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Comparison of bge-m3, Intfloat: Multilingual-E5-Large
2 modelsBAAIbge-m3Remove ×intfloatIntfloat: Multilingual-E5-LargeRemove ×
What’s differentBGE-M3 is a versatile text embedding model that supports multi-functionality, multi-linguality, and multi-granularity, allowing it to perform dense retrieval, multi-vector retrieval, and sparse retrieval in…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…
DateMay 27, 2024ListedJun 4, 2024Listed
Listed rate$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints1 endpoint →1 endpoint →
Context window8.2K512
Max output7.4K460
Parameters——
Open weightsSupportedSupported

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