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| 3 models | sentence-transformersall-MiniLM-L12-v2Remove × | intfloatIntfloat: E5-Base-v2Remove × | QwenQwen3-Embedding-8BRemove × |
|---|---|---|---|
| What’s different | We present a sentence transformation model that generates semantically similar sentences. Our model is based on the Sentence-Transformers architecture and was trained on a large dataset of sentence pairs.… | The e5-base-v2 embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, producing efficient and high-quality semantic embeddings optimized for tasks such as… | 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… |
| Date | Feb 28, 2023Listed | Nov 22, 2023Listed | Jun 10, 2025Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | $0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | $0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ |
| Provider endpoints | 1 endpoint → | 1 endpoint → | 1 endpoint → |
Benchmarks Each result retains its evaluation configuration | |||
| FreshStack · MTEB 1.38.43 ↗MTEB 1.38.43; test/default; dataset 7a20df1a | Not reported | Not reported | 0.43017 ↗Revision 4e423935; test/defaultContributor reported |
Specifications | |||
| Context window | 512 | 512 | 41K |
| Max output | 460 | 460 | 32K |
| Parameters | — | — | 8B |
| Open weights | Supported | Supported | Supported |