HumanEval vs BigCodeBench
HumanEval or BigCodeBench? HumanEval is a short 2021 set of single Python functions written from docstrings, useful as a cheap sanity check. BigCodeBench has 1,140 practical tasks that call functions from 139 libraries, with an average of 5.6 tests per task.
| HumanEval | BigCodeBench | |
|---|---|---|
| Made by | OpenAI | BigCode project |
| Task | Write one short function from a docstring | Practical tasks calling many libraries across 7 domains |
| Size | 164 problems | 1,140 tasks; Hard subset of 148 |
| Language | Python | Python |
| Headline result | Codex 28.8% pass@1 in the original paper | Top of 60 LLMs up to 60%, humans 97% |
| Watch out for | Public since 2021; top models have largely mastered it | Results can vary with batch size and version; fix settings |
| License | MIT | Apache-2.0 |
Verdict: when to use which
Use HumanEval if you want a quick baseline comparable with many papers.
Use BigCodeBench if you want tasks closer to everyday library-heavy Python work.
Sources
Other comparisons: SWE-bench vs SWE-bench-Live · HumanEval vs LiveCodeBench · MMLU vs GPQA · AlpacaEval vs MT-Bench (LLM-as-a-judge paper) · MT-Bench (LLM-as-a-judge paper) vs LMArena (Chatbot Arena) · BEIR vs MTEB Leaderboard · WebArena vs OSWorld · HarmBench vs StrongREJECT · GAIA vs BrowseComp