MiniMax: MiniMax M3
minimax's mid-tier model. Long-context specialist with 1.0M window.
Scores by test
Methodology →What you need to know
MiniMax M3 is defined by its high-performance ceiling across complex logic and agentic tasks. With perfect internal scores in tool calling, structured output, and agentic planning, it is engineered for autonomous workflows that require strict adherence to schemas and multi-step reasoning. This technical capability is paired with a 1.0M token context window, making it suitable for processing massive datasets without losing coherence.
The model is priced at $0.30 per million input tokens and $1.20 per million output tokens. Given its overall rank of 12th out of 105 models and an average internal score of 4.58, the blended cost of $0.975 per million tokens represents a high value-to-performance ratio for developers needing frontier-level reasoning without the premium pricing of top-tier proprietary models.
Performance is inconsistent in specific utility areas. While it excels at strategic analysis and multilingual tasks, it struggles with safety calibration and basic classification. Developers should expect a higher rate of false positives or unfiltered responses, requiring more robust external guardrails than those used with more conservative models.
Use this model if you are building complex agents, automating structured data extraction, or working with extremely long documents. Skip this model if your application requires strict safety alignment or high-precision classification.
Strengths — Top 3
Relative weaknesses — Bottom 3
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