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| 3 models | googleembeddinggemma-300mRemove × | togethercomputerTogether: Tev1 4B ExperimentalRemove × | QwenQwen3-Embedding-8BRemove × |
|---|---|---|---|
| What’s different | EmbeddingGemma is a 300M parameter multilingual open embedding model from Google DeepMind, designed for efficient deployment even on low-resource devices, producing high-quality text vector representations… | Tev1 4B Experimental is an experimental decision model from Together AI, a supervised fine-tune of Qwen3.5-4B trained to choose one option from a structured state, question, and list of 2-24... | 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 | Sep 16, 2025Listed | Sep 30, 2026Listed | Jun 10, 2025Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | See provider quotes | $0.042 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | $0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ |
| Provider endpoints | 0 endpoints → | 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 | 2K | 32.8K | 41K |
| Max output | — | 8 | 32K |
| Parameters | 300M | 4B | 8B |
| Open weights | Not reported | Supported | Supported |