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
“of these cases now GPT 40 mini also has a knowledge cuto date like most of these models have knowledge up to October 2023 which is pretty recent for these large language models this is less than a year”
“if you're using 40 to build your app and you feel like it's too expensive well you may want to downgrade and save a whole lot of money in the usage of your API so this is related to the API and”
“look at the speed of that way faster right so that's going to be great especially for people using chat GPT for free now they have this model that's good and is fast and is free okay now”
“If you're doing anything with vision, it's actually slower than the flagship model.”
“introducing our most cost efficient small model GPT 40 mini scores an 82% on the mlu and currently outperforms GPT 4”
“2.5 seconds for GPT 40 mini 4.6 seconds for GPT 40 now according to GPT 40 mini”
“It supports up to 16,000 output tokens per request, think of that as around 12,000 words.”
“modalities but the GPT 40 mini that's now rolled out just supports text and vision not video not audio and yes we”
“positive news it supports up to 16,000 output tokens per request think of that as being around 12,000 Words which is pretty impressive it has knowledge up to”
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What to get right first
The decisions that are painful to change later in GPT-4o mini.
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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Frequently Asked Questions
Find answers to common questions about GPT-4o mini