Unverified50% confidenceFactExact time
Inference is a continuous, fragmented task that is latency-sensitive and involves massive concurrency, with each request requiring one forward-pass computation.
1
Sources
50%
Confidence
Long-term
Relevance
9/12/2026
First Seen
Sources
Related Entities
Related Claims
Unverified在推理阶段输入内容通过并行化注意力机制一次性处理,而输出内容需自回归逐Token生成,无法并行化,构成大模型推理延迟的根本瓶颈74% similarUnverifiedUnder a linear conversation structure, token consumption is cumulative—every request requires retransmitting the entire history, increasing inference latency and driving up API call costs.72% similarVerifiedIn traditional static batching, all requests must wait for the longest sequence in the batch to finish generating before resources are released, causing completed short requests to idle and wait, wasting computational resources.72% similarUnverified护栏设计的核心权衡是延迟成本——越复杂的检查逻辑,响应时间增加越多72% similarUnverified追求高吞吐与追求低延迟是两个相互制衡的优化方向,扩大批处理规模可提升吞吐但拉长单请求等待时间71% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/916556API
curl https://kongchang.com/api/v1/knowledge/claims/916556MCP
get_claim(id=916556)