{ "embedding": { "voyage-2": { "description": "General-purpose embedding model optimized for a balance between cost, latency, and retrieval quality.", "inputTokens": 4000, "inputTokenPrice": 0.1, "dimensions": 1024 }, "voyage-large-2": { "description": "General-purpose embedding model that is optimized for retrieval quality.", "inputTokens": 16000, "inputTokenPrice": 0.12, "dimensions": 1536 }, "voyage-law-2": { "description": "Optimized for legal and long-context retrieval and RAG. Also improved performance across all domains.", "inputTokens": 16000, "inputTokenPrice": 0.12, "dimensions": 1024 }, "voyage-code-2": { "description": "Optimized for code retrieval (17% better than alternatives). ", "inputTokens": 16000, "inputTokenPrice": 0.12, "dimensions": 1536 }, "voyage-multilingual-2": { "description": "Optimized for multilingual retrieval and RAG", "inputTokens": 32000, "inputTokenPrice": 0.12, "dimensions": 1024 }, "voyage-finance-2": { "description": "Optimized for finance retrieval and RAG.", "inputTokens": 32000, "inputTokenPrice": 0.12, "dimensions": 1024 }, "voyage-3-large": { "description": "", "inputTokens": 32000, "inputTokenPrice": 0.18, "dimensions": 1536 }, "voyage-3": { "description": "", "inputTokens": 32000, "inputTokenPrice": 0.06, "dimensions": 1536 }, "voyage-3-lite": { "description": "", "inputTokens": 32000, "inputTokenPrice": 0.02, "dimensions": 1536 }, "voyage-code-3": { "description": "", "inputTokens": 32000, "inputTokenPrice": 0.18, "dimensions": 1536 }, "voyage-multimodal-3": { "description": "", "inputTokens": 32000, "inputTokenPrice": 0.12, "dimensions": 1536 } } }