DeepSeek just made its 75% price cut on V4-Pro permanent. Xiaomi's MiMo slashed V2.5 pricing by up to 99%， effective today. Most coverage frames this as a price war. The more interesting part is the engineering that makes these numbers sustainable.

DeepSeek's V4 paper describes a *hybrid attention architecture* that attacks the core bottleneck of long-context inference： the KV cache. Traditional transformers store key-value pairs for every token in the context. At 1 million tokens， this cache alone can fill an entire GPU's memory. V4 introduces two interleaved attention types.