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| 2 models | sentence-transformersparaphrase-MiniLM-L6-v2Remove × | intfloatIntfloat: Multilingual-E5-LargeRemove × |
|---|---|---|
| What’s different | We present a sentence similarity model based on the Sentence Transformers architecture, which maps sentences to a 384-dimensional dense vector space. The model uses a pre-trained BERT encoder and applies… | 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… |
| Date | Mar 3, 2023Listed | Jun 4, 2024Listed |
API prices USD · provider configuration shown below | ||
| Listed rate | $0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | $0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ |
| Provider endpoints | 1 endpoint → | 1 endpoint → |
Specifications | ||
| Context window | 512 | 512 |
| Max output | 460 | 460 |
| Parameters | — | — |
| Open weights | Supported | Supported |