Counterexample from
@nvidia's own supply chain:
They post-trained the smallest model, Nemotron 3.5 Lightning, and it outperformed Nemotron 3 Ultra on predictive correctness “by a large gap.”
Retraining on 1 GPU, a couple of hours.
Nemo + Palantir Ontology + Autopilot, running on-prem because the data is sensitive. A governed learning loop beats “just wait for the next general model” when the work is operational, private, and continuous.