Model4h ago
Open-Weight Models Cut 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 usage. This trend makes long-document processing viable on consumer-grade hardware without sacrificing significant model performance.