Jimmy Ba
GitHub | ArXiv
| PDF
OpenWebMath is a dataset containing the majority of the high-quality, mathematical text from the internet. It is filtered and extracted from over 200B HTML files on Common Crawl down to a set of 6.3 million documents containing a total of 14.7B tokens. OpenWebMath is intended for use in pretraining and finetuninglarge language models.
You can download the dataset using Hugging Face:
from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/open-web-math/open-web-math.aime_2025
Homepage and repository
Homepage: https://matharena.ai/
Repository: https://github.com/eth-sri/matharena
Dataset Summary
This dataset contains the questions from AIME 2025 used for the MathArena Leaderboard
Data Fields
The dataset contains the following fields:
problem_idx (int64): Problem index within the corresponding MathArena benchmark.
problem (string): Problem statement, usually stored as LaTeX source.
answer (int64): Gold final answer.
problem_type… See the full description on the dataset page: https://huggingface.co/datasets/MathArena/aime_2025.Nemotron-CC-Math-v1
Nemotron-Pre-Training-Dataset-v1 Release
👩💻 Authors: Rabeeh Karimi Mahabadi, Sanjeev Satheesh
📘 Paper: Nemotron-cc-math: A 133 Billion-Token-Scale High Quality Math Pretraining Dataset
📝 Blog: Nemotron-cc-math blog
Data Overview
We’re excited to introduce Nemotron-CC-Math - a large-scale, high-quality math corpus extracted from Common Crawl which was used in nemotron pre-training.
This dataset is built to preserve and surface high-value mathematical and code content… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-CC-Math-v1.math_qaOur dataset is gathered by using a new representation language to annotate over the AQuA-RAT dataset. AQuA-RAT has provided the questions, options, rationale, and the correct options.AutoMathText-2.5
AutoMathText-2.5
🚀 AutoMathText-2.5: A Foundational High-Quality STEM Training Dataset
📊 AutoMathText-2.5 consists of over 2 trillion tokens of high-quality, deduplicated text spanning web content, mathematics, code, reasoning, and bilingual data. This dataset was meticulously curated using a three-tier deduplication pipeline and AI-powered quality assessment to provide superior training data for large language models.
Our dataset combines 50+… See the full description on the dataset page: https://huggingface.co/datasets/math-ai/AutoMathText-2.5.MathVista
Dataset Card for MathVista
Dataset Description
Paper Information
Dataset Examples
Leaderboard
Dataset Usage
Data Downloading
Data Format
Data Visualization
Data Source
Automatic Evaluation
License
Citation
Dataset Description
MathVista is a consolidated Mathematical reasoning benchmark within Visual contexts. It consists of three newly created datasets, IQTest, FunctionQA, and PaperQA, which address the missing visual domains and are tailored to evaluate logical… See the full description on the dataset page: https://huggingface.co/datasets/AI4Math/MathVista.orca-math-word-problems-200k
Dataset Card
This dataset contains ~200K grade school math word problems. All the answers in this dataset is generated using Azure GPT4-Turbo. Please refer to Orca-Math: Unlocking the potential of
SLMs in Grade School Math for details about the dataset construction.
Dataset Sources
Repository: microsoft/orca-math-word-problems-200k
Paper: Orca-Math: Unlocking the potential of
SLMs in Grade School Math
Direct Use
This dataset has been designed to… See the full description on the dataset page: https://huggingface.co/datasets/microsoft/orca-math-word-problems-200k.competition_math
Dataset Card for Mathematics Aptitude Test of Heuristics (MATH) dataset
Dataset Summary
The Mathematics Aptitude Test of Heuristics (MATH) dataset consists of problems
from mathematics competitions, including the AMC 10, AMC 12, AIME, and more.
Each problem in MATH has a full step-by-step solution, which can be used to teach
models to generate answer derivations and explanations.
