Jina Embeddings v5
excellent quality per parameter, on weights you may not use commercially
a genuinely strong sub-1b multilingual model that most readers of this page cannot legally deploy — and the licence is not what its reputation suggests.
the engineering deserves credit. v5-text-small is 677 million parameters, takes 32,768 tokens of context, truncates from 1,024 dimensions down to 32, and claims support for 93 languages against training on 32. Jina reports 71.7 average on english MTEB, though without naming the board version. distilling v4-class quality into a sub-billion-parameter model is a real achievement.
the licence is the problem, and it is worth being blunt because the received wisdom is wrong. Jina embedding weights are non-commercial. we read v4's licence file directly: section 2(a) grants rights for non-commercial purposes only, and commercial use requires a separate agreement. v5-text-small, which replaced it in february 2026, is CC-BY-NC-4.0. neither is a licence you can build a product on without buying something extra, and Jina is routinely listed alongside apache and mit models as though it were equivalent.
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
- jina.ai
a genuinely strong sub-1b multilingual model that most readers of this page cannot legally deploy — and the licence is not what its reputation suggests.
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