---
title: "MATH"
source: EleutherAI LM Evaluation Harness
source_url: https://github.com/EleutherAI/lm-evaluation-harness
licence: MIT
domain: agentic-ai
subdomain: eleutherai-lm-eval
date_added: 2026-04-25
---

# MATH

## Paper
Measuring Mathematical Problem Solving With the MATH Dataset
https://arxiv.org/abs/2103.03874

Many intellectual endeavors require mathematical problem solving, but this skill remains beyond the capabilities of computers. To measure this ability in machine learning models, we introduce MATH, a new dataset of 12,500 challenging competition mathematics problems. Each problem in MATH has a full step-by-step solution which can be used to teach models to generate answer derivations and explanations.

NOTE: This task corresponds to the MATH (`hendrycks_math`) implementation at https://github.com/EleutherAI/lm-evaluation-harness/tree/master . For the variant which uses the custom 4-shot prompt in the Minerva paper (https://arxiv.org/abs/2206.14858), and SymPy answer checking as done by Minerva, see `lm_eval/tasks/minerva_math`.

Homepage: https://github.com/hendrycks/math


## Citation
```
@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}
}
```

### Groups and Tasks

#### Groups

- `hendrycks_math`: the MATH benchmark from Hendrycks et al. 0- or few-shot.

#### Tasks

- `hendrycks_math_algebra`
- `hendrycks_math_counting_and_prob`
- `hendrycks_math_geometry`
- `hendrycks_math_intermediate_algebra`
- `hendrycks_math_num_theory`
- `hendrycks_math_prealgebra`
- `hendrycks_math_precalc`
- `hendrycks_math500`

### Checklist

The checklist is the following:

For adding novel benchmarks/datasets to the library:
* [x] Is the task an existing benchmark in the literature?
  * [x] Have you referenced the original paper that introduced the task?
  * [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?
    * Answer extraction code is taken from the original MATH benchmark paper's repository.


If other tasks on this dataset are already supported:
* [x] Is the "Main" variant of this task clearly denoted?
* [x] Have you provided a short sentence in a README on what each new variant adds / evaluates?
* [x] Have you noted which, if any, published evaluation setups are matched by this variant?
