text-embedding-3-large
the default everyone reaches for, and it is showing its age
still a solid general-purpose embedding with the most flexible dimension control here — on an 8k context and a model that has not been updated since january 2024.
this is the model most rag tutorials use and most production stacks inherited. it is good, it is well documented, and if you are already sending requests to OpenAI it costs you no new vendor relationship, no new key and no new billing conversation. $0.13 a million puts it mid-table.
its best feature is the dimensions parameter, which lets you request any smaller output size rather than picking from a fixed list the way Cohere and voyage do. shortening to 256 dimensions costs far less quality than naive truncation would, and it means index size is a dial rather than a decision made once at model selection.
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
- $0.13 / 1m tokens
- website
- platform.openai.com
still a solid general-purpose embedding with the most flexible dimension control here — on an 8k context and a model that has not been updated since january 2024.
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