--- title: 32x Reduced Memory Usage With Binary Quantization description: Binary Quantization is a vector compression algorithm that reduces memory requirements. It works by retaining the sign of each dimension in a vector and... canonical: https://daily.dev/posts/32x-reduced-memory-usage-with-binary-quantization-fmrdm9xxu twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: 32x Reduced Memory Usage With Binary Quantization | daily.dev og:description: Binary Quantization is a vector compression algorithm that reduces memory requirements. It works by retaining the sign of each dimension in a vector and... og:url: https://daily.dev/posts/32x-reduced-memory-usage-with-binary-quantization-fmrdm9xxu og:image: https://api.daily.dev/og/posts/FMRdm9Xxu.png og:image:alt: 32x Reduced Memory Usage With Binary Quantization og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # 32x Reduced Memory Usage With Binary Quantization **[Weaviate](https://daily.dev/sources/weaviate)** · 14 min read · 0 upvotes · 0 comments ## Summary Binary Quantization is a vector compression algorithm that reduces memory requirements. It works by retaining the sign of each dimension in a vector and encoding it as a 1 or 0. Working with Binarized Vectors involves considering the distance between binary vectors and the importance of data distribution. Binary Quantization offers performance improvements in terms of search time, indexing time, and memory footprint. Benchmarking can help determine the optimal compression technique for your data. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: --- Tags: [#weaviate](https://daily.dev/tags/weaviate) [View this post on daily.dev](https://daily.dev/posts/32x-reduced-memory-usage-with-binary-quantization-fmrdm9xxu) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"32x Reduced Memory Usage With Binary Quantization","url":"https://daily.dev/posts/32x-reduced-memory-usage-with-binary-quantization-fmrdm9xxu","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/32x-reduced-memory-usage-with-binary-quantization-fmrdm9xxu"},"datePublished":"2024-04-02T15:51:41.295Z","dateModified":"2024-04-02T15:51:39.601Z","description":"Binary Quantization is a vector compression algorithm that reduces memory requirements. It works by retaining the sign of each dimension in a vector and...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/3e72569cc44e90fb676b16e5b13336c6?_a=AQAEufR","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/3e72569cc44e90fb676b16e5b13336c6?_a=AQAEufR","isAccessibleForFree":true,"articleSection":"Weaviate","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Weaviate","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/07d0692410934a578c4d59e02f7ea685","url":"https://daily.dev/sources/weaviate"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/32x-reduced-memory-usage-with-binary-quantization-fmrdm9xxu","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"weaviate","timeRequired":"PT14M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Weaviate","item":"https://daily.dev/sources/weaviate"},{"@type":"ListItem","position":3,"name":"32x Reduced Memory Usage With Binary Quantization"}]} ```