Expired75% confidenceFactTime unknown
On code capability benchmarks such as HumanEval, top large language models have already achieved pass rates exceeding 90%.
5
Sources
75%
Confidence
Medium-term (~90 days)
Relevance
5/31/2026
First Seen
Valid until: 8/29/2026(expired)
Sources
Related Entities
Related Claims
UnverifiedBenchmark overfitting is a core problem in current large model evaluation; some models achieve pass rates above 90% on HumanEval but perform far below expectations in real codebases.77% similarUnverifiedStandardized code benchmark tests such as HumanEval show that top models have already exceeded a pass@1 score of 90%.77% similarUnverifiedThe pass rate of top models in 2025 on the HumanEval benchmark has exceeded 90%.76% similarUnverifiedTop large language models have generally surpassed 90% on MMLU, causing the test's discriminative power to decline.75% similarUnverifiedThe poster noted that cache hit rates in coding tasks are typically as high as 90% or more.73% similar
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