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Australian-made LLM beats OpenAI and Google at legal retrieval
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25Adrian Lucas Malec
adlumal
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I benchmarked embedding APIs for speed, compared local vs hosted models, and tuned USearch for sub-millisecond retrieval on 143k chunks using only CPU. The post walks through the results, trade-offs, and what I learned about embedding API terms of service.
The main motivation for using USearch is that CPU compute is cheap and easy to scale.
Blog post: https://huggingface.co/blog/adlumal/lightning-fast-vector-search-for-legal-documents
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The Massive Legal Embedding Benchmark (MLEB)
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How I Built Lightning-Fast Vector Search for Legal Documents
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