Verified65% confidenceTradeoffExact time
Increasing batch size to improve throughput typically sacrifices per-request latency
3
Sources
65%
Confidence
Long-term
Relevance
9/9/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedPursuing extreme throughput often comes at the cost of per-request latency, as throughput and latency metrics constrain each other.78% similarUnverifiedThe more memory entries there are, the more tokens are carried with each request, and the calling cost and response latency increase accordingly.77% similarUnverifiedRequest hedging introduces additional compute load and theoretically reduces the system's maximum throughput; if hedging is triggered frequently, it often indicates the system is already overloaded and needs to be scaled up.73% similarUnverifiedLong context significantly raises time to first token, because prefill computation grows with input length; hitting the cache can skip most of the prefill and directly improve first-token latency.73% similarVerifiedExcessive upfront thinking incurs increased latency and computational costs, which may not be worthwhile in scenarios that prioritize response speed.73% similar
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