Unverified50% confidenceFactExact time
The pass@k metric is widely adopted on standard benchmarks such as HumanEval and MBPP.
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50%
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Long-term
Relevance
9/22/2026
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Unverified当前主流基准测试体系如HumanEval、MBPP等代码评估集往往关注平均性能，对分布式的场景特定退化现象敏感度不足70% similarUnverifiedGLM-5.2 performs prominently on mainstream coding benchmarks such as HumanEval and MBPP.67% similarUnverifiedThe pass@k metric measures the probability that, when the model generates k candidate code snippets, at least one of them passes all test cases.65% similarUnverifiedTo evaluate whether a local model is suitable for your needs, you can refer to standardized benchmark scores such as MMLU and HumanEval.64% similarUnverifiedThe pass@1 metric was originally borrowed from the code generation evaluation domain (such as the HumanEval benchmark) to measure the probability of a model generating correct code on the first attempt.64% similar
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