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Ask HN: Best Embedding Models?

18 points by devstein 22 days ago · 19 comments · 1 min read


Hey HN, which embedding models are people using? There has been so much development around foundational LLMs, but haven't seen much news about embedding models.

PhilippGille 21 days ago

Benchmarks only paint part of the picture, but it's still a decent place to start looking into recent models:

https://huggingface.co/spaces/mteb/leaderboard

rapatel0 22 days ago

I've liked qwen and embeddinggemma for local search. Qwen because 32K is enough to basically fit a whole page into the context window and embeddiggemma because it's crazy efficient.

stevenfazzio 21 days ago

Cohere's embed-v4.0 is my daily driver as far as a high performance model is concerned. I do a lot of cluster analysis and data visualization and I like that there's an `input_type="clustering"` mode in addition to the standard `input_type="search"` mode.

For a fast, open, and local model, I've found it hard to beat https://huggingface.co/sentence-transformers/all-MiniLM-L6-v...

emschwartz 21 days ago

I’ve been using MixedBread, which is a pretty old model at this point. Recently, I tried comparing it to some newer models and was disappointed that the results weren’t dramatically and uniformly better.

You probably can’t go wrong if you pick a recent one that scores decently well on benchmarks and is at the right price point (or memory requirement) for whatever you’re trying to do.

pstorm 21 days ago

Just fyi, for RAG/similarity search, adding a reranker was much bigger pay off than switching embedding models.

  • devsteinOP 21 days ago

    What top K do you use for vector search before passing into the reranker?

    • pstorm 21 days ago

      At a minimum, you increase top-k to cast a wider net, then after reranking, take the N you really want. You have to play around with it a bit, but that’s the idea.

sp1982 21 days ago

I am using openai small embedding model with custom compression. It is super cheap. You can read more at https://corvi.careers/blog/vector-search-embedding-compressi...

LogicCraft678 21 days ago

Feels like embeddings are underrated compared to LLM's hype, but they doing great.

  • Alifatisk 21 days ago

    Why do you feel like embeddings are underrated? What is it with embeddings that deserves more attention?

preetsojitra 21 days ago

Meta's Perception Encoder Audio-Visual, its CLIP like but has three modality: Audio, Video and Text

didgeoridoo 21 days ago

I’m partial to jina.ai — they have open models for code and prose, all easily runnable locally.

jayshah5696 21 days ago

embeddings are easy to fine tune. Try modern bert.

mutant 20 days ago

not a single "of what data" or "in what env"

best in what?

sovenyr 21 days ago

please check OpenAI embedding models - especially small one

Yogeshshirsath 21 days ago

E5 (Microsoft)

frederickabrah 21 days ago

who knows a tool for rug check in crypto

halvorbuilds 21 days ago

gemma4

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