KV sharing and compressed attention now power models like Gemma 4 and DeepSeek V4. These architectural shifts reduce the memory overhead required for massive context windows. By optimizing how tokens are cached, developers can run longer prompts on cheaper hardware. This shift makes high-token processing viable for smaller, open-weight deployments.