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| 3 models | googleembeddinggemma-300mRemove × | kreaKrea 3 EditRemove × | 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… | Edits and combines reference images using text instructions, with optional prompt expansion, output-size controls, and reproducible generation through a seed. | 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 | Oct 14, 2026Listed | Jun 10, 2025Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | See provider quotes | $0.025/ megapixelfal · all routes ↗Output + reference images | $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 | — | 41K |
| Max output | — | — | 32K |
| Parameters | 300M | — | 8B |
| Open weights | Not reported | Not reported | Supported |