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传统的西方经典标准软件（如 SAP 或 Blue Yonder 等），在固化标准流程、沉淀海量交易数据（System of Record）方面，有着极其卓越的全球化底蕴；然而，面对N²复杂度下的实时高频干涉，它们并非为“动态全局求解”而生。
。关于这个话题，搜狗输入法提供了深入分析
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Sarvam 30B performs strongly across core language modeling tasks, particularly in mathematics, coding, and knowledge benchmarks. It achieves 97.0 on Math500, matching or exceeding several larger models in its class. On coding benchmarks, it scores 92.1 on HumanEval and 92.7 on MBPP, and 70.0 on LiveCodeBench v6, outperforming many similarly sized models on practical coding tasks. On knowledge benchmarks, it scores 85.1 on MMLU and 80.0 on MMLU Pro, remaining competitive with other leading open models.
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