o1-mini is a compact, cost-optimized variant of OpenAI's o1 reasoning model, designed to bring chain-of-thought reasoning to applications where the full o1 model would be too expensive or slow. It retains the core reasoning mechanism — internally working through problems before answering — but is calibrated for tasks that need logical rigor without the breadth of world knowledge that larger models provide.
OpenAI positioned o1-mini as particularly strong on coding, math, and structured reasoning tasks relative to its cost, making it a practical choice for pipelines that benefit from deliberate reasoning but operate under inference budget constraints. It is faster and cheaper than full o1 while preserving meaningful accuracy gains over standard GPT-4 Turbo on these categories.
Key Features
Chain-of-thought reasoning in a smaller, faster, lower-cost package
Competitive coding and mathematical reasoning for its size tier
More predictable and structured outputs on logic-heavy tasks
Lower per-token cost than full o1 while retaining core reasoning benefits
Well-suited for automated pipelines requiring consistent deductive accuracy
Ideal Use Cases
Automated code review and bug-finding in CI/CD pipelines
Math tutoring applications requiring step-by-step correctness
Structured data extraction requiring logical inference
Cost-conscious deployments needing reasoning beyond standard chat models
Example Prompts for o1-mini
Technical Specifications
| Provider | OpenAI |
| Category | Reasoning |
| Modality | Text -> Text (reasoning) |
Frequently Asked Questions
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