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
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-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.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.DAPO-Math-17kNemotron-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.MathInstruct
🦣 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.MathVision
Measuring Multimodal Mathematical Reasoning with the MATH-Vision Dataset
[💻 Github] [🌐 Homepage] [📊 Main Leaderboard ] [📊 Open Source Leaderboard ] [🌿 Wild Leaderboard ] [🔍 Visualization] [📖 Paper]
🌿 NEW: MATH-Vision-Wild
MATH-Vision-Wild is a photographic, real-world variant of MATH-Vision. The same testmini problems are physically captured on printed paper, iPads, laptops, and projectors under varying lighting and angles — the conditions VLMs actually… See the full description on the dataset page: https://huggingface.co/datasets/MathLLMs/MathVision.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.AutoMathText🎉 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.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.Big-Math-RL-Verified
Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
Big-Math is the largest open-source dataset of high-quality mathematical problems, curated specifically for reinforcement learning (RL) training in language models. With over 250,000 rigorously filtered and verified problems, Big-Math bridges the gap between quality and quantity, establishing a robust foundation for advancing reasoning in LLMs.
Request Early Access to Private… See the full description on the dataset page: https://huggingface.co/datasets/SynthLabsAI/Big-Math-RL-Verified.Nemotron-SFT-Math-v4
Nemotron-SFT-Math-v4
Dataset Description:
Nemotron-SFT-Math-v4 is a large-scale mathematical reasoning dataset containing model-generated reasoning trajectories. Solutions in this version are generated using DeepSeek-V4-Pro on High inference mode.
The problems in this dataset are sourced from nvidia/Nemotron-Math-v2, which contains high-quality mathematical problems derived from the Art of Problem Solving (AoPS) community and Math StackExchange/MathOverflow… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-SFT-Math-v4.Nemotron-Math-Proofs-v3-SFT
Nemotron-Math-Proofs-v3-SFT
Dataset Description:
Nemotron-Math-Proofs-v3-SFT is a long-form mathematical reasoning dataset containing proof-generation, proof-refinement, verification, and meta-verification traces. The release contains 414,890 samples representing 15,818 unique problems after quality filtering.
The source pool contains 15,879 hard proof problems selected from the AoPS subset of nvidia/Nemotron-Math-Proofs-v1. Responses are generated using… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Math-Proofs-v3-SFT.formal-math-autoformalization
Formal Math Autoformalization Dataset
A growing, CC0 public-domain corpus of ⟨natural-language statement ↔ Lean 4 statement + proof⟩ pairs, contributed through the Agentic Commons network.
Why this is scarce data. Mathlib already contains millions of proven Lean theorems — but as bare Lean, with no paired natural language:
theorem add_comm (a b : ℕ) : a + b = b + a := ... -- no "addition on naturals is commutative" attached
The scarce, valuable artifact is the pairing of the… See the full description on the dataset page: https://huggingface.co/datasets/AgenticCommons/formal-math-autoformalization.open-math-courses
Open Mathematics Courses
Graduate and research-level mathematics lessons with complete proofs, worked examples and solved exercises, one row
per lesson. The lessons are the Markdown sources of the public site https://kokunoyumeto.github.io/open-math-courses-public/ (snapshot commit 4219d3885c68).
3,145 lessons in 140 courses, about 16,927 thousand words.
Fields: course_id, course_title, lesson_title, source_path, page_url, authorship, license, words,
text (Markdown with TeX… See the full description on the dataset page: https://huggingface.co/datasets/KokunoYumeto/open-math-courses.We-Math
Dataset Card for WE-MATH (ACL 2025)
GitHub | Paper | Website
Inspired by human-like mathematical reasoning, we introduce We-Math, the first benchmark specifically designed to explore the problem-solving principles beyond the end-to-end performance. We meticulously collect and categorize 6.5K visual math problems, spanning 67 hierarchical knowledge concepts and 5 layers of knowledge granularity.
Citation
If you find the content of this project helpful, please cite our… See the full description on the dataset page: https://huggingface.co/datasets/We-Math/We-Math.MathX-5M
Modotte
Note : This datset is the part of a lineup MathX by Modotte you can get a lots of datasets on this same linup main focus is to provide very high quality datasets for model training
and finetuning
This dataset is curated from high-quality public sources and enhanced with synthetic data from both closed and open-source models. It serves as a strong foundation for instruction-based model tuning and fine-tuning, offering one of the most refined and extensive corpora… See the full description on the dataset page: https://huggingface.co/datasets/Modotte/MathX-5M.open-math-proof-checks
Open Mathematics: arguments, reviews and corrections
Current S6 coverage: 155 whole named source units, 1,011 public messages, 38 full annex comparisons and39 scoped teaching tasks. The complete affine-descent development links the preliminary calculations, three whole proofs, both exercises and actual receiving integrations. Read the proof history and teaching explanation.
Earlier release descriptions below record the scope at the time of each increment. The linked current… See the full description on the dataset page: https://huggingface.co/datasets/KokunoYumeto/open-math-proof-checks.dart-math-hard
🎯 DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
📝 Paper@arXiv | 🤗 Datasets&Models@HF | 🐱 Code@GitHub
🐦 Thread@X(Twitter) | 🐶 中文博客@知乎 | 📊 Leaderboard@PapersWithCode | 📑 BibTeX
[!IMPORTANT]
🔥 Excited to find our DART-Math-DSMath-7B (Prop2Diff) trained on DART-Math-Hard comparable to the AIMO winner NuminaMath-7B on CoT,
but based solely on MATH & GSM8K prompt set, leaving much room to improve!
