ReasoningOpenAI

o3-mini

o3-mini is OpenAI's cost-effective reasoning model in the o-series family, designed for tasks requiring deliberate problem-solving with a 200K token context window.

Context 200K
Tier Reasoning
Knowledge Oct 2024
Tools Supported
Input from
$1.10 / 1M tokens
across 1 provider

API Pricing

ProviderInput / 1MOutput / 1MSpeedTTFTUpdated
$1.10$4.40162 t/s19.0s4/14/2026

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

Model Details

General

Creator
OpenAI
Family
o-series
Tier
Reasoning
Context Window
200K
Knowledge Cutoff
Oct 2024
Modalities
Text

Capabilities

Tool Calling
Yes
Open Source
No
Subtypes
Chat Completion

Strengths & Limitations

  • Specialized reasoning architecture for deliberate problem-solving tasks
  • 200K token context window for handling long documents and complex problems
  • Tool calling support with function execution capabilities
  • More cost-effective than flagship o3 while maintaining reasoning capabilities
  • Output rate of 150.69 tokens per second for steady response generation
  • Knowledge cutoff of October 2024 for relatively current information
  • Part of OpenAI's o-series reasoning model family
  • Text-only modality with no image or multimodal input support
  • High time to first token at 7,676ms due to reasoning processing overhead
  • Proprietary model with no open-source weights available
  • Optimized for reasoning tasks rather than general conversational use
  • Slower response times compared to standard chat models

Key Features

200,000 token context window
Tool calling with function execution
Chat completion interface
Reasoning-optimized processing architecture
Streaming response support
Text-based input and output
Step-by-step problem solving capabilities
Integration with OpenAI API platform

About o3-mini

o3-mini is OpenAI's reasoning-tier model in the o-series family, positioned as a more cost-effective alternative to the flagship o3 model while maintaining strong problem-solving capabilities. The model is designed for tasks that require deliberate reasoning and step-by-step problem solving rather than fast conversational responses. The model operates with a 200,000 token context window and supports text-only interactions through chat completion. It includes tool calling capabilities and maintains a knowledge cutoff of October 2024. Performance benchmarks show an output rate of 150.69 tokens per second with a time to first token of 7,676 milliseconds, reflecting the reasoning model's deliberate processing approach that prioritizes accuracy over speed. o3-mini targets use cases where reasoning quality matters more than response speed, such as mathematical problem solving, code debugging, scientific analysis, and complex logical tasks. It provides an accessible entry point to OpenAI's reasoning model capabilities while offering better cost efficiency than the full o3 model for applications that don't require the highest tier of reasoning performance.

Common Use Cases

o3-mini is designed for applications requiring careful reasoning and problem-solving rather than rapid conversational responses. It excels at mathematical problem solving, complex code analysis and debugging, scientific research tasks, logical reasoning challenges, and multi-step analytical work. The model is particularly suitable for educational applications, research assistance, technical documentation analysis, and scenarios where accuracy and thoughtful processing are more important than response speed. Its cost-effective positioning makes it accessible for reasoning-heavy workloads that don't require the full capabilities of the flagship o3 model.

Frequently Asked Questions

How much does o3-mini cost per million tokens?

o3-mini pricing varies by provider and usage type. Check the pricing table above for current rates across all available providers offering o3-mini access.

What is o3-mini best used for?

o3-mini is optimized for reasoning tasks that require deliberate problem-solving, such as mathematical calculations, code debugging, scientific analysis, and complex logical reasoning. Its design prioritizes accuracy and step-by-step thinking over response speed.

How does o3-mini compare to the full o3 model?

o3-mini provides a more cost-effective option within OpenAI's o-series reasoning family while maintaining strong problem-solving capabilities. It offers the same 200K context window and tool calling features but is positioned as a more accessible alternative to the flagship o3 model for reasoning tasks that don't require the highest tier of performance.