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Distillation
Phase 02 · LLM Fundamentalstechnique

Training a small, efficient 'student' model to copy the outputs and performance of a massive 'teacher' model.

Why it exists

Large frontier models (like GPT-4) are slow and expensive. Distilled student models deliver 80-90% performance at a fraction of latency and cost.

How it works

The student model is trained on completions and logit distributions generated by the teacher model across thousands of representative prompts.

Where you'll use this