Unverified50% confidenceFactExact time
The prefill stage is highly parallel with large throughput but latency that grows with context length, while the decode stage generates tokens auto-regressively and its speed is limited by memory bandwidth.
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50%
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Long-term
Relevance
10/11/2026
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Related Claims
UnverifiedIn the inference pipeline, the Prefill stage is compute-intensive and time-consuming, while the Decode stage performs token-by-token autoregressive generation and is sensitive to latency.77% similarVerifiedThe prefill stage of Transformer inference is primarily bottlenecked by compute (FLOPS), while the decode stage is primarily bottlenecked by memory bandwidth.75% similarUnverified传统混合部署中Prefill阶段的大批量计算会阻塞Decode阶段的token生成，导致TTFT波动剧烈72% similarUnverifiedIn the Prefill phase, performance differences among the three model types are within the noise range; in the Decode phase, performance is actually about 1.4% faster after applying the patch.71% similar
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