Model distillation

What Model distillation means in practice

Distillation trains a small model to imitate the behaviour of a larger one by minimising the divergence between their output distributions on a shared corpus. The practical effect is a 5–20× reduction in inference cost at a single-digit-percent quality loss on the distilled task. For enterprises, distillation is the path from "we proved this works with a 70B model" to "we can afford to serve this at production volume on an 8B model". MindMap routinely distils a customer's domain-specific 70B prototype into an 8B production model once the eval suite confirms behavioural parity within the customer's acceptance threshold.