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Description

Gemini Embedding models, which include the advanced Gemini Embedding 2, are integral to Google's Gemini AI framework and are specifically created to translate text, phrases, sentences, and code into numerical vector forms that encapsulate their semantic significance. In contrast to generative models that create new content, these embedding models convert input into dense vectors that mathematically represent meaning, facilitating the comparison and analysis of information based on conceptual relationships instead of precise wording. This functionality allows for various applications, including semantic search, recommendation systems, document retrieval, clustering, classification, and retrieval-augmented generation processes. Additionally, the model accommodates input in over 100 languages and can handle requests of up to 2048 tokens, enabling it to effectively embed longer texts or code while preserving a deep contextual understanding. Ultimately, the versatility and capability of the Gemini Embedding models play a crucial role in enhancing the efficacy of AI-driven tasks across diverse fields.

Description

Weaviate is an open-source vector database built for the AI era, giving teams one platform for vector search, retrieval-augmented generation, and agent memory. Store data objects together with embeddings from your preferred machine learning models and scale effortlessly to billions of objects. Import your own vectors or rely on Weaviate's built-in vectorization, then search across vector, keyword, and hybrid methods to get highly relevant results, even when filters are applied. By connecting to today's leading large language models, Weaviate helps you build grounded search and question-answering over your own data. The platform reaches well beyond storage: its Query Agent translates plain-language questions into accurate queries with citations, Engram delivers managed long-term memory for AI agents, and Weaviate Embeddings removes the work of running your own embedding pipeline. Available as self-hosted open source or fully managed Weaviate Cloud across AWS, GCP, and Azure, backed by SOC 2 Type II, native multi-tenancy, replication, and role-based access control. From semantic search to recommendation to fully agentic applications, Weaviate is the foundation to ship AI products faster.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Agno
Amazon SageMaker
Amazon Web Services (AWS)
Anthropic
Boomi
Claude Code
Contextual AI
DSPy
DigitalOcean
Dynamiq
Google Cloud Marketplace
Jina AI
LlamaIndex
Mem0
Microsoft Azure
Model Context Protocol (MCP)
NVIDIA AI Data Platform
Nomic Atlas
Parallel
Snowflake

Integrations

Agno
Amazon SageMaker
Amazon Web Services (AWS)
Anthropic
Boomi
Claude Code
Contextual AI
DSPy
DigitalOcean
Dynamiq
Google Cloud Marketplace
Jina AI
LlamaIndex
Mem0
Microsoft Azure
Model Context Protocol (MCP)
NVIDIA AI Data Platform
Nomic Atlas
Parallel
Snowflake

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
Open source (free); free Weaviate Cloud tier; paid Cloud plans from $45/mo.
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

Google

Founded

1998

Country

United States

Website

blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-embedding-2/

Vendor Details

Company Name

Weaviate

Founded

2019

Country

The Netherlands

Website

weaviate.io

Product Features

Alternatives

Alternatives

Embeddinghub Reviews

Embeddinghub

Featureform