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  5. Model Distillation
Inference & Deployment

Model Distillation

Model distillation creates a deployment model by training it to imitate selected behavior of a larger or more capable model.

Ask Melo about this← all terms

Teacher outputs, probabilities, intermediate states, and labeled data can supply the student's targets. The student may be faster or smaller, but the retained behavior depends on its capacity and the coverage of distillation data.

Related terms

Open WeightsClosed WeightsOn-Device InferenceServerless InferenceAmazon BedrockBatching

Where Model Distillation comes up

  • CoreWeave Model Distillation: Train a Cheaper Specialist From Your Own Production Traffic
  • Jensen Huang Calls AI Distillation 'Competition' as Bessent Calls It Theft
  • Anthropic Says New Distillation Defenses Cut Stolen Reasoning Data by 90 to 99 Percent
  • Hugging Face ML Intern: How One Developer Built Six Custom Models for About $103 (and the Prompt Playbook Behind It)