Gemini Embedding 2Google
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Google GenAI SDKGoogle
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Related Products
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About
Gemini Embedding models, including the newer Gemini Embedding 2, are part of Google’s Gemini AI ecosystem and are designed to convert text, phrases, sentences, and code into numerical vector representations that capture their semantic meaning. Unlike generative models that produce new content, the embedding model transforms input data into dense vectors that represent meaning in a mathematical format, allowing computers to compare and analyze information based on conceptual similarity rather than exact wording. These embeddings enable applications such as semantic search, recommendation systems, document retrieval, clustering, classification, and retrieval-augmented generation pipelines. The model can process input in more than 100 languages and supports up to 2048 tokens per request, allowing it to embed longer pieces of text or code while maintaining strong contextual understanding.
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About
The Gemini API libraries provide official, production-ready Google GenAI SDKs for building with the Gemini API in popular programming languages. Google recommends using the Google GenAI SDK when building with Gemini, since these libraries are developed and maintained by Google, used across official documentation and examples, and are generally available for production use. The SDKs are available for Python, JavaScript/TypeScript, Go, Java, and C#, with installation through standard package managers such as pip install google-genai, npm install google/genai, Maven dependencies for google genai, and dotnet add package Google GenAI. They provide access to the latest Gemini API features and are designed to offer the best performance when working with Gemini models. Google strongly recommends migrating from legacy libraries to the new Google GenAI SDK because the legacy libraries are not actively maintained.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
AI developers and data engineers who need a high-performance embedding model to convert text or code into semantic vectors for search, retrieval, and AI applications
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Audience
Developers and AI engineering teams that need official Google SDKs to integrate Gemini API features into applications
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Pricing
Free
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationGoogle
Founded: 1998
United States
blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-embedding-2/
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Company InformationGoogle
Founded: 1998
United States
ai.google.dev/gemini-api/docs/libraries
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Categories |
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Integrations
Gemini
Python
C#
Gemini Enterprise
Gemini Enterprise Agent Platform
Go
Google AI Studio
Java
JavaScript
Maven
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Integrations
Gemini
Python
C#
Gemini Enterprise
Gemini Enterprise Agent Platform
Go
Google AI Studio
Java
JavaScript
Maven
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