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| 3 models | minimaxMiniMax: MiniMax M2Remove × | togethercomputerTogether: Tev1 4B ExperimentalRemove × | Briaremove_background_guidedRemove × |
|---|---|---|---|
| What’s different | MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier… | Tev1 4B Experimental is an experimental decision model from Together AI, a supervised fine-tune of Qwen3.5-4B trained to choose one option from a structured state, question, and list of 2-24... | 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 | Oct 23, 2025Listed | Sep 30, 2026Listed | Oct 14, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.255 in / $1.02 out/ 1M tokensMinimax · via OpenRouter · all routes ↗minimax/fp8 · quantization=fp8 | $0.042 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | See provider quotes |
| Provider endpoints | 3 endpoints → | 1 endpoint → | 0 endpoints → |
Specifications | |||
| Context window | 204.8K | 32.8K | — |
| Max output | 131.1K | 8 | — |
| Parameters | — | 4B | — |
| Tool calling | Supported | Not reported | Not reported |
| Structured output | Supported | Not reported | Not reported |
| Reasoning | Supported | Not reported | Not reported |
| Open weights | Supported | Supported | Not reported |