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Voyage 4 Large

Voyage 4 Large is Voyage AI's Voyage 4 flagship embedding model. It uses a mixture-of-experts (MoE) architecture. Voyage AI reports state-of-the-art general retrieval in their published benchmarks, with serving costs about 40% lower than comparable dense models, and average gains over OpenAI text-embedding-3-large, Cohere Embed v4, and Gemini Embedding 001 in the same comparison. It shares one embedding space with voyage-4 and voyage-4-lite.

index.ts
import { embed } from 'ai';


const result = await embed({
  model: 'voyage/voyage-4-large',
  value: 'Sunny day at the beach',
})
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About Voyage 4 Large

Voyage 4 Large is the first production embedding model to use a mixture-of-experts architecture, released N/A. MoE activates only a subset of parameters per token, achieving flagship-level retrieval accuracy at lower inference cost than a dense model of equivalent quality.

Voyage AI reports Voyage 4 Large surpasses voyage-3-large on retrieval accuracy at a lower price point, with serving costs about 40% below comparable dense models. It supports a context window of 32K tokens and the full Matryoshka dimension set (2048, 1024, 512, 256) with quantization-aware training.

As the top of the Voyage 4 series, Voyage 4 Large produces the strongest average retrieval scores in Voyage AI's published benchmarks. Use it for document embeddings in asymmetric setups where you pair it with voyage-4 or voyage-4-lite on the query side to control per-query costs.