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| 3 models | googleGoogle: Gemini Embedding 2Remove × | googleembeddinggemma-2Remove × | intfloatIntfloat: Multilingual-E5-LargeRemove × |
|---|---|---|---|
| What’s different | Gemini Embedding 2 is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic search and retrieval-augmented generation (RAG). It… | EmbeddingGemma 2 is a 740M parameter multimodal embedding model from Google DeepMind that maps text (incl. code), images, video and audio, alone or interleaved, into a single 768-dimensional vector space,… | 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 | May 20, 2026Listed | Oct 8, 2026Listed | Jun 4, 2024Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.20 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | See provider quotes | $0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ |
| Provider endpoints | 1 endpoint → | 0 endpoints → | 1 endpoint → |
Specifications | |||
| Context window | 8.2K | 8.2K | 512 |
| Max output | 7.4K | — | 460 |
| Parameters | — | — | — |
| Image input | Supported | Not reported | Not reported |
| Audio input | Supported | Not reported | Not reported |
| Video input | Supported | Not reported | Not reported |
| Open weights | Not reported | Not reported | Supported |