TECH Signal 506
Developer builds 500k-domain personal search engine for $10 using Gemma 4B and weighted crawling
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Illustration only Photo by Pierre Bamin on Unsplash
A developer built a personal search engine indexing 560,183 homepages for about $10 by using a small local language model to summarize pages and a weighted queue to prioritize personal sites over corporate documentation.
This project demonstrates a viable architecture for personal, non-commercial web indexing at a fraction of typical search engine costs. It highlights how prioritizing outbound links based on page categories can effectively filter out corporate SEO sludge without resorting to hard blocks.
Written by elseif from the cluster below · every claim links back to a sourceThe three things worth knowing
The search engine indexed 560,183 homepages for roughly $10 using an overnight GPU rental and a local Gemma 4B model.
The system avoids storing raw page text, keeping the database under a gigabyte by wiping scratch text after the model generates metadata.
A weighted queue prioritizes links from personal sites like portfolios and zines while deprioritizing corporate and documentation links to improve result quality.
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