2024年12月20日 星期五 新京报
Alison HoltSocial affairs editor。关于这个话题，新收录的资料提供了深入分析
。新收录的资料对此有专业解读
Why the FT?See why over a million readers pay to read the Financial Times.，这一点在新收录的资料中也有详细论述
While the two models share the same design philosophy , they differ in scale and attention mechanism. Sarvam 30B uses Grouped Query Attention (GQA) to reduce KV-cache memory while maintaining strong performance. Sarvam 105B extends the architecture with greater depth and Multi-head Latent Attention (MLA), a compressed attention formulation that further reduces memory requirements for long-context inference.