+
+

Related Products

  • Vertex AI
    961 Ratings
    Visit Website
  • LM-Kit.NET
    26 Ratings
    Visit Website
  • Parasoft
    142 Ratings
    Visit Website
  • RaimaDB
    12 Ratings
    Visit Website
  • ScreenMeet
    33 Ratings
    Visit Website
  • Visual Lease
    430 Ratings
    Visit Website
  • Wallester
    263 Ratings
    Visit Website
  • FISPAN
    5 Ratings
    Visit Website
  • Creatio
    522 Ratings
    Visit Website
  • BidJS
    33 Ratings
    Visit Website

About

Cohere's Embed is a leading multimodal embedding platform designed to transform text, images, or a combination of both into high-quality vector representations. These embeddings are optimized for semantic search, retrieval-augmented generation, classification, clustering, and agentic AI applications.​ The latest model, embed-v4.0, supports mixed-modality inputs, allowing users to combine text and images into a single embedding. It offers Matryoshka embeddings with configurable dimensions of 256, 512, 1024, or 1536, enabling flexibility in balancing performance and resource usage. With a context length of up to 128,000 tokens, embed-v4.0 is well-suited for processing large documents and complex data structures. It also supports compressed embedding types, including float, int8, uint8, binary, and ubinary, facilitating efficient storage and faster retrieval in vector databases. Multilingual support spans over 100 languages, making it a versatile tool for global applications.

About

Gemini Embedding’s first text model (gemini-embedding-001) is now generally available via the Gemini API and Vertex AI, having held a top spot on the Massive Text Embedding Benchmark Multilingual leaderboard since its experimental launch in March, thanks to superior performance across retrieval, classification, and other embedding tasks compared to both legacy Google and external proprietary models. Exceptionally versatile, it supports over 100 languages with a 2,048‑token input limit and employs the Matryoshka Representation Learning (MRL) technique to let developers choose output dimensions of 3072, 153,6, or 768 for optimal quality, performance, and storage efficiency. Developers can access it through the existing embed_content endpoint in the Gemini API, and while legacy experimental versions will be deprecated later in 2025, migration requires no re‑embedding of existing content.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI teams seeking a solution for generating high-quality, multimodal embeddings that enhance search accuracy and contextual understanding

Audience

Data scientists wanting a solution for multilingual retrieval, classification and other advanced AI applications

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

$0.47 per image
Free Version
Free Trial

Pricing

$0.15 per 1M input tokens
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Cohere
Founded: 2019
Canada
cohere.com/embed

Company Information

Google
Founded: 1998
United States
developers.googleblog.com/en/gemini-embedding-available-gemini-api/

Alternatives

Codestral Embed

Codestral Embed

Mistral AI

Alternatives

Categories

Categories

Integrations

Cohere
Gemini
Gemini Enterprise
Google AI Studio
Python
Vertex AI
voyage-4-large

Integrations

Cohere
Gemini
Gemini Enterprise
Google AI Studio
Python
Vertex AI
voyage-4-large
Claim Cohere Embed and update features and information
Claim Cohere Embed and update features and information
Claim Gemini Embedding and update features and information
Claim Gemini Embedding and update features and information