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What is voyage-4-large?

The Voyage 4 model family from Voyage AI signifies a pioneering stage in the development of text embedding models, engineered to produce exceptional semantic vectors via a unique shared embedding space that allows for the generation of compatible embeddings among the various models within the series, thus empowering developers to effortlessly integrate models for both document and query embedding, which significantly boosts accuracy while also considering latency and cost factors. This lineup includes the voyage-4-large, the premier model that utilizes a mixture-of-experts architecture to reach state-of-the-art retrieval accuracy while achieving nearly 40% lower serving costs than comparable dense models; voyage-4, which effectively balances quality with performance; voyage-4-lite, which provides high-quality embeddings with a minimized parameter count and lower computational requirements; and the open-weight voyage-4-nano, ideal for local development and prototyping, distributed under an Apache 2.0 license. The seamless interoperability among these four models, all operating within the same shared embedding space, allows for interchangeable embeddings that foster innovative asymmetric retrieval techniques, which can greatly elevate performance across a wide range of applications. This integrated approach equips developers with a dynamic toolkit that can be customized to address various project demands, establishing the Voyage 4 family as an attractive option in the continuously evolving field of AI-driven technologies. Furthermore, the diverse capabilities and flexibility of these models enable organizations to experiment and adapt their embedding strategies to optimize specific use cases effectively.

What is CO2 Emissions, CII & EU ETS?

Our CO2 estimator delivers precise calculations of fuel consumption and CO2 emissions by analyzing the recorded voyage sequences and event details. This capability is made possible through AXSMarine's trade flows combined with our exclusive speed curves. By utilizing a voyage estimator, you can determine CO2 emissions, evaluate potential EUA costs, and outline the series of events for a particular journey. Additionally, Shiplist enables ranking of tonnage lists based on CO2 emissions, TCE, and voyage expenses associated with specific shipments. The emissions dashboard offers insights into historical CO2 emissions and financial risks, including CII, EEOI, and EUA, for individual vessels or entire fleets. You can visualize CO2 emissions, CII ratings, EEOI values, and EUA financial risks for each ship since 2013, while also reviewing all completed voyages and their effects on emissions and ratings. AXSMarine provides an unparalleled and reliable approach to CO2 estimation, ensuring rapid access to CO2 calculations across a grid of multiple vessels, enhancing decision-making processes for users. This comprehensive toolset supports better environmental management in shipping operations.

Media

Media

Integrations Supported

Cohere Embed
Gemini
Hugging Face
MongoDB Atlas
OpenAI
Voyage AI

Integrations Supported

AXSMarine API Hub
AXSMarine Trade Flows
Alphaliner

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Voyage AI

Date Founded

2023

Company Location

United States

Company Website

blog.voyageai.com/2026/01/15/voyage-4/

Company Facts

Organization Name

AXSMarine

Date Founded

2000

Company Location

France

Company Website

public.axsmarine.com/co2emissions-and-cii

Categories and Features

Embedding Models

Not specified

Categories and Features

Emissions Management

Not specified

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