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Comparison of multilingual-e5-large-instruct, Intfloat: E5-Base-v2, VoyageAI by MongoDB: voyage-code-4
3 modelsintfloatmultilingual-e5-large-instructRemove ×intfloatIntfloat: E5-Base-v2Remove ×voyageaiVoyageAI by MongoDB: voyage-code-4Remove ×
What’s differentThe Multilingual-E5 models, initialized from XLM-RoBERTa, support up to 512 tokens per input — any longer text will be silently truncated. To ensure optimal performance, always prefix inputs with “query:”…The 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-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...
DateApr 17, 2025ListedNov 22, 2023ListedAug 13, 2026Listed
Listed rateSee provider quotes$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.12 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints0 endpoints →1 endpoint →1 endpoint →
Context window51251232K
Max output—46028.8K
Parameters———
Open weightsNot reportedSupportedNot reported

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