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| 3 models | QwenQwen3-Embedding-4BRemove × | intfloatIntfloat: Multilingual-E5-LargeRemove × | voyageaiVoyageAI by MongoDB: voyage-4-liteRemove × |
|---|---|---|---|
| What’s different | The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3… | 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… | 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 | Jun 10, 2025Listed | Jun 4, 2024Listed | Jul 27, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.02 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | $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 | 32.8K | 512 | 32K |
| Max output | 29.5K | 460 | 28.8K |
| Parameters | 4B | — | — |
| Open weights | Supported | Supported | Not reported |