ARC: AI2 Reasoning Challenge

Reasoning

Dataset of natural, grade-school science multiple-choice questions (authored for human tests).

Contributed By

@jjallaire

Code

src/inspect_evals/arc

Paper

https://arxiv.org/abs/1803.05457

Overview

ARC is a benchmark using natural science questions to evaluate a model’s knowledge and reasoning capabilities. The dataset ships with Easy and Challenge sets.

Usage

Installation

There are two ways of using Inspect Evals, from pypi as a dependency of your own project and as a standalone checked out GitHub repository.

If you are using it from pypi, install the package and its dependencies via:

pip install inspect-evals

If you are using Inspect Evals in its repository, start by installing the necessary dependencies with:

uv sync

Running evaluations

Now you can start evaluating models. For simplicity’s sake, this section assumes you are using Inspect Evals from the standalone repo. If that’s not the case and you are not using uv to manage dependencies in your own project, you can use the same commands with uv run dropped.

uv run inspect eval inspect_evals/arc_easy --model openai/gpt-5-nano
uv run inspect eval inspect_evals/arc_challenge --model openai/gpt-5-nano

To run multiple tasks simulteneously use inspect eval-set:

uv run inspect eval-set inspect_evals/arc_easy inspect_evals/arc_challenge

You can also import tasks as normal Python objects and run them from python:

from inspect_ai import eval, eval_set
from inspect_evals.arc import arc_easy, arc_challenge
eval(arc_easy)
eval_set([arc_easy, arc_challenge], log_dir='logs-run-42')

After running evaluations, you can view their logs using the inspect view command:

uv run inspect view

For VS Code, you can also download Inspect AI extension for viewing logs.

If you don’t want to specify the --model each time you run an evaluation, create a .env configuration file in your working directory that defines the INSPECT_EVAL_MODEL environment variable along with your API key. For example:

INSPECT_EVAL_MODEL=anthropic/claude-opus-4-1-20250805
ANTHROPIC_API_KEY=<anthropic-api-key>

Options

You can control a variety of options from the command line. For example:

uv run inspect eval inspect_evals/arc_easy --limit 10
uv run inspect eval inspect_evals/arc_challenge --max-connections 10
uv run inspect eval inspect_evals/arc_easy --temperature 0.5

See uv run inspect eval --help for all available options.

Dataset

The ARC dataset is a dataset of 7,787 genuine grade-school level, multiple-choice science questions. Here is an example prompt (after being further process by Inspect):

Answer the following multiple choice question. The entire content of your response should be of the following format: ’ANSWER: $LETTER (without quotes) where LETTER is one of A,B,C,D.

An astronomer observes that a planet rotates faster after a meteorite impact. Which is the most likely effect of this increase in rotation?

Planetary density will decrease.

Planetary years will become longer.

Planetary days will become shorter.

Planetary gravity will become stronger.

The model is then tasked to pick the correct choice.

Scoring

A simple accuracy is calculated over the datapoints.