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| 4 models | thenlpergte-baseRemove × | intfloatIntfloat: Multilingual-E5-LargeRemove × | kreaKrea 3 EditRemove × | BAAIbge-m3-multi-8kRemove × |
|---|---|---|---|---|
| What’s different | 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… | 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… | Edits and combines reference images using text instructions, with optional prompt expansion, output-size controls, and reproducible generation through a seed. | BGE-M3 is a multilingual text embedding model developed by BAAI, distinguished by its Multi-Linguality (supporting 100+ languages), Multi-Functionality (unified dense, multi-vector, and sparse retrieval),… |
| Date | Nov 22, 2023Listed | Jun 4, 2024Listed | Oct 14, 2026Listed | Sep 3, 2026Listed |
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 ↗ | $0.025/ megapixelfal · all routes ↗Output + reference images | See provider quotes |
| Provider endpoints | 1 endpoint → | 1 endpoint → | 1 endpoint → | 0 endpoints → |
Specifications | ||||
| Context window | 512 | 512 | — | 8.2K |
| Max output | 460 | 460 | — | — |
| Parameters | — | — | — | — |
| Open weights | Supported | Supported | Not reported | Not reported |