Besides, our DART method is also fully compatible… See the full description on the dataset page: https://huggingface.co/datasets/hkust-nlp/dart-math-hard.StackMathQA
StackMathQA
StackMathQA: A Curated Collection of 2 Million Mathematical Questions and Answers Sourced from Stack Exchange
StackMathQA is a meticulously curated collection of 2 million mathematical questions and answers, sourced from various Stack Exchange sites. This repository is designed to serve as a comprehensive resource for researchers, educators, and enthusiasts in the field of mathematics and AI research.
Configs
configs:
- config_name: stackmathqa1600k… See the full description on the dataset page: https://huggingface.co/datasets/math-ai/StackMathQA.forum-competition-math-training-pool
Forum competition mathematics training pool
Olympiad and contest mathematics from three public datasets, gathered at pinned revisions and
shipped twice over. sources/ holds each dataset the way its publisher ships it, in its own file
format with its own fields and nothing renamed, 287091 rows across three folders. pool/ holds the
union of those same datasets in one format, one JSON object per line, deduplicated by problem text
and reduced to 282140 rows, every row labelled with… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/forum-competition-math-training-pool.ImgCode-8.6M
MathCoder-VL: Bridging Vision and Code for Enhanced Multimodal Mathematical Reasoning
Repo: https://github.com/mathllm/MathCoder
Paper: https://huggingface.co/papers/2505.10557
Introduction
We introduce MathCoder-VL, a series of open-source large multimodal models (LMMs) specifically tailored for general math problem-solving. We also introduce FigCodifier-8B, an image-to-code model.
Base Model
Ours
Mini-InternVL-Chat-2B-V1-5
MathCoder-VL-2B
InternVL2-8B… See the full description on the dataset page: https://huggingface.co/datasets/MathLLMs/ImgCode-8.6M.olympiad-math-training-pool
Olympiad mathematics training pool
Public olympiad and competition mathematics, four datasets gathered at pinned revisions, shipped
twice over. sources/ holds each dataset the way its publisher ships it, in its own file format
with its own fields and nothing renamed, 229052 rows across four folders. pool/ holds the union
of those same datasets in one format, one JSON object per line, deduplicated by problem text and
reduced to 225822 rows, every row labelled with the dataset it… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/olympiad-math-training-pool.mathmetics-dataset-intmax
Transformer Math Dataset (200,000,000 Samples Sharded)
High-precision synthetic mathematical expression dataset generated for training sequence-to-sequence math Transformers in JAX/Flax.
Dataset Structure
Total Samples: 200,000,000
Shard Format: JSONL sharded files (100,000 samples per shard)
Supported Operations: +, -, *, /, ^, sin, cos, tan, log, ln, exp, sqrt, abs
Expression Depth Range: Depth 4 to 6
Integer Operand Ratio: 80%
Data Fields
Each… See the full description on the dataset page: https://huggingface.co/datasets/saidurga001301/mathmetics-dataset-intmax.competition-math-training-pool
Competition mathematics training pool
Public competition mathematics, six datasets gathered at pinned revisions, shipped twice over.
sources/ holds each dataset the way its publisher ships it, in its own file format with its own
fields and nothing renamed, 1951046 rows across six folders. pool/ holds the union of those
same datasets in one format, one JSON object per line, deduplicated by problem text and reduced
to 1125451 rows, every row labelled with the dataset it came from… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/competition-math-training-pool.dart-math-uniform
🎯 DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
📝 Paper@arXiv | 🤗 Datasets&Models@HF | 🐱 Code@GitHub
🐦 Thread@X(Twitter) | 🐶 中文博客@知乎 | 📊 Leaderboard@PapersWithCode | 📑 BibTeX
Datasets: DART-Math
DART-Math datasets are the state-of-the-art and data-efficientopen-source instruction tuning datasets for mathematical reasoning.
Figure 1: Left: Average accuracy on 6 mathematical benchmarks. We compare with models… See the full description on the dataset page: https://huggingface.co/datasets/hkust-nlp/dart-math-uniform.Math-CoT-44k-Qwen3-32b-n32-16384-with-logprob-and-entropy
Qwen3-32B Math n32 16384 (44k Queries)
This dataset contains multi-sampled rollout traces from Qwen3-32B on around 44k math queries.
For each query, the model is rolled out 32 times with a maximum generation length of 16384 tokens.
Each response is annotated with answer correctness (acc_reward), and includes token-level statistics (action_entropy, action_log_probs) for further analysis and research.
Resources
Paper: Rethinking Generalization in Reasoning SFT: A… See the full description on the dataset page: https://huggingface.co/datasets/jasonrqh/Math-CoT-44k-Qwen3-32b-n32-16384-with-logprob-and-entropy.MM-MathInstruct
MathCoder-VL: Bridging Vision and Code for Enhanced Multimodal Mathematical Reasoning
Repo: https://github.com/mathllm/MathCoder
Paper: https://huggingface.co/papers/2505.10557
Introduction
We introduce MathCoder-VL, a series of open-source large multimodal models (LMMs) specifically tailored for general math problem-solving. We also introduce FigCodifier-8B, an image-to-code model.
Base Model
Ours
Mini-InternVL-Chat-2B-V1-5
MathCoder-VL-2B… See the full description on the dataset page: https://huggingface.co/datasets/MathLLMs/MM-MathInstruct.MathX-20M
Modotte
Note : This datset is the part of a lineup MathX by Modotte you can get a lots of datasets on this same linup main focus is to provide very high quality datasets for model training
and finetuning
This dataset is curated from high-quality public sources and enhanced with synthetic data from both closed and open-source models. It serves as a strong foundation for instruction-based model tuning and fine-tuning, offering one of the most refined and extensive corpora… See the full description on the dataset page: https://huggingface.co/datasets/Modotte/MathX-20M.