Model8d ago
Open-Weight Models Slash Long-Context 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. Developers can now deploy longer sequences without linear hardware costs. This trend prioritizes inference throughput over raw parameter counts to make long-context LLMs commercially viable.