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Comparison of Intfloat: Multilingual-E5-Large, bge-m3
2 modelsintfloatIntfloat: Multilingual-E5-LargeRemove ×BAAIbge-m3Remove ×
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…BGE-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…
DateJun 4, 2024ListedMay 27, 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 window5128.2K
Max output4607.4K
Parameters——
Open weightsSupportedSupported

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