DEEP EXPLANATION

What Is Knowledge Distillation for LLMs? (ANSWERED)

Model BasedLLMsMedium12 min read

LLM interview topic on distillation — teacher/student training, latency/cost wins, and quality regression risks.

TL;DR — Quick Answer

Knowledge distillation trains a smaller student model to mimic a larger teacher's outputs (logits, sequences, or preferences), cutting latency and cost while retaining much capability. Use it when you need on-device or high-QPS inference and can accept some quality loss; validate with task-specific evals, not just perplexity.

The Interview Question

Explain knowledge distillation for large language models. When would you distill a large teacher into a smaller student for production, and what quality risks should you expect?

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