---
title: "Discussion on \"Embedding model dimensions for image search: what the published evidence shows\" | Hashnode"
description: "Discussion on \"Embedding model dimensions for image search: what the published evidence shows\". Publicly published results suggest that embedding vectors often add cost without meaningfully improving image-search quality, so smaller dimensions are worth evaluating.\n1. Two common assumptions abou"
url: "https://hashnode.com/posts/embedding-model-dimensions-for-image-search-what-the-published-evidence-shows/6ab3277d55c4c2e0b287824c"
---

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# [Embedding model dimensions for image search: what the published evidence shows](https://infocruncher.hashnode.dev/embedding-model-dimensions-for-image-search-what-the-published-evidence-shows?utm_source=hashnode&utm_medium=feed)

Publicly published results suggest that embedding vectors often add cost without meaningfully improving image-search quality, so smaller dimensions are worth evaluating. 1. Two common assumptions abou

Sep 23 · 14 min read · infocruncher.hashnode.dev  
Updated Sep 24  
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-   [#ai-search](https://hashnode.com/tag/ai-search)
-   [#embedding-models](https://hashnode.com/tag/embedding-models)

## Written by

[Dylan Hogg](https://hashnode.com/@dylanhogg)

@dylanhogg · Sydney, Australia

  
[View profile](https://hashnode.com/@dylanhogg)

ML, AI, Maths, Software and the future.

ML Engineer

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