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| 3 models | BAAIbge-m3-multiRemove × | intfloatIntfloat: E5-Large-v2Remove × | voyageaiVoyageAI by MongoDB: voyage-multimodal-3.5Remove × |
|---|---|---|---|
| What’s different | 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),… | The 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… | voyage-multimodal-3.5 is a state-of-the-art multimodal embedding model capable of vectorizing not only text, images, and video individually, but also content that interleaves all three modalities. It… |
| Date | Feb 28, 2025Listed | Nov 22, 2023Listed | Jul 27, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | See provider quotes | $0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | $0.12 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ |
| Provider endpoints | 0 endpoints → | 1 endpoint → | 1 endpoint → |
Specifications | |||
| Context window | 512 | 512 | 32K |
| Max output | — | 460 | 28.8K |
| Parameters | — | — | — |
| Image input | Not reported | Not reported | Supported |
| Open weights | Not reported | Supported | Not reported |