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Comparison of Intfloat: Multilingual-E5-Large, Intfloat: E5-Base-v2, multilingual-e5-large-instruct
3 modelsintfloatIntfloat: Multilingual-E5-LargeRemove ×intfloatIntfloat: E5-Base-v2Remove ×intfloatmultilingual-e5-large-instructRemove ×
What’s differentThe 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…The 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:”…
DateJun 4, 2024ListedNov 22, 2023ListedApr 17, 2025Listed
Listed rate$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗See provider quotes
Provider endpoints1 endpoint →1 endpoint →0 endpoints →
Context window512512512
Max output460460—
Parameters———
Open weightsSupportedSupportedNot reported

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