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Comparison of Intfloat: E5-Large-v2, Intfloat: Multilingual-E5-Large, Krea: K3 Edit
3 modelsintfloatIntfloat: E5-Large-v2Remove ×intfloatIntfloat: Multilingual-E5-LargeRemove ×kreaKrea: K3 EditRemove ×
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-large embedding model encodes sentences, paragraphs, and documents across over 90 languages into a 1024-dimensional dense vector space, delivering robust semantic embeddings optimized…Edits one to eight reference images from a text prompt, returning one image.
DateNov 22, 2023ListedJun 4, 2024ListedOct 15, 2026Listed
Listed rate$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗See provider quotes
Provider endpoints1 endpoint →1 endpoint →0 endpoints →
Context window51251265.5K
Max output46046059K
Parameters———
Image inputNot reportedNot reportedSupported
Open weightsSupportedSupportedNot reported

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