Unverified50% confidenceFactExact time
Commonly used evaluation benchmarks for measuring the gap between open-source and closed-source models include HumanEval/SWE-bench for coding ability, MATH and GPQA for reasoning ability, and MMLU for overall performance.
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10/11/2026
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UnverifiedThe industry broadly relies on benchmark tests such as MMLU, HumanEval, GPQA, and SWE-bench to measure model capabilities.78% similarUnverifiedPublic benchmarks (such as MMLU, HumanEval, and HellaSwag) measure model performance on standardized questions, which often diverges greatly from specific business scenarios74% similarVerifiedMainstream large model evaluation benchmarks include MMLU, HumanEval/SWE-bench, MATH, and GPQA73% similarUnverifiedHumanEval and SWE-bench are commonly used to evaluate large model coding capabilities, MMLU and GPQA for comprehensive reasoning, and IFEval for instruction following.71% similarUnverifiedHigh-difficulty benchmarks that have emerged in recent years include GPQA (graduate-level science question answering), SWE-bench (real software engineering tasks), and various agentic evaluations.70% similar
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