Model
104d agoNew LLMs Slash Long-Context Memory Costs
KV sharing and compressed attention now drive efficiency in Gemma 4 and DeepSeek V4. These architectural shifts reduce the memory overhead required for massive context windows. By optimizing how models store key-value pairs, developers can run longer sequences on cheaper hardware.
The Signal
This move makes high-token processing viable for smaller, open-weight deployments.