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| 3 models | minimaxMiniMax: MiniMax M2.5Remove × | googleembeddinggemma-2Remove × | Briaremove_background_guidedRemove × |
|---|---|---|---|
| What’s different | MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1... | 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,… | Prompt-guided background removal by Bria: tell it what to keep or what to remove and get a clean cutout with true transparency, at the original resolution with the original pixels untouched. Trained… |
| Date | Feb 12, 2026Listed | Oct 8, 2026Listed | Oct 14, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.27 in / $0.95 out/ 1M tokensVenice · via OpenRouter · all routes ↗venice | See provider quotes | See provider quotes |
| Provider endpoints | 12 endpoints → | 0 endpoints → | 0 endpoints → |
Specifications | |||
| Context window | 204.8K | 8.2K | — |
| Max output | 32.8K | — | — |
| Parameters | — | — | — |
| Tool calling | Supported | Not reported | Not reported |
| Structured output | Supported | Not reported | Not reported |
| Reasoning | Supported | Not reported | Not reported |
| Prompt caching | Supported | Not reported | Not reported |
| Open weights | Supported | Not reported | Not reported |