为什么存力决定Token收益？YRCache重构AI推理经济学 - 企业动态 - 焱融科技

This page discusses how storage capacity is becoming crucial in determining token rewards in AI inference systems, shifting the industry's focus from pure computational power to efficiently managing large-scale KV caches. As the demand for long context and multi-agent applications increases, the industry recognizes that SSDs can supplement traditional memory types (HBM, DRAM) due to their larger capacity and lower cost. YRCache, introduced by Yanrong Technology, aims to optimize resource utilization and token production efficiency through a multi-level cache architecture. This evolution marks a strategic shift as industry competition transitions toward storage capabilities and data flow efficiency, addressing challenges such as memory limitations and high operational costs.