Unverified50% confidenceBenchmarkExact time
Commonly used benchmarks for evaluating large language model capabilities include MMLU, HumanEval, MATH, and GPQA.
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9/29/2026
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UnverifiedHumanEval and SWE-bench are commonly used to evaluate large model coding capabilities, MMLU and GPQA for comprehensive reasoning, and IFEval for instruction following.79% similarVerifiedStandard AI benchmarks include MMLU (a comprehensive knowledge test covering 57 subjects), GPQA (graduate-level professional question answering), SWE-bench (real-world software engineering tasks), HumanEval and MBPP (programming ability), and MATH and GSM8K (mathematical reasoning)78% similarUnverifiedTo evaluate whether a local model is suitable for your needs, you can refer to standardized benchmark scores such as MMLU and HumanEval.77% similarVerifiedMMLU evaluates a model's breadth of knowledge across 57 subject areas, HumanEval measures code generation accuracy, GSM8K tests mathematical reasoning, and HELM constructs a comprehensive multi-dimensional evaluation framework.76% similarVerifiedMainstream large model evaluation benchmarks include MMLU, HumanEval/SWE-bench, MATH, and GPQA76% similar
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