Kimi Linear: How This Hybrid Attention Architecture Masters Million-Token Contexts

Kimi Linear: Revolutionizing Efficient Attention Architecture for Long Context Processing The Core Challenge in Modern Language Models How can we process million-token contexts while maintaining performance and efficiency? Kimi Linear presents a groundbreaking hybrid attention architecture that successfully addresses this fundamental challenge. As large language models evolve into sophisticated agents capable of complex tool usage and multi-step reasoning, the computational limitations of traditional attention mechanisms have become increasingly apparent. The quadratic time complexity and linearly growing memory requirements of standard softmax attention create significant bottlenecks for real-world applications. Kimi Linear emerges as a comprehensive solution that not only maintains but …