711
Dictionary

Model Distillation

Training a small model to mimic a large one.

1 min readupdated 2026-07-04

/ quick answer

Distillation uses a big model to label a dataset, then trains a small model on those labels. Produces fast, cheap models that keep 80-95% of teacher quality on the target task. Training a small model to mimic a large one.

Training a small model to mimic a large one. Distillation uses a big model to label a dataset, then trains a small model on those labels. Produces fast, cheap models that keep 80-95% of teacher quality on the target task. In practice: Distill GPT-4 outputs on your support tickets into a fine-tuned Llama-3-8B — 20x cheaper, near-parity.
Definition
Distillation uses a big model to label a dataset, then trains a small model on those labels. Produces fast, cheap models that keep 80-95% of teacher quality on the target task.
Example
Distill GPT-4 outputs on your support tickets into a fine-tuned Llama-3-8B — 20x cheaper, near-parity.

/ frequently asked

What is Model Distillation?

Distillation uses a big model to label a dataset, then trains a small model on those labels. Produces fast, cheap models that keep 80-95% of teacher quality on the target task.

What is an example of Model Distillation?

Distill GPT-4 outputs on your support tickets into a fine-tuned Llama-3-8B — 20x cheaper, near-parity.

Why does Model Distillation matter?

Training a small model to mimic a large one.

What should I learn after Model Distillation?

Open the related workflows and prompts further down this page: they show how this idea is applied in a real task, step by step.

/ topics#ai#training

/ continue exploring

Related concepts

The vocabulary this page depends on.

  • →Fine-Tuning

    Continuing to train a base model on your own examples to specialize its behavior.

  • →RLHF

    Reinforcement learning from human feedback, the alignment technique behind ChatGPT.

  • →DPO (Direct Preference Optimization)

    A simpler alternative to RLHF that skips the reward model.

  • →LoRA

    Low-Rank Adaptation: cheap fine-tuning that patches only small matrices.

all dictionary →

Related workflows

Turn this into a repeatable process.

all workflows →

Related tool stacks

The tools that run it in production.

all tool stacks →

Comparisons & alternatives

Pick between the options.

all comparisons →