Deployment · 4 min read
Deployment is a system problem, not a conversion step
Why a model that works in the lab can still fail on the device that has to ship it.
The model is only the beginning
A trained model is not yet a field-ready system. Its runtime, memory budget, operators, target silicon and surrounding application all determine whether it can serve a real workload.
That is why a deployment cannot be reduced to exporting a checkpoint. The meaningful unit of work is the complete path from model and constraints to a package that is ready to run.
The target changes the answer
A decision that is reasonable on a workstation may be wrong on an embedded GPU, NPU or CPU. Hardware-aware deployment requires testing the exact model-runtime-device combination that will be used in production.