KV sharing and compressed attention now drive efficiency in models like Gemma 4 and DeepSeek V4. These techniques reduce the memory overhead required for massive context windows. This shift lowers inference costs for developers. Practitioners can now deploy long-context applications without requiring prohibitive amounts of VRAM for key-value caches.