Supported Tasks and Leaderboards
[More Information Needed]
Languages… See the full description on the dataset page: https://huggingface.co/datasets/qwedsacf/competition_math.aime26
AIME 26
American Invitational Mathematics Examination (AIME) 2026
Citation
If you use the AIME26 dataset in your research, please consider citing it as follows:
@misc{aime26,
title={American Invitational Mathematics Examination (AIME) 2026},
author={Zhang, Yifan and Math-AI, Team},
year={2026},
}
minervamathMathInstruct
🦣 MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning
MathInstruct is a meticulously curated instruction tuning dataset that is lightweight yet generalizable. MathInstruct is compiled from 13 math rationale datasets, six of which are newly curated by this work. It uniquely focuses on the hybrid use of chain-of-thought (CoT) and program-of-thought (PoT) rationales, and ensures extensive coverage of diverse mathematical fields.
Project Page:… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/MathInstruct.Nemotron-Math-v2
Nemotron-Math-v2
This repository contains the dataset accompanying the paper Nemotron-Math: Efficient Long-Context Distillation of Mathematical Reasoning from Multi-Mode Supervision.
Code: NeMo-Skills
Documentation: NeMo-Skills Nemotron-Math-v2 Documentation
Dataset Description
Nemotron-Math-v2 is a large-scale mathematical reasoning dataset containing approximately 347K high-quality mathematical problems and 7M model-generated reasoning trajectories. The dataset… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Math-v2.Math-Reasoning
Math-Reasoning
Dataset Description
Mathematical problem-solving, rewriting, and dialogue data for reasoning-oriented language-model training. This repository is part of the K2 Horizon collection.
The repository is organized into multiple subsets. Every subset has a train split backed by Parquet shards, which supports Dataset Viewer inspection and streaming access.
K2 Horizon Dataset Series
Dataset repository
Focus
Subsets
IFM/TxT360-v2… See the full description on the dataset page: https://huggingface.co/datasets/IFM/Math-Reasoning.hmmt_feb_2025
Homepage and repository
Homepage: https://matharena.ai/
Repository: https://github.com/eth-sri/matharena
Dataset Summary
This dataset contains the questions from HMMT February 2025 used for the MathArena Leaderboard
Data Fields
The dataset contains the following fields:
problem_idx (int64): Problem index within the corresponding MathArena benchmark.
problem (string): Problem statement, usually stored as LaTeX source.
answer (string): Gold final answer.… See the full description on the dataset page: https://huggingface.co/datasets/MathArena/hmmt_feb_2025.DAPO-Math-17kaime24
AIME 24
American Invitational Mathematics Examination (AIME) 2024
Citation
If you use the AIME24 dataset in your research, please consider citing it as follows:
@misc{aime24,
title={American Invitational Mathematics Examination (AIME) 2024},
author={Zhang, Yifan and Math-AI, Team},
year={2024},
}
hmmt_feb_2026
Homepage and repository
Homepage: https://matharena.ai/
Repository: https://github.com/eth-sri/matharena
Dataset Summary
This dataset contains the questions from HMMT February 2026 used for the MathArena Leaderboard
Data Fields
The dataset contains the following fields:
problem_idx (int64): Problem index within the corresponding MathArena benchmark.
answer (string): Gold final answer.
problem_type (list[string]): Problem type/category labels.
problem… See the full description on the dataset page: https://huggingface.co/datasets/MathArena/hmmt_feb_2026.swallow-math-v2
SwallowMath-v2
Resources
📑 arXiv: Read our paper for detailed methodology at arXiv:2505.02881.
🤗 Sister Dataset: Discover SwallowCode2, our companion dataset for code generation.
🧮 What is it?
SwallowMath-v2 is a large-scale mathematical dataset containing 32 billion tokens, developed as the successor to SwallowMath-v1.
Building on the success of v1, this release aims to construct a larger-scale and more permissively licensed corpus to support open and… See the full description on the dataset page: https://huggingface.co/datasets/tokyotech-llm/swallow-math-v2.Openthoughts_math_30k_opsdAutoMathText🎉 This work, introducing the AutoMathText dataset and the AutoDS method, has been accepted to The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025 Findings)! 🎉
AutoMathText
AutoMathText is an extensive and carefully curated dataset encompassing around 200 GB of mathematical texts. It's a compilation sourced from a diverse range of platforms including various websites, arXiv, and GitHub (OpenWebMath, RedPajama, Algebraic Stack). This rich repository… See the full description on the dataset page: https://huggingface.co/datasets/math-ai/AutoMathText.math-500