There is no trustworthy current leaderboard, so the most recent reliable figure is already months old.
HumanEval
HumanEval checks whether a model can write a short, correct Python function from a plain-English description, graded by whether the code passes a set of unit tests.
From 2021 it was the field's default coding test, until models got so good at it that it stopped telling anyone apart.
The model gets a function signature and a docstring (for example, 'return the list of prime numbers below n') and must write the body so it passes the hidden unit tests. The 164 problems are mostly short, self-contained, and easy by today's standards.
HumanEval is worth knowing precisely because it is over: it was the benchmark that defined AI coding progress for years, and watching it die of success is the clearest example of benchmark saturation. A model scoring below 70 percent here is a red flag, but above 95 percent the number tells you almost nothing, because nearly every model clears it and the test was thoroughly memorized.
Pass@1, the share of problems where the model's first attempt passes all unit tests. OpenAI created it but maintains no leaderboard; the closest independent tracker is EvalPlus, which checks the stricter HumanEval+ variant.
The original 2021 baseline (OpenAI's Codex) was 28.8 percent. By 2025 nearly every frontier model clears 90 percent and many reach 95 to 97 percent, so a one or two point difference is statistical noise, not skill.
There is no trustworthy current leaderboard, which is why this panel shows a dated anchor. HumanEval is saturated and effectively retired: its 164 problems have been public since 2021 and appear in essentially every code-training corpus (the median problem shows up over 9,000 times on GitHub), so high scores partly reflect memorization. The test is also narrow, mostly easy single-function problems with few unit tests, so it misses real engineering. The 2026 numbers floating around aggregators are vendor self-reported; evaluators have moved to SWE-bench and LiveCodeBench.
The benchmark creates the need to know. The catalog explains the ideas behind it:
No reliable current leaderboard. The most cited figure is a dated anchor:
EvalPlus board (last updated DEC 2024, independently evaluated): o1 Preview and o1 Mini tied at the top with 96.3% HumanEval Pass@1 (89.0% on the stricter HumanEval+). No 2025 or 2026 model appears on the board; circulating newer figures are all vendor self-reported.