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Comparison of Intfloat: E5-Large-v2, Intfloat: Multilingual-E5-Large, Together: Tev1 4B Experimental
3 modelsintfloatIntfloat: E5-Large-v2Remove ×intfloatIntfloat: Multilingual-E5-LargeRemove ×togethercomputerTogether: Tev1 4B ExperimentalRemove ×
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…Tev1 4B Experimental is an experimental decision model from Together AI, a supervised fine-tune of Qwen3.5-4B trained to choose one option from a structured state, question, and list of 2-24...
DateNov 22, 2023ListedJun 4, 2024ListedSep 30, 2026Listed
Listed rate$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.042 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints1 endpoint →1 endpoint →1 endpoint →
Context window51251232.8K
Max output4604608
Parameters——4B
Open weightsSupportedSupportedSupported

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