# Knn versus match scores

**URL:** <https://discuss.elastic.co/t/knn-versus-match-scores/344386>\
**Category:** Elasticsearch\
**Tags:** vector-search\
**Created:** [October 4, 2023, 12:22pm UTC](https://discuss.elastic.co/t/knn-versus-match-scores/344386 "2023-10-04T12:22:13Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![sbruinsje](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/sbruinsje/32/108568_2.png) [@sbruinsje](https://discuss.elastic.co/u/sbruinsje)\
**Post date:** [October 4, 2023, 12:22pm UTC](https://discuss.elastic.co/t/knn-versus-match-scores/344386/1 "2023-10-04T12:22:13Z")

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When doing a hybrid search using a `query` and a `knn` clause using the \_search api, the combined document score is the sum of both scores. What I am unable to find in the docs is how the knn and match scores relate? Are they comparable?

As an extreme example. Lets say a good score for the "match" part is a score of `5` and a good score for the "knn" part is `0.5`, then the sum of both doesn't add much value. Its overwhelmingly just the "match" part that determines the overal score.

Ofcourse you can boost the knn score to make it a more significant factor of the scores, but are there any guidelines on how competitive knn scores are compared to a standard text matching query and how much you will need to boost them (or the other way around)?

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**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [November 1, 2023, 12:22pm UTC](https://discuss.elastic.co/t/knn-versus-match-scores/344386/2 "2023-11-01T12:22:25Z")

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