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| 3 models | intfloatmultilingual-e5-large-instructRemove × | googleembeddinggemma-300mRemove × | thenlpergte-baseRemove × |
|---|---|---|---|
| What’s different | The Multilingual-E5 models, initialized from XLM-RoBERTa, support up to 512 tokens per input — any longer text will be silently truncated. To ensure optimal performance, always prefix inputs with “query:”… | EmbeddingGemma is a 300M parameter multilingual open embedding model from Google DeepMind, designed for efficient deployment even on low-resource devices, producing high-quality text vector representations… | The 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… |
| Date | Apr 17, 2025Listed | Sep 16, 2025Listed | Nov 22, 2023Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | See provider quotes | See provider quotes | $0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ |
| Provider endpoints | 0 endpoints → | 0 endpoints → | 1 endpoint → |
Specifications | |||
| Context window | 512 | 2K | 512 |
| Max output | — | — | 460 |
| Parameters | — | 300M | — |
| Open weights | Not reported | Not reported | Supported |