ReasoningOpenAI

o1-mini

o1-mini is OpenAI's cost-efficient reasoning model designed for coding, math, and science tasks with a 128K token context window.

Context 128K
Tier Reasoning
Knowledge Jun 2024
Tools Supported
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API Pricing

No pricing data available for this model at the moment.

Prices updated daily. Last check: 4/14/2026

Model Details

General

Creator
OpenAI
Family
o-series
Tier
Reasoning
Context Window
128K
Knowledge Cutoff
Jun 2024
Modalities
Text

Capabilities

Tool Calling
Yes
Open Source
No
Subtypes
Chat Completion

Strengths & Limitations

  • Specialized reasoning architecture for complex mathematical and logical problems
  • 128K token context window for processing substantial amounts of code or text
  • Tool calling support for integration with external systems and APIs
  • More cost-effective than the full o1 model while retaining core reasoning capabilities
  • Designed specifically for coding, mathematics, and scientific problem-solving
  • Systematic approach to problem-solving with extended thinking time
  • Strong performance on tasks requiring multi-step logical reasoning
  • Text-only modality with no image or multimodal input support
  • Proprietary model with no access to weights or local deployment
  • Slower response times compared to standard chat models due to reasoning process
  • Knowledge cutoff of June 2024 may limit awareness of recent developments
  • Smaller context window than some competing models in the reasoning category

Key Features

•128K token context window
•Tool calling with structured outputs
•Chat completion API interface
•Extended reasoning processing time
•Mathematical problem-solving capabilities
•Code analysis and debugging features
•Scientific reasoning and analysis
•Multi-step logical problem solving

About o1-mini

o1-mini is OpenAI's cost-efficient reasoning model within the o-series family, positioned as a more affordable alternative to the full o1 model while maintaining strong reasoning capabilities. The model specializes in mathematical reasoning, coding problems, and scientific tasks where step-by-step logical thinking is required. The model operates with a 128K token context window and supports text-only interactions through chat completions. o1-mini includes tool calling capabilities and has a knowledge cutoff of June 2024. Unlike traditional language models that generate responses quickly, o1-mini uses extended reasoning time to work through complex problems systematically before providing answers. o1-mini is primarily used for applications requiring multi-step reasoning such as debugging code, solving mathematical problems, scientific analysis, and logical problem-solving where accuracy is more important than response speed. It serves as a middle ground between OpenAI's general-purpose models and the more capable but expensive o1 model.

Common Use Cases

o1-mini is well-suited for applications requiring systematic reasoning and problem-solving capabilities, particularly in coding, mathematics, and scientific domains. Its cost-efficient design makes it appropriate for educational platforms teaching programming or mathematics, code review and debugging workflows, mathematical computation tasks, and scientific analysis where logical reasoning is more important than speed. The model excels in scenarios where problems require breaking down complex issues into logical steps, making it valuable for technical support, algorithm development, research assistance, and analytical tasks that benefit from methodical thinking rather than rapid response generation.

Frequently Asked Questions

How much does o1-mini cost per million tokens?

o1-mini pricing varies by provider and usage type. Check the pricing table above for current rates across all providers offering this model.

What is o1-mini best used for?

o1-mini excels at mathematical reasoning, coding problems, debugging, scientific analysis, and any task requiring systematic step-by-step problem solving. It's designed for scenarios where reasoning accuracy is more important than response speed.

How does o1-mini differ from the standard o1 model?

o1-mini is positioned as a more cost-efficient alternative to the full o1 model while maintaining core reasoning capabilities. It offers similar systematic problem-solving approaches but at a lower cost point, making it more accessible for applications that need reasoning capabilities without requiring the full performance of the flagship o1 model.