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Layers / Model / Foundation / Embedding models

Embedding models

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Models whose output is a vector rather than a reply — text, image and code embeddings, and rerankers. Where those vectors are stored is a vector database.

NOINDEX

This category is below the depth bar — it holds 8 listings where we would want 12 before trusting a shortlist, so it is excluded from search engines and says so here rather than quietly.

8 in this category
SORTED BY STARS

NARROW BY WHAT THIS CATEGORY ASKS

LICENCE · 2 NOT READ

INPUT MODALITIES · 5 NOT READ

PRODUCTUSED BYSTARSDOWNLOADS 30D
MinishFast State-of-the-Art Static Embeddings2,205BbcembeddingNetease Youdao's open-source embedding and reranker models for RAG products.1,880colivaraColivara is a suite of services that allows you to store, search, and retrieve documents based on their visual embedding. ColiVara has state of the art retrieval performance on both text and visual do1,485kubeaiAI Inference Operator for Kubernetes. The easiest way to serve ML models in production. Supports VLMs, LLMs, embeddings, and speech-to-text.1,258Ggraphrag-local-ollamaLocal models support for Microsoft's graphrag using ollama (llama3, mistral, gemma2 phi3)- LLM & Embedding extraction1,108Curiosity🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and860ai-dial-coreThe main component of AI DIAL, which provides unified API to different chat completion and embedding models, assistants, and applications660cleoraCleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.544

SORTED BY ONE STATED COLUMN · USED BY = LISTED PRODUCTS DEPENDING ON IT, IN THIS DIRECTORY — NOT A POPULARITY FIGURE · NO OVERALL SCORE AND NO RANK COLUMN, BECAUSE BLENDING ADOPTION, STARS AND DOWNLOADS NEEDS WEIGHTS, AND WEIGHTS ARE AN OPINION PRESENTED AS ARITHMETIC

Cite this page

The count and its date sit inside the citation, because “Embedding models” without a date is a claim that quietly goes wrong as the category fills.

infratoapp, “Embedding models — Model / Foundation”, read 28 October 2026. 8 listed products. https://www.infratoapp.com/layers/models/embeddings

No overall score, and no rank column

Blending adoption, stars and downloads needs weights, and weights are an opinion presented as arithmetic — so this table sorts by one stated column at a time and shows which. This view holds no billing column and joins no billing table: a sponsor cannot appear higher, and the signals meter is a row’s own confidence, never a score you can sort on.

Frequently asked

What is in the Embedding models category?
8 products in the Model / Foundation layer of the AI stack. Models whose output is a vector rather than a reply — text, image and code embeddings, and rerankers. Where those vectors are stored is a vector database. Listed members include Minish, bcembedding and colivara. Every fact on each listing carries the page it was read from and the date it was read.
How are Embedding models compared here?
By the 8 attributes this category declares, asked of every member and answered only where a source states it. A product with no answer on record shows a gap rather than a guess, and no blended score is published — weights would be an opinion presented as arithmetic.
Minish or bcembedding?
Both are listed under Embedding models. We publish no verdict between them — we hold no benchmark that would support one. What we do hold is the same attribute sheet for each, side by side with the source behind every value, at /compare/bcembedding-vs-model2vec.
What does a blank mean on a embedding models row?
That nobody has told us, not that the answer is no. A hollow ring is "no answer on record", which is a different state from a recorded no — and the two look different on purpose. A listing with a blank has not failed the question; it has not been read for it.
How often are embedding models figures re-read?
Every value carries the date it was read and a link to the page it came from. Prices move fastest and are re-read most often; an attribute read weeks ago says so rather than presenting itself as current. Anything past 21 days is hidden rather than shown stale.
Is this every embedding model there is?
No. This is 8 we have read and can cite. A directory that claimed completeness would be making a promise it cannot keep, so the page states its own count instead and says when a category is too thin to shortlist from.
Can a vendor pay to rank higher here?
No. Nothing on this page can be bought: a sponsor cannot enter a table, reorder a row or change a mark, and there is no ranked position for sale. How the site is paid for, and the line each source of money does not cross, is set out under money and independence at /our-data#sec5.