Voyage context 3
voyage-context-3 is a contextualized chunk embedding model that produces vectors capturing both chunk-level detail and full document context. It processes entire documents in a single pass and generates a distinct embedding per chunk. Supports flexible output dimensions (256, 512, 1024, 2048) via Matryoshka learning and multiple quantization options (float32, int8, uint8, binary). Per-chunk context window is 32K tokens; total document context is 120K tokens.
- Type
- Text
- Weights
- Closed
- Likes
- 16
Model hub
voyageai/voyage-context-3
- Repo
- voyageai/voyage-context-3
- Access
- Public
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Voyage AI provides best-in-class embedding models and rerankers for search and retrieval over unstructured data, used to power retrieval-augmented generation (RAG) and AI applications. It offers general-purpose, domain-specific (finance, legal, code) and company-specific fine-tuned models. Founded in 2023 and based in Palo Alto, the company was acquired by MongoDB, Inc. in February 2025 and now operates as a MongoDB subsidiary.