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Comparison of Intfloat: E5-Base-v2, VoyageAI by MongoDB: voyage-4-lite
2 modelsintfloatIntfloat: E5-Base-v2Remove ×voyageaiVoyageAI by MongoDB: voyage-4-liteRemove ×
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…voyage-4-lite is a lightweight, general-purpose embedding model optimized for low latency and cost. Enabled by Matryoshka learning and quantization-aware training, voyage-4-lite supports embeddings in 2048,…
DateNov 22, 2023ListedJul 27, 2026Listed
Listed rate$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.02 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints1 endpoint →1 endpoint →
Context window51232K
Max output46028.8K
Parameters——
Open weightsSupportedNot reported

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