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Comparison of Intfloat: E5-Large-v2, multilingual-e5-large-instruct, Respan: Span-02
3 modelsintfloatIntfloat: E5-Large-v2Remove ×intfloatmultilingual-e5-large-instructRemove ×respanRespan: Span-02Remove ×
What’s differentThe e5-large-v2 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-accuracy semantic embeddings optimized for retrieval, semantic…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:”…Set a thinking deadline in milliseconds; returns typed decisions or direct numbers with confidence, and accepts up to four images.
DateNov 22, 2023ListedApr 17, 2025ListedOct 16, 2026Listed
Listed rate$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗See provider quotes$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints1 endpoint →0 endpoints →1 endpoint →
Context window512512131.1K
Max output460—118K
Parameters———
Image inputNot reportedNot reportedSupported
Open weightsSupportedNot reportedNot reported

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