GTE vs Nomic Embed

Embedding model family from Alibaba, trained for retrieval and ranking.

功能对比

GTE 与 Nomic Embed 功能对比
维度	GTE	Nomic Embed
Dimensions	1024	768
License	Apache-2.0	Apache-2.0
Max tokens	8192	8192
Open weights	Yes	Yes
Provider	Alibaba	Nomic 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。

该选哪个？

由上述差异按固定规则生成，不是模型生成的。

Choose GTE if…

已记录的属性中，没有任何一项显示它更有优势。

Choose Nomic Embed if…

已记录的属性中，没有任何一项显示它更有优势。

GTE

model · Embedding Models

GTE is a family of text embedding models trained for retrieval, with variants covering English and multilingual use and long inputs. It solves the same problem as the other retrieval-focused embedding families: a general-purpose encoder is not optimised for the asymmetric comparison of a short query against a long document. It exists because retrieval quality is decided at the embedding step, and a family that scores well on public retrieval benchmarks is the cheapest way to improve everything downstream.

Nomic Embed

model · Embedding Models

Nomic Embed is an open embedding model released with an open training dataset and reproducible training run, as well as long-context support. It solves two problems at once: most open embedding models publish weights but not the data they were trained on, which makes their behaviour hard to reason about, and most cap inputs short of a document. It exists because an embedding model whose training data is inspectable can be evaluated for the biases that come from that data.