[softwaredoug]

You can do pretty fast (single digit ms) cosine similarity on 1m vectors with numpy on the CPU. And there are small embedded databases like RocksDB with HNSW indices that work well beyond that. Especially staying at like 256 dims. Quantization can shrink even further.

Also locally you’re QPS is very low as you’re the only searcher.

So with enough RAM, and small enough dataset, it should be fine.

[MutedEstate45]

Thanks for your suggestions, especially RocksDB! I’m gonna play around with it today. Do you have any ideas related to use cases? I was thinking something like dynamic RAG for transformers.js