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Gte Large En

huggingface.co·Infrastructure

gte-large-en-v1.5 is a large English text embedding model developed by Alibaba-NLP, optimized for sentence similarity, semantic search, and retrieval-augmented generation tasks. It is available on Hugging Face with an Apache-2.0 license and supports integration via the Transformers library and Transformers.js. The model excels on MTEB benchmarks and is designed for efficient performance in production RAG and search applications.

Open SourceWebAPI
GGte Large En preview
Visit huggingface.co↗
2alternatives
3features
2024since

Overview

3 features

In the Foundation models & chat space, Gte Large En takes a focused approach. Developers needing high-quality, efficient text embeddings for semantic search, retrieval, and similarity applications without proprietary APIs. Gte Large En is an open-source project aimed at developers and AI researchers. Gte Large En is open source under the Open Source license. It ships for the web and API.

It is developed by Alibaba-NLP, and it first shipped in 2024. Key capabilities include Text Embeddings, Sentence Similarity, and Semantic Search.

Summary written by a language model from the project’s public pages.

  • ✓Text Embeddings
  • ✓Sentence Similarity
  • ✓Semantic Search
Tags
text-embeddingsentence-transformerssemantic-searchretrieval-modelmteb-benchmark
AI capabilities
Text
Inference: LocalWeights: Open

Built with & integrations

Hosting
AWS
Runs on
BrowserAPI-only
Detected from
AWS
x-amz-cf-id header · x-amz-cf-pop header · via header

Trust & compliance

License
Open Source
Verified signals
✓HTTPS✓Open Source

Indexing history

1

What PulseGate has recorded for this listing

  1. Indexed22 Jul · 09:13 UTC
    Alibaba-NLP/gte-large-en-v1.5 verified against its public source
    Source: PulseGate · Open ↗

Frequently asked questions about Gte Large En

What is Gte Large En?
Developers needing high-quality, efficient text embeddings for semantic search, retrieval, and similarity applications without proprietary APIs. It is catalogued under Foundation models & chat on PulseGate.
Who should use Gte Large En?
Gte Large En is an open-source project built for developers and AI researchers.
Is Gte Large En free?
Yes — Gte Large En is open source under the Open Source license and free to use.
What platforms does Gte Large En run on?
Gte Large En runs on the web and API.
Is Gte Large En still active?
Unverified. Gte Large En has not been re-checked since it entered the index, so there is no finding either way — and only a positive finding would say otherwise.
What projects are similar to Gte Large En?
Similar projects tracked by PulseGate include Gte Base En, Gte Small, and Gte Base.Gte Base EnGte SmallGte Base
Who makes Gte Large En?
Gte Large En is developed by Alibaba-NLP.
When did Gte Large En launch?
Gte Large En first shipped in 2024.

At a glance

Pricing
Open Source
Platforms
Web
Languages
English
License
Open Source
Built for
developers and AI researchers
Model
Open source
Solves
Developers needing high-quality, efficient text embeddings for semantic search, retrieval, and similarity applications without proprietary APIs.

Registered as

Hugging Face
Alibaba-NLP/gte-large-en-v1.5

Developer

Alibaba-NLP

Live coverage

Identity confidence
Medium · 70.4
Indexed
22 Jul 2026
Lifecycle
Alive
Last seen
22 Jul 2026
Identity audit (13)
Slug
alibaba-nlp-gte-large-en-v1-5-huggingface-co
Lifecycle state recorded
22 Jul 2026
Verification state
Indexed for public listing
Listing state
Listed: yes
Index status
Included in index
Latest evidence snapshot
22 Jul 2026
Timeline basis
Indexed-at chronology. This listing's first-seen date was written by the catalog backfill, not observed here, so it is not treated as a sighting.
Name from
Derived from the project's own page and URL.
Category from
Derived from the model's own Hugging Face metadata.
Summary from
Written by a language model from public pages.
Languages from
Detected by a language model from page content.
Last updated
6 Aug 2026
Canonical URL
https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5

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