MiniMax: MiniMax M1
minimax's efficiency model. Long-context specialist with 1M window.
Scores by test
Methodology →What you need to know
MiniMax M1 distinguishes itself through high-tier performance in complex reasoning and execution. It achieves top marks in strategic analysis, agentic planning, and tool calling, making it a strong candidate for autonomous workflows and multi-step technical orchestration. This capability extends to multilingual support and a 1M token context window, allowing for deep analysis of large datasets across different languages.
The model exhibits significant failures in data formatting and precision tasks. It is ineffective at handling tabular data and struggles with classification and constrained rewriting. These weaknesses suggest that while the model can plan a complex strategy, it cannot reliably format that strategy into a strict schema or extract specific categories from text.
At a blended cost of $1.75 per million tokens, the model is priced competitively for its reasoning capabilities, though its overall rank of 91 out of 105 suggests it lacks the general-purpose versatility of leading models in its price tier. You are paying for specialized agentic strength rather than broad reliability.
Use this model if you are building complex agents that require high-level planning, tool integration, or long-context multilingual analysis. Skip this model if your use case requires precise data extraction, tabular processing, or strict adherence to formatting constraints.
Strengths — Top 3
Relative weaknesses — Bottom 3
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