MiniMax-M2
MiniMax-M2 is an AI model published by MiniMaxAI, released on 2025-10-27, for AI model, with 2300.0B parameters, and 205K tokens context length, requiring about 239.99 GB storage, under the MIT License license.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
| Modality | Input | Output |
|---|---|---|
| Text | $0.3 | $1.2 |
MiniMax M2 currently shows benchmark results led by LiveCodeBench (23 / 120, score 83), IF Bench (9 / 29, score 72.30), MMLU Pro (50 / 126, score 82). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.
MiniMax-M2 is an AI model published by MiniMaxAI, released on 2025-10-27, for AI model, with 2300.0B parameters, and 205K tokens context length, requiring about 239.99 GB storage, under the MIT License license.
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