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OpenAI Text Embedding 3 vs Cohere Embed

Hosted embedding models with configurable output dimensions.

功能对比

OpenAI Text Embedding 3 与 Cohere Embed 功能对比
维度 OpenAI Text Embedding 3 Cohere Embed
Dimensions 1536 by default, 256 to 3072 selectable 1024
License Proprietary Proprietary
Max tokens 8191 512
Open weights No No
Provider OpenAI Cohere

灰底行表示两者相同;有差异的行才是下方推荐结论的依据。

该选哪个?

由上述差异按固定规则生成,不是模型生成的。

Choose OpenAI Text Embedding 3 if…

已记录的属性中,没有任何一项显示它更有优势。

Choose Cohere Embed if…

已记录的属性中,没有任何一项显示它更有优势。

OpenAI Text Embedding 3

model · Embedding Models

Text Embedding 3 is OpenAI's hosted embedding family, notable for letting the caller choose a shorter output vector than the model natively produces. It solves the storage problem directly: embedding indexes are sized by dimensions times vectors, so trimming 3072 dimensions to 512 or 256 shrinks the index substantially at a small quality cost. It exists because that trade is one the caller is better placed to make than the model author, and it removes the need to retrain to change it.

Cohere Embed

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.