M4A

Voyage AI

State-of-the-art embedding models for semantic search and RAG

paidproductionembeddingssearchragapi
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Memory Types

semantic

Integrations

langchain, llamaindex, pinecone, weaviate


Overview


Voyage AI provides state-of-the-art embedding models specifically optimized for search and retrieval-augmented generation (RAG). Founded by researchers from Stanford and Google, Voyage focuses exclusively on embeddings, achieving superior performance on retrieval benchmarks compared to general-purpose embedding models.


The company offers domain-specific embedding models optimized for different use cases (code, finance, legal, etc.), providing better accuracy than one-size-fits-all solutions. Voyage's models consistently top the MTEB (Massive Text Embedding Benchmark) leaderboard, demonstrating measurable quality advantages.


Key Features


  • **Domain-Specific Models**: Optimized for code, finance, legal, etc.
  • **Top MTEB Performance**: Consistently ranks #1 on benchmarks
  • **RAG-Optimized**: Designed specifically for retrieval tasks
  • **Multiple Sizes**: Balance quality and cost
  • **Simple API**: Easy integration
  • **Reranking**: Improves search result quality
  • **Batch Processing**: Efficient bulk embedding
  • **Custom Models**: Fine-tune for your domain

    • When to Use Voyage AI


    Voyage AI is ideal for:

  • RAG applications requiring best retrieval quality
  • Domain-specific search (code, legal, finance)
  • Applications where embedding quality matters most
  • Teams benchmarking embedding providers
  • Production search systems
  • Replacing general-purpose embeddings for better accuracy

    • Pros


  • Best-in-class embedding quality
  • Domain-specific optimization
  • Consistently tops benchmarks
  • Simple, clean API
  • Good documentation
  • Transparent pricing
  • Founded by top researchers
  • Focus on one thing done well

    • Cons


  • More expensive than some alternatives
  • Limited to embeddings (no LLMs)
  • Smaller ecosystem than OpenAI
  • Newer company with less track record
  • Requires API dependency
  • No self-hosting option
  • Limited integrations compared to established providers
  • Single-purpose service

    • Pricing


  • **voyage-3**: $0.10 per 1M tokens
  • **voyage-finance-2**: $0.12 per 1M tokens
  • **voyage-code-2**: $0.12 per 1M tokens
  • **Reranking**: $0.05 per 1K searches

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