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Description

Microsoft has developed E5 Text Embeddings, which are sophisticated models that transform textual information into meaningful vector forms, thereby improving functionalities such as semantic search and information retrieval. Utilizing weakly-supervised contrastive learning, these models are trained on an extensive dataset comprising over one billion pairs of texts, allowing them to effectively grasp complex semantic connections across various languages. The E5 model family features several sizes—small, base, and large—striking a balance between computational efficiency and the quality of embeddings produced. Furthermore, multilingual adaptations of these models have been fine-tuned to cater to a wide array of languages, making them suitable for use in diverse global environments. Rigorous assessments reveal that E5 models perform comparably to leading state-of-the-art models that focus exclusively on English, regardless of size. This indicates that the E5 models not only meet high standards of performance but also broaden the accessibility of advanced text embedding technology worldwide.

Description

The Gemini Embedding's inaugural text model, known as gemini-embedding-001, is now officially available through the Gemini API and Gemini Enterprise Agent Platform, having maintained its leading position on the Massive Text Embedding Benchmark Multilingual leaderboard since its experimental introduction in March, attributed to its outstanding capabilities in retrieval, classification, and various embedding tasks, surpassing both traditional Google models and those from external companies. This highly adaptable model accommodates more than 100 languages and has a maximum input capacity of 2,048 tokens, utilizing the innovative Matryoshka Representation Learning (MRL) method, which allows developers to select output dimensions of 3072, 1536, or 768 to ensure the best balance of quality, performance, and storage efficiency. Developers are able to utilize it via the familiar embed_content endpoint in the Gemini API.

API Access

Has API

API Access

Has API

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Integrations

Gemini
Gemini Enterprise
Gemini Enterprise Agent Platform
Google AI Studio
Python

Integrations

Gemini
Gemini Enterprise
Gemini Enterprise Agent Platform
Google AI Studio
Python

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$0.15 per 1M input tokens
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

github.com/microsoft/unilm/tree/master/e5

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

developers.googleblog.com/en/gemini-embedding-available-gemini-api/

Product Features

Product Features

Alternatives

Alternatives

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word2vec

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