Evals

HumanEval Benchmark

HumanEval is OpenAI's evaluation harness for code-generation models, described in its README as "an evaluation harness for the HumanEval problem solving dataset described in the paper 'Evaluating Large Language Models Trained on Code'." Functional correctness is measured by executing model-generated code against unit tests, reported as pass@1, pass@10, and pass@100 by default.

GitHub

SDKs

📦
GitHubRepository
https://github.com/openai/human-eval

Other Resources

🔗
Paper
https://arxiv.org/abs/2107.03374
🔗
Dataset
https://huggingface.co/datasets/openai/openai_humaneval

Work with this as data

Every API here is available over the APIs.io API and to AI agents over MCP.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for apis

7 MCP tools reach this
  • find_apisBrowse and filter every API in the catalog.
  • get_api_artifactsOne API's artifacts, grouped by type.
  • get_openapiThe primary OpenAPI for this API.
  • find_similar_apisAPIs that look like this one.
  • apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
  • resolveTurn a domain, URL or GitHub org into the provider it belongs to.
  • find_cohortsEvery scored population of providers in the catalog.
All 92 tools →

Call it yourself

curl for this page
This API 
curl "https://apis.io/api/v1/apis/humaneval-benchmark"
All apis 
curl "https://apis.io/api/v1/apis?limit=25"

Discovery needs no key. Ratings and market analysis are Pro.

Get an API key

Free tier, no form to fill in. Signing in shares your email address with us — we store it to create your key and to recognise you if you sign in with another provider. See our Privacy Policy and Terms.

GitHub Google LinkedIn

A second provider on the same verified email joins the account you already have.

API entry from apis.yml

apis.yml Raw ↑ 
name: HumanEval Benchmark
description: HumanEval is OpenAI's evaluation harness for code-generation models, described in its README
  as "an evaluation harness for the HumanEval problem solving dataset described in the paper 'Evaluating
  Large Language Models Trained on Code'." Functional correctness is measured by executing model-generated
  code against unit tests, reported as pass@1, pass@10, and pass@100 by default.
humanURL: https://github.com/openai/human-eval
baseURL: https://github.com/openai/human-eval
tags:
- Benchmarks
- Code Generation
- Functional Correctness
- Pass@k
- Reference-Based
tags_raw:
- Benchmark
- Code Generation
- Functional Correctness
- Pass@k
- Reference-Based
properties:
- type: GitHubRepository
  url: https://github.com/openai/human-eval
- type: Paper
  url: https://arxiv.org/abs/2107.03374
- type: Dataset
  url: https://huggingface.co/datasets/openai/openai_humaneval