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Comparison of gte-large, Intfloat: Multilingual-E5-Large, Nemotron-3-Embed-8B
3 modelsthenlpergte-largeRemove ×intfloatIntfloat: Multilingual-E5-LargeRemove ×nvidiaNemotron-3-Embed-8BRemove ×
What’s differentThe GTE models are trained by Alibaba DAMO Academy. They are mainly based on the BERT framework and currently offer three different sizes of models, including GTE-large, GTE-base, and GTE-small. The GTE…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…Nemotron-3-Embed-8B is a multilingual text embedding model from NVIDIA, based on Ministral-3-8B, that maps text into 4096-dimensional dense vectors for retrieval and semantic similarity. Spanning 34…
DateNov 22, 2023ListedJun 4, 2024ListedJul 16, 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 window51251232.8K
Max output460460—
Parameters——8B
Open weightsSupportedSupportedNot reported

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