Nicholas Liu (@DecagonAI) on speculative decoding in practice.
Lessons from evaluating DFlash and EAGLE: how concurrency, MoE verification costs and structured outputs shape latency, cost and deployment decisions.
Decagon shares lessons on speculative decoding with DFlash and EAGLE
AINicholas Liu of Decagon shares lessons from evaluating DFlash and EAGLE for speculative decoding. The post says concurrency, MoE verification costs and structured outputs shape latency, cost and deployment decisions.
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Original title: Nicholas Liu (@DecagonAI) on speculative decoding in practice.