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.
承租人违反前款规定的，出租人有权解除合同，并有权要求赔偿因此遭受的损失。。新收录的资料是该领域的重要参考
走过二十年，这项工作成为加强和改进代表建议工作的举措，究竟如何“督”“办”？ 一份建议被划上“重点”之后，会发生什么？。业内人士推荐新收录的资料作为进阶阅读
I’m worried that the above quote doesn’t convey how hard Distinction is to read. Yes, it’s long. Yes, it uses outsider-art sentence structure. But it’s not just a dense jungle—it’s a dense jungle inside a labyrinth.，详情可参考新收录的资料