Skip to content
最近更新: 58m ago
Coding 基准测试饱和

HumanEval Code Generation 排行榜

164 Python function-generation problems where models must write correct code from docstrings, tested against unit tests. The original code generation benchmark.

为什么重要: The most recognized coding benchmark, though becoming saturated above 90%. Evidence of training data contamination in some models.

顶级模型

97.5%

GPT-5.4

平均评分

88.9%

共49个模型

已测试模型

49

指标: pass@1

人类基准

-

评分范围: 0%100%

HumanEval Scores - Top 25 Models

Ranked by HumanEval score (%)

LMMarketCap.com

模型排名

All models with a reported HumanEval score, ranked by highest pass@1.

#1
97.5%
#2
97%
#2
97%
#4
96.8%
#5
96.5%
#6
96.3%
#9
95.5%
#10
95.2%
#12
95%
#16
93.8%
#19
92.4%
#19
92.4%
#23
91.5%
#24
90.5%
#25
90.2%
#28
89.5%
#29
89.4%
#30
89%
#31
88.4%
#31
88.4%
#34
87.2%
#35
87.1%
#36
86.6%
#37
84.9%
#39
84.1%
#40
84%
#41
82.6%
#41
82.6%
#43
80.5%
#44
78.6%
#45
76.8%
#46
74.3%
#47
74.1%
#48
69.5%

关于 HumanEval

全名
HumanEval Code Generation
类别
Coding
指标
pass@1 (%)
评分范围
0%100%
人类基准
尚未确定
状态
饱和
Frequently Asked Questions

HumanEval is a standardized evaluation that measures AI model performance on specific tasks. It provides comparable scores across different models, helping developers choose the right model for their needs.

GPT-5.4 currently holds the top score on the HumanEval benchmark. See our full rankings table above for the complete leaderboard with 49 models.

We update benchmark data from multiple sources including HuggingFace open-source model leaderboards and LMArena. Scores are refreshed regularly as new evaluations are published and new models are released.

No. While HumanEval is an important indicator, real-world performance depends on many factors including pricing, latency, context window, and specific task requirements. We recommend using our composite score which weighs multiple benchmarks and practical factors.

相关基准测试

HumanEval Benchmark - AI Code Generation Leaderboard (2026) | LM Market Cap