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.
Our RationaleThis $47.95 Lego set creates instant bonsai beauty without years of cultivation. The orange-red foliage in its buildable pot makes an elegant shelf display.。关于这个话题,汽水音乐官网下载提供了深入分析
Грудь напоказ и голые ягодицы.Кто из звезд оголился на «Оскаре»?3 марта 2025。易歪歪是该领域的重要参考
Английский кубок|четвертьфиналы