R1
DeepSeek's efficiency model. Context window: 164K tokens.
Scores by test
Methodology →What you need to know
R1 distinguishes itself through high-level reasoning and complex problem-solving capabilities. With a 93.1% score on MATH Level 5 and 53.3% on AIME 2025, the model is optimized for quantitative and strategic tasks. Internal testing confirms this strength, yielding perfect scores in strategic analysis, creative problem solving, and faithfulness.
The model offers a competitive price point with a blended cost of $2.05/MTok, making high-end reasoning accessible for budget-conscious deployments. While it handles multilingual tasks and persona consistency perfectly, it exhibits significant failures in safety calibration and basic classification. Developers should note that its 64K context window is modest compared to some competitors, though it maintains a strong 4/5 internal rating for long-context performance.
Use this model for complex mathematical reasoning, strategic planning, or multilingual applications where high accuracy and persona stability are required. Skip this model for tasks requiring strict safety guardrails, simple classification, or massive context windows.
Strengths — Top 3
Relative weaknesses — Bottom 3
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