GPT-4o mini
OpenAI's most cost-efficient small model, GPT-4o mini offers multimodal intelligence and high-speed performance at a significantly lower price point.
openaiGPT-4oJuly 18, 2024About GPT-4o mini
Learn about GPT-4o mini's capabilities, features, and how it can help you achieve better results.
A New Standard for Small Models
GPT-4o mini represents a significant leap in AI efficiency, designed to replace GPT-3.5 Turbo as the go-to model for developers. Built with a native multimodal architecture, it delivers GPT-4 class performance at a fraction of the cost and latency. It features a massive 128,000 token context window and supports complex outputs of up to 16,384 tokens, making it ideal for processing long-form documents and high-volume data streams.
Intelligence Meets Affordability
Unlike previous small models that sacrificed intelligence for speed, GPT-4o mini maintains high reasoning capabilities across text and vision tasks. It is 60% cheaper than GPT-3.5 Turbo and significantly more capable, scoring 82% on the MMLU benchmark. This model is specifically optimized for applications where low latency and high reliability are paramount, such as real-time customer assistants and large-scale data classification engines.
Use Cases
Discover the different ways you can use GPT-4o mini to achieve great results.
Customer Support Automation
Handling high volumes of customer inquiries with low latency and high accuracy at a fraction of the cost.
Content Summarization
Processing large documents or long-form content into concise summaries within the 128k context window.
Data Extraction
Converting unstructured text or images into structured data formats like JSON for database ingestion.
Multilingual Translation
Providing real-time translation across dozens of languages for chat applications and global communication.
Educational Tutoring
Serving as an interactive study assistant for students needing help with math, science, and language arts.
Basic Vision Tasks
Analyzing images to identify objects, extract text via OCR, or provide descriptions for accessibility.
Strengths
Limitations
API Quick Start
openai/gpt-4o-mini
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const completion = await openai.chat.completions.create({
messages: [{ role: "user", content: "Explain quantum physics." }],
model: "gpt-4o-mini",
});
console.log(completion.choices[0].message.content);
}
main();Install the SDK and start making API calls in minutes.
Community Feedback
See what the community thinks about GPT-4o mini
“GPT-4o mini has basically killed the market for fine-tuning older models for basic RAG. The costs are too low to ignore.”
“The speed is just insane. I'm getting tokens back almost instantly for my translation agent.”
“OpenAI really forced the hands of Anthropic and Google with this pricing. $0.15 for 1M tokens is a new floor.”
“I swapped out 3.5 for mini and the logic improvement was visible in the first five minutes of testing.”
“It is finally cheap enough to use LLMs for basic data cleaning at scale without a massive cloud bill.”
“The vision performance for OCR is actually better than some specialized models that cost 10x more.”
Related Videos
Watch tutorials, reviews, and discussions about GPT-4o mini
“It is faster and cheaper than GPT-3.5 Turbo across the board.”
“The vision capabilities for a model this small are genuinely surprising.”
“Pricing is basically a race to zero now with this release.”
“It manages to keep the context window massive while being tiny.”
“Benchmarks show it beating Claude Haiku in almost every category.”
“GPT 40 mini is a lightweight model so it's much faster than GPT 40.”
“It's way way faster than GPT 4.”
“For daily tasks, most users won't even notice the reasoning difference.”
“The image recognition is very consistent for basic objects.”
“It handles complex instructions much better than the old 3.5 model.”
“It currently outperforms their gbd4 on the chat preferences in the LMC leaderboard.”
“Everything looks perfect and you know this particular receipt looks like a typical receipt.”
“The response time is practically sub-second for short prompts.”
“It is very effective at summarizing long PDFs through the API.”
“You can run millions of tokens for just a few dollars.”
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Pro Tips
Expert tips to help you get the most out of GPT-4o mini and achieve better results.
Use for RAG
Utilize the low input cost to perform extensive Retrieval Augmented Generation without high expenses.
Structure with JSON Mode
Use the JSON mode or function calling parameters to ensure consistent data structures for backend workflows.
Batch Processing
Employ OpenAI's Batch API with this model to reduce costs by 50% for non-urgent tasks.
Temperature Tuning
Set a lower temperature between 0.1 and 0.3 for factual extraction tasks to maximize accuracy.
Testimonials
What Our Users Say
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Head of Growth, ScaleUp Labs
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Founder, DataDriven.io
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Frequently Asked Questions
Find answers to common questions about GPT-4o mini