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| 3 models | googleembeddinggemma-300mRemove × | intfloatmultilingual-e5-large-instructRemove × | ideogramIdeogram V4.5 Text to ImageRemove × |
|---|---|---|---|
| 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… | The Multilingual-E5 models, initialized from XLM-RoBERTa, support up to 512 tokens per input — any longer text will be silently truncated. To ensure optimal performance, always prefix inputs with “query:”… | Generate high-quality images, posters, and logos with Ideogram 4.5, with accurate text rendering and low, medium, or high quality tiers. |
| Date | Sep 16, 2025Listed | Apr 17, 2025Listed | Sep 30, 2026Released |
API prices USD · provider configuration shown below | |||
| Listed rate | See provider quotes | See provider quotes | See provider quotes |
| Provider endpoints | 0 endpoints → | 0 endpoints → | 1 endpoint → |
Benchmarks Each result retains its evaluation configuration | |||
| AA Image ↗2.1 | Not reported | Not reported | 1,015.68 ↗Text-to-image · all categories · quality=highIndependent result95% CI 1,000.68–1,030.68 · n=2,634 |
Specifications | |||
| Context window | 2K | 512 | — |
| Max output | — | — | — |
| Parameters | 300M | — | — |