Text embedding model family trained on weakly supervised pairs.
| 维度 | E5 | Jina Embeddings |
|---|---|---|
| Dimensions | 1024 | 768 |
| License | MIT | Apache-2.0 |
| Max tokens | 512 | 8192 |
| Open weights | Yes | Yes |
| Provider | Microsoft | Jina AI |
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。
由上述差异按固定规则生成，不是模型生成的。
Choose E5 if…
已记录的属性中，没有任何一项显示它更有优势。
Choose Jina Embeddings if…
已记录的属性中，没有任何一项显示它更有优势。
model · Embedding Models
E5 is an embedding model family trained on large collections of weakly supervised text pairs, with the task described in the input so one model serves queries, passages and classification. It solves the problem that an embedding model trained on one kind of pair transfers poorly to another. It exists because describing the task in the text is a cheap way to make one model cover several retrieval settings.
model · Embedding Models
Jina Embeddings are embedding models built with long-context inputs as a design goal rather than a limitation to work around, so a whole document section can be embedded instead of a truncated fragment. It solves the chunking problem: when the encoder caps at a few hundred tokens, long documents must be split, and the split loses the context that made the passage meaningful. It exists because retrieval quality is often limited by what had to be discarded before embedding rather than by the model itself.
