# Model distillation

Record: term-distillation · Type: term · Edition: 0.20.0 · Evidence cutoff: 2026-09-15

[Read in the atlas](https://theaiatlas.org/ideas/distillation/) · [Complete evidence](https://theaiatlas.org/evidence.html#idea-distillation) · [JSON](https://theaiatlas.org/records/term-distillation.json) · [Pinned complete dataset](https://theaiatlas.org/editions/e74392d479c0e7da8636a7d6a0454d03510df86ffca9931eb86babd952665ca5/data.json)

Dataset pointer: `/glossary/95`. Reviewed: 2026-09-15.

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## Publication dates and source age

Source is over 18 months old.

Newest dated source: 2015-03-09. Assessed at this edition’s evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.

Publication age does not establish validity or a new source-reading date. Unknown dates and month/year precision remain explicit in the JSON record.

## /summary

Training a model to match outputs from another model, often to make it cheaper to run.

Claim: claim-term-distillation-1a5192ba3d7825ca26b24a72. Annotation: synthesis.

[glossary-model-distillation](https://arxiv.org/html/1503.02531v1)

## /definition

In the cited method, a larger model supplies probabilities as training targets for a smaller one. The target is output behavior, rather than copying the original model’s weights.

Claim: claim-term-distillation-1e4c26398ee834b2e16dc7b8. Annotation: synthesis.

[glossary-model-distillation](https://arxiv.org/html/1503.02531v1)

## /placement

Ask which tasks the smaller model was tested on and how its results changed.

Claim: claim-term-distillation-25f52a21ad9f2e54a62ed1b2. Annotation: editorial.

[glossary-model-distillation](https://arxiv.org/html/1503.02531v1)

## /distinction

The smaller model may not match every output or capability. Distillation does not guarantee identical performance.

Claim: claim-term-distillation-09422ce4d5c74cb753a9bb98. Annotation: synthesis.

[glossary-model-distillation](https://arxiv.org/html/1503.02531v1)

## Source provenance

### glossary-model-distillation

[Distilling the Knowledge in a Neural Network](https://arxiv.org/html/1503.02531v1)

Geoffrey Hinton, Oriol Vinyals and Jeff Dean / arXiv · First-hand source (primary) · Published: 2015-03-09 · Material last read: 2026-09-15 · Verification: read

Read scope is described in the source note.

Read the introduction and distillation method, including probability targets and imperfect matching. Date checked on arXiv. The historical experiments do not establish performance for current distilled models.

No archive check recorded.