Embedding model family that ranks well on retrieval benchmarks.
| Merkmal | BGE | Cohere Embed |
|---|---|---|
| Dimensions | 1024 | 1024 |
| License | MIT | Proprietary |
| Max tokens | 512 | 512 |
| Open weights | Yes | No |
| Provider | BAAI | Cohere |
Schattierte Zeilen sind bei beiden gleich; die abweichenden Zeilen begründen die Empfehlung unten.
Aus den Unterschieden oben durch feste Regeln erzeugt, nicht von einem Modell.
Choose BGE if…
Keines der erfassten Merkmale zeichnet es zu Ihren Gunsten aus.
Choose Cohere Embed if…
Keines der erfassten Merkmale zeichnet es zu Ihren Gunsten aus.
model · Embedding Models
BGE is a family of embedding models trained specifically for retrieval, available in sizes small enough to run locally. It solves the problem that a general-purpose embedding model is not optimised for the asymmetric comparison a search query and a document require. It exists because retrieval quality is set at the embedding step, so a model trained for it improves everything downstream without changing anything else.
model · Embedding Models
Cohere Embed is a hosted embedding model that distinguishes the query from the document being indexed, and supports a hundred languages in one model. It solves the asymmetry problem explicitly: a question and a passage are not the same kind of text, and encoding them with the same mode is a compromise. It exists because multilingual retrieval otherwise means either a separate model per language or one model doing all of them badly.
