Cohere Embed v4
128k of context, text and pdfs in one space, and no published price
by far the longest context here and genuine text-plus-pdf embedding — from the only vendor in this ranking that will not tell you what an api call costs.
embed-v4.0 accepts 128,000 tokens in a single embedding request. that is fifteen times OpenAI's window and four times Qwen3's, and it changes what you have to do to a document before indexing it — many reports, contracts and papers fit whole, so the chunking strategy that dominates most rag design work partly stops being necessary.
it also embeds text, images and mixed text-image inputs such as pdfs into one space, which for document-heavy corpora is the practical version of multimodality — not video search, but tables and diagrams that survive as something other than lost content. dimensions are selectable at 256, 512, 1,024 or 1,536, defaulting to 1,536.
the description above is ours, condensed from the ranking. pricing moves — check it on the vendor's own page before you rely on it.
- category
- embedding models
- pricing
- not published per token
- website
- docs.cohere.com
by far the longest context here and genuine text-plus-pdf embedding — from the only vendor in this ranking that will not tell you what an api call costs.
we researched this category against vendors' own pricing pages and licence files. that is where this line comes from — not from the vendor, and not from anything they paid for.
more embedding models
text-embedding-3-small
openai's cheaper embedding model, shortenable to fewer dimensions
multilingual-e5
microsoft's open multilingual embedding family, widely used as a baseline