AllocateWhat is model distillation?
Distillation trains a smaller, cheaper model to imitate a larger one by learning from its outputs. Teams use a frontier model to handle a task, collect its best responses, then distill them into a small open model that serves the same task at a tenth of the cost and latency.
Distillation is the standard graduation path: prove the workflow on a frontier API, then distill onto owned open weights once volume justifies it.
Combined with your own outcome data, distillation plus fine-tuning often beats the original teacher on the specific task, because the student specializes.
Related terms
Allocate is the cloud inference platform for companies that want to train and run their own models.