Building production AI means balancing accuracy, cost, and deployment flexibility.
Today, we're making that easier:
✨ Voyage 4 series: Shared embedding space lets you mix models across pipeline stages. Use voyage-4-large for indexing, voyage-4-lite for queries, and voyage-4-nano locally.
🎥 voyage-multimodal-3.5: Native video retrieval and the first production-grade video embedding model to support Matryoshka embeddings for flexible dimensionality.
🌍 New availability: Deploy on MongoDB Atlas, Google Cloud, Amazon Web Services (AWS), or Microsoft Azure.
The most accurate models. Available everywhere you build.
Read the full announcement: https://t.co/ZeAeEshaLG
embedding — A list of numbers representing a piece of text's meaning, so that similar meanings end up numerically close and can be searched.
multimodal — A model that works with more than text — reading images, audio, or video, and sometimes generating them too.
Why it matters
A shared embeddingA list of numbers representing a piece of text's meaning, so that similar meanings end up numerically close and can be searched.Full definition → space lets you index with a large model, query with a small one and run a nano model locally without re-embedding, trading cost against accuracy per stage.
