Model
92d agoNew LLMs Slash Long-Context Costs
KV sharing and compressed attention now drive efficiency in models like Gemma 4 and DeepSeek V4. These architectural shifts reduce the memory overhead required for massive context windows. Developers gain faster inference speeds and lower VRAM requirements.
The Signal
This trend makes processing million-token documents viable for smaller, open-weight deployments.