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| 3 models | intfloatIntfloat: E5-Base-v2Remove × | inclusionAIMing-Image-0.1-DesignRemove × | googleembeddinggemma-2Remove × |
|---|---|---|---|
| What’s different | 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… | Design-native, open-weight text-to-image (6B) — ranked #1 among open-weight models on Artificial Analysis's UI/UX Design leaderboard. Renders legible UI and poster text plus cohesive graphics, illustration… | EmbeddingGemma 2 is a 740M parameter multimodal embedding model from Google DeepMind that maps text (incl. code), images, video and audio, alone or interleaved, into a single 768-dimensional vector space,… |
| Date | Nov 22, 2023Listed | Sep 22, 2026Released | Oct 8, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | See provider quotes | See provider quotes |
| Provider endpoints | 1 endpoint → | 0 endpoints → | 0 endpoints → |
Benchmarks Each result retains its evaluation configuration | |||
| AA Image ↗2.1 | Not reported | 998.76 ↗Text-to-image · all categoriesIndependent result95% CI 989.76–1,007.76 · n=20,016 | Not reported |
Specifications | |||
| Context window | 512 | — | 8.2K |
| Max output | 460 | — | — |
| Parameters | — | — | — |
| Open weights | Supported | Supported | Not reported |