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What is voyage-3-large?

Voyage AI has launched voyage-3-large, a groundbreaking multilingual embedding model that demonstrates superior performance across eight diverse domains, including law, finance, and programming, boasting an average enhancement of 9.74% compared to OpenAI-v3-large and 20.71% over Cohere-v3-English. The model utilizes cutting-edge Matryoshka learning alongside quantization-aware training, enabling it to deliver embeddings in dimensions of 2048, 1024, 512, and 256, while supporting various quantization formats such as 32-bit floating point, signed and unsigned 8-bit integer, and binary precision, which greatly reduces costs for vector databases without compromising retrieval quality. Its ability to manage a 32K-token context length is particularly noteworthy, as it significantly surpasses OpenAI's 8K limit and Cohere's mere 512 tokens. Extensive tests across 100 datasets from multiple fields underscore its remarkable capabilities, with the model's flexible precision and dimensionality options leading to substantial storage savings while maintaining high-quality output. This significant development establishes voyage-3-large as a strong contender in the embedding model arena, setting new standards for both adaptability and efficiency in data processing. Overall, its innovative features not only enhance performance in various applications but also promise to transform the landscape of multilingual embedding technologies.

What is Voyage AI?

Voyage AI specializes in building cutting-edge embedding models and rerankers for high-performance search and retrieval systems. Its technology is designed to improve how unstructured data is indexed, searched, and used in AI applications. By strengthening retrieval quality, Voyage AI enables more accurate and grounded RAG responses. The platform offers a spectrum of models, ranging from ready-to-use general models to highly specialized domain and company-specific solutions. These models are optimized for industries such as legal, finance, and software development. Voyage AI focuses on efficiency by delivering shorter vector representations that lower storage and search costs. Its models run with low latency and reduced inference expenses, making them suitable for production-scale workloads. Long-context support allows applications to reason over large datasets and documents. Voyage AI’s modular design ensures easy integration with any vector database or language model. Deployment options include pay-as-you-go APIs, cloud marketplaces, and on-premise or licensed models. The platform is trusted by leading AI-driven companies for mission-critical retrieval tasks. Voyage AI ultimately helps organizations build smarter, faster, and more cost-effective AI-powered search experiences.

Media

Media

Integrations Supported

Snowflake
Cohere
LangChain
OneSignal
PyTorch
Voyage AI

Integrations Supported

Snowflake
LiteLLM
Pinecone Rerank v0
Snowflake Cortex AI
Weaviate
voyage-3-large
voyage-4-large

API Availability

API Availability

Has API

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

MongoDB

Date Founded

2007

Company Location

United States

Company Website

blog.voyageai.com/2025/01/07/voyage-3-large/

Company Facts

Organization Name

MongoDB

Date Founded

2007

Company Location

United States

Company Website

www.voyageai.com

Categories and Features

Embedding Models

Not specified

Categories and Features

Embedding Models

Not specified

Reranking Models

Not specified

Semantic Search

Not specified

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