Side by side
See the difference.
Scores, capabilities and costs for the models you’re considering.
Scroll to compare models →
| 3 models | MiniMaxAIMiniMax-M3Remove × | minimaxMiniMax: MiniMax M2.5Remove × | minimaxMiniMax: MiniMax M2.7Remove × |
|---|---|---|---|
| What’s different | MiniMax-M3 is a native multimodal model with 1M context. It has ~428B parameters and ~23B activated parameters. | 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... | MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates… |
| Date | Jun 2, 2026Listed | Feb 12, 2026Listed | Mar 18, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.28 in / $1.10 out/ 1M tokensdeepinfra · via Hugging Face · all routes ↗ | $0.27 in / $0.95 out/ 1M tokensVenice · via OpenRouter · all routes ↗venice | $0.21 in / $0.84 out/ 1M tokensGMICloud · via OpenRouter · all routes ↗gmicloud/fp8 · quantization=fp8 |
| Provider endpoints | 7 endpoints → | 12 endpoints → | 10 endpoints → |
Specifications | |||
| Context window | 1M | 204.8K | 204.8K |
| Max output | — | 32.8K | 131.1K |
| Parameters | — | — | — |
| Tool calling | Supported | Supported | Supported |
| Structured output | Supported | Supported | Supported |
| Image input | Supported | Not reported | Not reported |
| Reasoning | Not reported | Supported | Supported |
| Prompt caching | Not reported | Supported | Supported |
| Open weights | Supported | Supported | Supported |