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Ask HN: Best Embedding Models?

18 points by devstein · 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.

15 threads
PhilippGille

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

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

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

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

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

  • devsteinOP

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

    • pstorm

      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.

_tgxm

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

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

  • Alifatisk

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

preetsojitra

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

didgeoridoo

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

jayshah5696

embeddings are easy to fine tune. Try modern bert.

mutant

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

best in what?

sovenyr

please check OpenAI embedding models - especially small one

Yogeshshirsath

E5 (Microsoft)

frederickabrah

who knows a tool for rug check in crypto

halvorbuilds

gemma4

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