Analyzing Memory Optimization Trade-offs in Kimi's Delta Attention
AccBalanced · x · 2026-07-19
The post analyzes Kimi's Delta Attention mechanism. While it retains a state similar to KV cache, its memory footprint does not grow with context length, offering a solution to the memory bottleneck of long-context large models.
However, this design comes with trade-offs: although the constant state space saves some memory, Kimi's enormous overall parameter count still imposes high memory demands.
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