Model Overview Card for OpenAI o3-mini

Basic Information

• Model Name: OpenAI o3-mini
• Developer/Creator: OpenAI
• Release Date: January 30, 2025
• Version: 1.0
• Model Type: Large Language Model (LLM)

Description

Overview:

OpenAI o3-mini is a compact yet powerful version of the o3 model series, designed to enhance reasoning capabilities while maintaining efficiency and performance. This model is particularly focused on tasks that require structured reasoning and prompt adherence, making it ideal for applications in programming, mathematics, and various logical challenges.

Key Features:

• Dense Transformer Architecture: Utilizes a dense transformer architecture that engages all model parameters for each input token, ensuring consistent performance across diverse tasks.
• Extended Context Length: Capable of processing up to 200K tokens, allowing for extensive context retention during interactions.
• Deliberative Alignment Safety Mechanism: Incorporates a new safety mechanism that analyzes prompts against safety specifications to better identify and mitigate harmful content.
• High Performance on Benchmarks: Achieves competitive scores on various benchmarks, including an ARC-AGI score of 32% and AIME 2024 score of 83.3%.
• Open Source Availability: Released under an MIT license, promoting broad usage and modification.

Intended Use:

OpenAI o3-mini is designed for developers, researchers, and educators who require advanced reasoning capabilities in their applications. It is particularly useful for tasks involving coding assistance, mathematical problem-solving, and logical reasoning.

Language Support:

The model primarily supports English but can accommodate multiple languages depending on user requirements.

Technical Details

Architecture:

OpenAI o3-mini employs a dense transformer architecture optimized for reasoning tasks. Key architectural features include:

• Total Parameters: Estimated around 200 billion.
• Attention Mechanisms: Engages all parameters for each token processed to ensure robust performance.
• Reinforcement Learning Training: Utilizes reinforcement learning techniques to optimize reasoning capabilities.

Training Data:

The model was trained on a vast dataset consisting of diverse sources of text, including books, articles, and code repositories.

• Data Source and Size: The training dataset includes over 14 trillion tokens from publicly available texts.
• Knowledge Cutoff: The model's knowledge is current as of January 2025.
• Diversity and Bias: The training data was curated to minimize biases while maximizing diversity in topics and styles, ensuring robust performance across different scenarios.

Performance Metrics:

OpenAI o3-mini has demonstrated impressive performance metrics:

Usage

Code Samples:

The model is available on the AI/ML API platform as "OpenAI o3 mini" .

API Documentation:

Detailed API Documentation is available here.

Ethical Guidelines

OpenAI emphasizes ethical considerations in AI development by promoting transparency regarding the model's capabilities and limitations. The organization encourages responsible usage to prevent misuse or harmful applications of generated content.

Licensing

OpenAI o3-mini is available under an open-source MIT license that allows both research and commercial usage rights while ensuring compliance with ethical standards regarding creator rights.

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Get OpenAI o3 mini API here.