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Comparison of Intfloat: E5-Base-v2, Intfloat: Multilingual-E5-Large, VoyageAI by MongoDB: voyage-code-4
3 modelsintfloatIntfloat: E5-Base-v2Remove ×intfloatIntfloat: Multilingual-E5-LargeRemove ×voyageaiVoyageAI by MongoDB: voyage-code-4Remove ×
What’s differentThe e5-base-v2 embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, producing efficient and high-quality semantic embeddings optimized for tasks such as…The multilingual-e5-large embedding model encodes sentences, paragraphs, and documents across over 90 languages into a 1024-dimensional dense vector space, delivering robust semantic embeddings optimized…voyage-code-4 is a code embedding model from Voyage AI, a MongoDB company. It is designed for coding agents and code retrieval, with Matryoshka embeddings at 2048, 1024, 512, and 256...
DateNov 22, 2023ListedJun 4, 2024ListedAug 13, 2026Listed
Listed rate$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.12 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints1 endpoint →1 endpoint →1 endpoint →
Context window51251232K
Max output46046028.8K
Parameters———
Open weightsSupportedSupportedNot reported

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