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Comparison of multilingual-e5-large-instruct, Intfloat: Multilingual-E5-Large, Intfloat: E5-Base-v2
3 modelsintfloatmultilingual-e5-large-instructRemove ×intfloatIntfloat: Multilingual-E5-LargeRemove ×intfloatIntfloat: E5-Base-v2Remove ×
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 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…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…
DateApr 17, 2025ListedJun 4, 2024ListedNov 22, 2023Listed
Listed rateSee provider quotes$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints0 endpoints →1 endpoint →1 endpoint →
Context window512512512
Max output—460460
Parameters———
Open weightsNot reportedSupportedSupported

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