KV sharing and compressed attention mechanisms now drive efficiency in models like Gemma 4 and DeepSeek V4. These techniques reduce the memory overhead required for massive context windows. By optimizing how tokens are cached, developers can run deeper conversations on cheaper hardware. This shift makes long-form document analysis computationally viable for smaller deployments.