Verified65% confidenceFactExact time
Large model inference is divided into two phases, Prefill and Decode; Prefill is a major component of Time to First Token (TTFT), while Decode corresponds to Time Per Output Token (TPOT).
3
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65%
Confidence
Long-term
Relevance
9/11/2026
First Seen
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Related Claims
UnverifiedTTFT (time to first token) refers to the latency from when a request is issued to when the model generates the first output token, and is mainly determined by the prefill stage.78% similarVerifiedLLM 推理分为预填充阶段（Prefill，计算密集型）和解码阶段（Decode，内存带宽密集型）两个阶段76% similarUnverifiedThe prefill stage of LLM inference processes all input tokens in parallel and generates the initial KV Cache; it is a compute-intensive operation and the direct determinant of TTFT.75% similarUnverifiedConstrained Decoding forces the model to sample only from a predefined set of tokens at inference time, achieving latency with near-zero additional overhead.71% similarUnverifiedThe decode phase of large language model inference generates only one token at a time and is a memory-bandwidth-bound operation, because generating each token requires loading the entire model weights from memory once.70% similar
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