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What is OpenAI o4-mini?

The o4-mini model, a refined version of the o3, was engineered to offer enhanced reasoning abilities and improved efficiency. Designed for tasks requiring intricate problem-solving, it stands out for its ability to handle complex challenges with precision. This model offers a streamlined alternative to the o3, delivering similar capabilities while being more resource-efficient. OpenAI's commitment to pushing the boundaries of AI technology is evident in the o4-mini’s performance, making it a valuable tool for a wide range of applications. As part of a broader strategy, the o4-mini serves as an important step in refining OpenAI's portfolio before the release of GPT-5. Its optimized design positions it as a go-to solution for users seeking faster, more intelligent AI models.

What is GPT-5 mini?

GPT-5 mini is a faster, more affordable variant of OpenAI’s advanced GPT-5 language model, specifically tailored for well-defined and precise tasks that benefit from high reasoning ability. It accepts both text and image inputs (image input only), and generates high-quality text outputs, supported by a large 400,000-token context window and a maximum of 128,000 tokens in output, enabling complex multi-step reasoning and detailed responses. The model excels in providing rapid response times, making it ideal for use cases where speed and efficiency are critical, such as chatbots, customer service, or real-time analytics. GPT-5 mini’s pricing structure significantly reduces costs, with input tokens priced at $0.25 per million and output tokens at $2 per million, offering a more economical option compared to the flagship GPT-5. While it supports advanced features like streaming, function calling, structured output generation, and fine-tuning, it does not currently support audio input or image generation capabilities. GPT-5 mini integrates seamlessly with multiple API endpoints including chat completions, responses, embeddings, and batch processing, providing versatility for a wide array of applications. Rate limits are tier-based, scaling from 500 requests per minute up to 30,000 per minute for higher tiers, accommodating small to large scale deployments. The model also supports snapshots to lock in performance and behavior, ensuring consistency across applications. GPT-5 mini is ideal for developers and businesses seeking a cost-effective solution with high reasoning power and fast throughput. It balances cutting-edge AI capabilities with efficiency, making it a practical choice for applications demanding speed, precision, and scalability.

Media

No images available

Media

Integrations Supported

Brokk
ChatGPT
ChatGPT Enterprise
ChatGPT Plus
ChatGPT Pro
Editee
Anara
PyGPT
Simtheory
T3 Chat

Integrations Supported

Brokk
ChatGPT
ChatGPT Enterprise
ChatGPT Plus
ChatGPT Pro
Editee
Amarsia
CSS
Cheaper Inference
Codex CLI
HTML
Microsoft Foundry Models
Shiori
Transor
Twigg

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$0.25 per 1M tokens
Input: $0.25 per 1M tokens
Output: $2 per 1M tokens

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

OpenAI

Date Founded

2015

Company Location

United States

Company Website

openai.com

Company Facts

Organization Name

OpenAI

Date Founded

2015

Company Location

United States

Company Website

platform.openai.com/docs/models/gpt-5-mini

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Small Language Models

Not specified

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