Sarvam 30B supports native tool calling and performs consistently on benchmarks designed to evaluate agentic workflows involving planning, retrieval, and multi-step task execution. On BrowseComp, it achieves 35.5, outperforming several comparable models on web-search-driven tasks. On Tau2 (avg.), it achieves 45.7, indicating reliable performance across extended interactions. SWE-Bench Verified remains challenging across models; Sarvam 30B shows competitive performance within its class. Taken together, these results indicate that the model is well suited for real-world agentic deployments requiring efficient tool use and structured task execution, particularly in production environments where inference efficiency is critical.
还有那些产后妈妈，是馆里最多的。她们的共同点是：刚生完孩子，身体松了，腰疼，腹直肌分离，抱孩子抱得肩膀僵。但来这里的理由，不止这些。
。使用 WeChat 網頁版是该领域的重要参考
It's an unfortunate truth that, once you've written a paper,
НХЛ — регулярный чемпионат
温泉でカラダがととのう？“ホット”な真価に迫る