A basement Gemma setup turns Reddit opinions into a product finder

A developer says a basement GPU setup helped turn millions of Reddit and Hacker News opinions into a browsable product-recommendation site. trustmebro.reviews returned to Show HN on November 4, offering an alternative to repeatedly searching forum threads for buying advice.

The creator, posting as davidzweig, describes the extraction stack as Gemma 4 26B MoE running through vLLM on pairs of NVLinked NVIDIA 3090 cards. He says the frontend was built with Claude’s coding help. That separates the local model doing extraction from the assistant used to build the interface; this is a web product, not a new Gemma checkpoint.

The public homepage displayed 47,699 products, places and tools and 13,576,547 opinions when reviewed. Those are the site’s claimed corpus totals, not unique customers, independently verified coverage or evidence of overnight growth.

Read the opinion behind the ranking

The site offers category and subreddit browsing, product search and a travel map highlighted by its creator. Its methodology page says it extracts verbatim recommendation excerpts, links them to their sources, resolves mentions to a canonical item and weights them using an author-trust model and time decay.

It also describes a Bayesian consensus intended to keep a handful of mentions from outranking hundreds. Copy-paste campaigns and self-promotion are supposed to be discounted. The homepage’s verification percentage and spam-filter claims have not been audited by AITrending; linking to an original comment does not prove that the commenter bought or tested the product.

For readers choosing an AI assistant, graphics card or ordinary household item, the concrete attraction is being able to inspect the language behind a recommendation rather than receiving only a generated verdict. The corpus and weighting can still reflect the communities sampled and the extraction model’s mistakes.

A fresh presentation of an older project

This is not the site’s first launch. The November 4 post explicitly calls itself a resubmission, and an October 2 Show HN post already described extracting product opinions with Gemma and an eight-3090 machine. The latest post supplies a current public discussion and a more specific model/runtime description, without establishing a new inference benchmark.

The homepage and browsing interface were publicly accessible without signing in during review. The creator also said the project was not currently monetized and invited someone to take it over; neither statement guarantees future pricing or continued operation.