Mistral Embed
a flat price, a tidy api, and almost no published specification
cheaper than OpenAI and easy to adopt if you are already a Mistral customer — from a model that publishes neither its dimensions nor its benchmark scores.
if your stack is already Mistral, this is the frictionless option: same api, same key, same invoice, at $0.10 per million tokens, which undercuts OpenAI's $0.13. the sdk integration is clean and 8k of context is adequate for chunked retrieval. as an incremental decision for an existing customer it is easy to justify.
as a standalone choice it is hard to evaluate, because Mistral publishes remarkably little about it. we could not confirm the output dimension count from Mistral's own documentation — third-party integration docs for Pinecone and Milvus state 1,024, but those are not the vendor. there is no published parameter count, no language count, and no MTEB score on Mistral's pages. the api documents an optional output_dimension parameter described as available where the feature exists, without saying what the defaults or maximum are.
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
- $0.10 / 1m tokens
- website
- docs.mistral.ai
cheaper than OpenAI and easy to adopt if you are already a Mistral customer — from a model that publishes neither its dimensions nor its benchmark scores.
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