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| 3 models | Unknowntext-embedding-3-smallRemove × | intfloatIntfloat: E5-Large-v2Remove × | voyageaiVoyageAI by MongoDB: voyage-4-liteRemove × |
|---|---|---|---|
| What’s different | 8.2K context | 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-4-lite is a lightweight, general-purpose embedding model optimized for low latency and cost. Enabled by Matryoshka learning and quantization-aware training, voyage-4-lite supports embeddings in 2048,… |
| Date | Oct 16, 2026Discovered | Nov 22, 2023Listed | Jul 27, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.02 in / $0.00 out/ 1M tokensExperiential · all routes ↗Standard list rate | $0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | $0.02 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 | — | 460 | 28.8K |
| Parameters | — | — | — |
| Open weights | Not reported | Supported | Not reported |