Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention

Jul 11, 2026

A new article by Sebastian Raschka discusses recent advances in large language model (LLM) architectures, such as KV sharing, multi-head compression (mHC), and compressed attention. These methods are being explored in models like Gemma 4 and DeepSeek V4 to help reduce the computational costs associated with processing long contexts.

Why it matters: These innovations could make large language models more efficient and accessible by lowering the computational requirements for handling long sequences.

Full story at: Ahead of AI — Sebastian Raschka ↗