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| 3 models | intfloatmultilingual-e5-large-instructRemove × | minimaxMiniMax: MiniMax M2.1Remove × | googleembeddinggemma-2Remove × |
|---|---|---|---|
| What’s different | 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:”… | MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a… | 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 | Apr 17, 2025Listed | Dec 23, 2025Listed | Oct 8, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | See provider quotes | $0.30 in / $1.20 out/ 1M tokensMinimax · via OpenRouter · all routes ↗minimax/fp8 · quantization=fp8 | See provider quotes |
| Provider endpoints | 0 endpoints → | 3 endpoints → | 0 endpoints → |
Specifications | |||
| Context window | 512 | 204.8K | 8.2K |
| Max output | — | 131.1K | — |
| Parameters | — | — | — |
| Tool calling | Not reported | Supported | Not reported |
| Structured output | Not reported | Supported | Not reported |
| Reasoning | Not reported | Supported | Not reported |
| Prompt caching | Not reported | Supported | Not reported |
| Open weights | Not reported | Supported | Not reported |