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Why Token-Level LLM Routers Spend 95% of Their Time on Cache Bookkeeping

信息来源:DEV Community·

内容摘要

Routing 5% of hard tokens to a 32B model and keeping the rest on a 0.6B model looks great on paper, until standard serving engines spend 95.8% of the step redoing prefix matching. TokenRouter fixes the scheduler and hits up to 64x higher throughput.
内容分类AI 教程与实战
内容层级普通情报
发布时间(北京时间)
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信息来源DEV Community
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