MiniMax M2.1 Preview
MiniMax M2.1 Preview is an AI model published by MiniMaxAI, released on 2025-12-23, for AI model, with 2300.0B parameters, and 200K tokens context length, under the Modified MIT 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 |
| Modality | Input cache | Output cache |
|---|---|---|
| Text | $0.03 | $0.375 |
M2.1 currently shows benchmark results led by MMLU Pro (7 / 126, score 88), SWE-bench Verified (32 / 105, score 74.80), GPQA Diamond (68 / 177, score 81). 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 M2.1 Preview is an AI model published by MiniMaxAI, released on 2025-12-23, for AI model, with 2300.0B parameters, and 200K tokens context length, under the Modified MIT license.
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