disaggregated-inference-prefill-compute-bound-decode-memory-bound

IN premise — summaries/2026/08/24/wiki-Transformer_deep_learning_architecture-chunk-4.md

Created 2026-08-24T17:11:26+00:00

Disaggregated inference separates the prefill phase (compute-bound, processes the full prompt in parallel) from the decode phase (memory-bound, generates one token at a time) onto different specialized hardware

Summary

When running a language model, the work of chewing through the input prompt and the work of generating the answer one word at a time have very different bottlenecks — one needs raw math speed, the other needs fast memory access. Routing each phase to hardware tuned for its specific weakness lets a serving system get more throughput out of the same dollar of silicon than a one-size-fits-all GPU cluster can.