Voyage AI
An AI company specializing in text embedding and reranking models. It provides high-quality vector representations for use cases including code retrieval, long-document understanding, and multilingual scenarios.
Core Facts
@ai-sdk/voyage is the official provider package within the Vercel AI SDK dedicated to Voyage AI embedding models
Voyage AI is known for its high-quality text embedding models, which are widely used in RAG, semantic search, and vectorization scenarios
Voyage AI is a company focused on text embedding and reranking models
Timeline (last 90 days)
Voyage AI's own model service (such as the voyage-3 series) and the npm package @ai-sdk/voyage are two different things: the former is a remote API, while the latter is merely an SDK adapter layer for calling it.
Dependency updates do not change the capabilities or billing of the Voyage AI model; what actually affects output quality is the model parameter specified in the request and the input content.
In AI SDK, @ai-sdk/voyage wraps the Voyage AI service into an interface consistent with providers such as OpenAI and Cohere, enabling developers to call different vendors' vector models with a unified embed/embedMany
Voyage AI's models include the voyage-3, voyage-code-3 and other series, and are commonly used in scenarios such as semantic retrieval, RAG, clustering, and deduplication
Voyage AI is a service provider focused on delivering high-quality embedding models, and its models are widely used in scenarios such as RAG and semantic search.
Voyage AI has trained dedicated embedding models for specific domains such as code, law, and finance, which often outperform general-purpose embedding models in retrieval accuracy for vertical scenarios.
Voyage AI is a company focused on text embedding models, with core products including the voyage-2 and voyage-large-2 series.
Voyage AI's embedding models stand out in standard benchmarks such as MTEB, and are particularly strong in code retrieval and long-document understanding scenarios.
Voyage AI is known for its high-quality text embedding models, which are widely used in RAG, semantic search, and vectorization scenarios
Voyage's main selling points compared to competitors such as OpenAI and Cohere are lower latency and higher retrieval accuracy.
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All Facts (15)
@ai-sdk/voyage is the official provider package within the Vercel AI SDK dedicated to Voyage AI embedding models
90%VerifiedVoyage AI is known for its high-quality text embedding models, which are widely used in RAG, semantic search, and vectorization scenarios
75%VerifiedVoyage AI is a company focused on text embedding and reranking models
75%UnverifiedVoyage's models can be called via its REST API, and @ai-sdk/voyage wraps that call into a provider conforming to the unified interface of the Vercel AI SDK.
70%UnverifiedDependency updates do not change the capabilities or billing of the Voyage AI model; what actually affects output quality is the model parameter specified in the request and the input content.
50%UnverifiedVoyage AI's own model service (such as the voyage-3 series) and the npm package @ai-sdk/voyage are two different things: the former is a remote API, while the latter is merely an SDK adapter layer for calling it.
50%UnverifiedIn AI SDK, @ai-sdk/voyage wraps the Voyage AI service into an interface consistent with providers such as OpenAI and Cohere, enabling developers to call different vendors' vector models with a unified embed/embedMany
50%UnverifiedVoyage AI's models include the voyage-3, voyage-code-3 and other series, and are commonly used in scenarios such as semantic retrieval, RAG, clustering, and deduplication
50%UnverifiedVoyage AI is a service provider focused on delivering high-quality embedding models, and its models are widely used in scenarios such as RAG and semantic search.
50%UnverifiedVoyage AI has trained dedicated embedding models for specific domains such as code, law, and finance, which often outperform general-purpose embedding models in retrieval accuracy for vertical scenarios.
50%UnverifiedVoyage AI is a company focused on text embedding models, with core products including the voyage-2 and voyage-large-2 series.
50%UnverifiedVoyage AI's embedding models stand out in standard benchmarks such as MTEB, and are particularly strong in code retrieval and long-document understanding scenarios.
50%UnverifiedVoyage's main selling points compared to competitors such as OpenAI and Cohere are lower latency and higher retrieval accuracy.
50%UnverifiedVoyage AI's embedding models perform notably in vertical domains such as code retrieval, legal, and finance, and support a context window of up to 32K tokens.
50%UnverifiedVoyage has embedding model versions specifically optimized for vertical domains such as code, legal, and medical.
50%