Voyage ai is proud to announce the launch of its next generation of embedded models, Trip-3 and Trip-3-Lite. The Voyage-3 and Voyage-3-Lite models are designed to exceed existing industry standards in a variety of domains, including technology, law, finance, multilingual applications, and long-term context understanding. According to Voyage ai evaluations, Voyage-3 outperforms OpenAI's V3 large model by an average of 7.55% across all tested domains, including technical documentation, code, law, finance, web content, multilingual datasets, extensive documents and conversational data. Additionally, Voyage-3 achieves this with 2.2x lower costs and a 3x smaller embedding dimension, resulting in significantly reduced vector database (vectorDB) costs. Similarly, Voyage-3-Lite offers 3.82% better retrieval accuracy than OpenAI's V3 large model, with 6x lower costs and 6x smaller embedding dimension.
Profitability without compromising quality
Cost efficiency is at the core of the new Voyage-3 series models. With a context length of 32,000 tokens, four times more than OpenAI's offering, Voyage-3 is a cost-effective solution for businesses that require high-quality retrieval without breaking the bank. For example, Voyage-3 costs $0.06 per million tokens, making it 1.6 times cheaper than Cohere English V3 and substantially more affordable than OpenAI's large V3 model. Additionally, Voyage-3's smaller integration dimension (1024 vs. OpenAI's 3072) results in lower vectorDB costs, allowing enterprises to scale their applications efficiently.
Voyage-3-Lite, the lightest variant of the model, is optimized for low latency operations. At $0.02 per million tokens, it is 6.5 times cheaper than OpenAI's large V3 model and has an embedding dimension 6 to 8 times smaller (512 vs. OpenAI's 3,072). This makes Voyage-3-Lite a viable option for organizations looking to maintain high recovery quality at a fraction of the cost.
Versatility in multiple domains
The success of the Voyage-3 series models extends beyond general-purpose inlays. Over the past nine months, Voyage ai has released a set of integrated Voyage-2 series models, including domain-specific models such as Voyage-Large-2, Voyage-Code-2, Voyage-Law-2, Voyage-Finance- 2. and Travel-Multilingual-2. These models have been extensively trained with data from their respective domains, demonstrating exceptional performance in specialized use cases.
For example, Voyage-Multilingual-2 offers superior retrieval quality in French, German, Japanese, Spanish and Korean, while maintaining best-in-class performance in English. These achievements are testament to Voyage ai's commitment to developing robust models tailored to specific business needs.
Technical specifications and innovations
Several research innovations underpin the development of Voyage-3 and Voyage-3-Lite. The models feature an improved architecture, leveraging distillation of larger models and pre-training on over 2 trillion high-quality tokens. Additionally, the alignment of retrieval results is refined through human feedback, further improving the accuracy and relevance of the models.
Key technical specifications of the Voyage-3 series models include:
Trip-3:
- Dimensions: 1024
- Context length: 32,000 tokens
- Cost: $0.06 per million tokens
- Retrieval quality (NDCG@10): 76 (outperforms OpenAI V3 large by 7.55%)
Trip-3-Lite:
- Dimensions: 512
- Context length: 32,000 tokens
- Cost: $0.02 per million tokens
- Retrieval quality (NDCG@10): 72 (outperforms OpenAI V3 large by 3.82%)
The models' ability to handle a context length of 32,000 tokens, compared to OpenAI's 8,000 tokens and Cohere's 512 tokens, makes them suitable for applications that require end-to-end understanding and retrieval of large documents, such as technical manuals, academic articles and legal case summaries.
Applications and use cases
Voyage-3 series models suit a wide range of industries and enable applications in domains such as:
- Technical documentation: Provide accurate and contextual retrieval of large technical manuals and programming guides.
- Code: It offers an improved understanding of code snippets, docstrings, and programming logic, making it ideal for software development and code review.
- Law: Support complex legal investigations by retrieving relevant judicial opinions, statutes, and legal arguments.
- Finance: Streamline retrieval of financial statements, SEC filings, and market analysis reports.
- Multilingual applications: Facilitating multilingual search and retrieval in 26 languages, including French, German, Japanese, Spanish and Korean.
Recommendations for users
Voyage ai recommends that any general-purpose integration user upgrade to Voyage-3 for improved recovery quality at a low cost. Voyage-3-Lite offers an excellent balance of performance and affordability for those looking for greater cost savings. Domain-specific use cases such as code, law, and finance can still benefit from Voyage-2 series models such as Voyage-Code-2, Voyage-Law-2, and Voyage-Finance-2, although Voyage-3 provides highly competitive performance in these areas as well.
Future developments
The Voyage ai team is continually working to expand the capabilities of the Voyage-3 series models. In the coming weeks, the release of Voyage-3-Large is expected to set a new standard for large-scale, general-purpose embeddings, further solidifying Voyage ai's position as a leader in this field. For those interested in exploring the potential of the Voyage-3 series, the first 200 million tokens can be tested for free. Users can use these models immediately by specifying “voyage-3” or “voyage-3-lite” as the model parameter in Voyage API calls. Voyage ai's launch of Voyage-3 and Voyage-3-Lite represents a major step forward in integration technology, offering a unique combination of high performance, low cost and versatility. With these new models, Voyage ai continues to lead the way in creating next-generation solutions for businesses and developers around the world.
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