AI Potluck
Model components / Benchmark / eval datasets

SWE-bench Verified

Princeton NLP / OpenAI

500 human-validated instances drawn from the wider SWE-bench dataset, each pairing a real GitHub issue with a test-verified solution patch and the fail-to-pass and pass-to-pass test lists that grade it. It was curated by OpenAI from the SWE-bench test set to reduce noise in the original 2,294-instance set.

The dataset card declares no license, and the harness repository's README points at a LICENSE.md path that does not exist. Verified 2026-08-13 via the SWE-bench_Verified card, its raw README and the SWE-bench repository LICENSE.

Openness

5 medium confidence
5.0
license
MIT(SWE-bench repository states MIT over its code and data
redistributability
full(downloadable parquet, ungated)
datasheet
yes(dataset card + arXiv:2310.06770)
held-out
no hidden split in Verified itself(the public 500-instance set is fully released
data-source
real GitHub PR/issue pairs

Ungated and downloadable, with full gold patches and tests, a datasheet present, and the license stated. The canonical SWE-bench repository describes itself as "Code and data for the following works" and lists SWE-bench among them; its "Citation & license" section says "MIT license", with the citation block directly beneath headed "For SWE-bench (Verified)". The Hugging Face card for Verified declares no license field, and where a repository license and a distribution-point license differ the repository license governs, so MIT is what applies and this counts as fully open. (Distinct from the broader and hidden SWE-bench variants, which can carry held-out splits.)

Adoption

4 high confidence
4.0

The de-facto standard agentic-coding benchmark: it is cited as the headline coding metric in nearly every frontier model release - GPT-5, Claude Opus, DeepSeek, Qwen and Kimi all report SWE-bench Verified - alongside a live, heavily-submitted leaderboard at swebench.com. Hugging Face records 413,323 downloads in the trailing 30 days across the declared artifacts, which puts it in the 100K-1M band, level 4 on the dataset adoption scale. It is the strongest citation-as-standard signal in this category.

Capability

not assessed

A dataset is not 'capable', so this axis is left unscored. SWE-bench Verified is notably contamination-resistant and discriminating for coding agents, since it runs against real repository state and executable tests, but that quality is noted here rather than turned into a number.

Verified 2026-08-13