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| 3 models | googleGoogle: Gemini Embedding 2Remove × | intfloatIntfloat: E5-Large-v2Remove × | voyageaiVoyageAI by MongoDB: voyage-code-4Remove × |
|---|---|---|---|
| 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… | 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-code-4 is a code embedding model from Voyage AI, a MongoDB company. It is designed for coding agents and code retrieval, with Matryoshka embeddings at 2048, 1024, 512, and 256... |
| Date | May 20, 2026Listed | Nov 22, 2023Listed | Aug 13, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.20 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | $0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | $0.12 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ |
| Provider endpoints | 1 endpoint → | 1 endpoint → | 1 endpoint → |
Specifications | |||
| Context window | 8.2K | 512 | 32K |
| Max output | 7.4K | 460 | 28.8K |
| 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 | Supported | Not reported |