• streaming — Sending a model's response token by token as it is generated, so the reader sees text immediately instead of waiting for the whole answer.
• distillation — Training a small, cheap model to imitate a big one's outputs, keeping much of the capability at a fraction of the cost.

Multi-teacher distillation across heterogeneous GPU clusters, plus caching and streaming of training data, cut a two-day training run to under five hours while a third-size student kept near-teacher accuracy — a template for teams whose retraining cadence gates iteration.

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