Large Context Window
Accepts up to 128,000 tokens of input in a single request, enabling processing of long documents, transcripts, or multi-turn conversation histories.
OpenAI
GPT-4o Mini
GPT-4o Mini is a text generation model developed by OpenAI and released in July 2024. It is designed to deliver low-cost, low-latency responses across a wide range of tasks, making it suitable for applications that require fast throughput or high request volumes. The model supports a 128,000-token context window and is compatible with the same range of languages as GPT-4o. GPT-4o Mini is positioned for use cases such as real-time customer interactions, processing large volumes of context, and multimodal reasoning tasks. It performs on academic benchmarks across both textual intelligence and multimodal reasoning, outscoring GPT-3.5 Turbo and other small models in those evaluations. Its combination of speed and affordability makes it a practical choice for developers building cost-sensitive production applications.
Jul 18, 2024
128,000 context
16,383 tokens output
Large Context Window
Low Latency Responses
Cost-Efficient Operation
Multilingual Text Generation
Multimodal Reasoning
Structured Output
Model Overview
High-signal model metadata in a structured two-column overview table.
Provider
The entity that provides this model.
OpenAI
Model ID
The routed model identifier exposed by upstream providers.
openai/gpt-4o-mini
Input Context Window
The number of tokens supported by the input context window.
128,000
tokens
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
16,383 tokens
tokens
Open Source
Whether the model's code is available for public use.
No
Release Date
When the model was first released.
Jul 18, 2024
1 year ago
Knowledge Cut-off Date
When the model's knowledge was last updated.
2023-10-31
API Providers
The providers that offer this model. This is not an exhaustive list.
Azure, OpenAI
Modalities
Types of data this model can process.
Text
Image
File
What is GPT-4o Mini
A fuller summary of positioning, capabilities, and source-specific details for GPT-4o Mini.
GPT-4o Mini is a text generation model developed by OpenAI and released in July 2024. It is designed to deliver low-cost, low-latency responses across a wide range of tasks, making it suitable for applications that require fast throughput or high request volumes. The model supports a 128,000-token context window and is compatible with the same range of languages as GPT-4o.
GPT-4o Mini is positioned for use cases such as real-time customer interactions, processing large volumes of context, and multimodal reasoning tasks. It performs on academic benchmarks across both textual intelligence and multimodal reasoning, outscoring GPT-3.5 Turbo and other small models in those evaluations. Its combination of speed and affordability makes it a practical choice for developers building cost-sensitive production applications.
Capabilities
What GPT-4o Mini supports
Low Latency Responses
Optimized for fast response times, making it suitable for real-time applications such as customer-facing chat interfaces.
Cost-Efficient Operation
Priced significantly lower than larger GPT-4 class models, allowing high-volume deployments without proportional cost increases.
Multilingual Text Generation
Supports the same range of languages as GPT-4o, enabling text generation and comprehension across diverse language inputs.
Multimodal Reasoning
Capable of reasoning over both text and image inputs, supporting tasks that combine visual and textual understanding.
Structured Output
Supports JSON mode and function calling, allowing developers to receive predictable, machine-readable responses for integration into pipelines.
Pricing for GPT-4o Mini
Primary API pricing shown in the same “quick compare” spirit as the reference page.
Input tokens
$0.15
Per million tokens
Output tokens
$0.60
Per million tokens
Price Comparison
Additional usage-cost dimensions synced into the project for this model.
Cache read
$0.07
maxTemperature
2
maxResponseSize
16,383 tokens
API Access & Providers
Places where this model is available, based on the synced detail-page metadata.
Azure
OpenAI
Provider Endpoints
Endpoint-level provider data currently available for this model.
Azure
Azure
OpenAI
Model Performance
Benchmark scores synced from the current model source and normalized into the local catalog.
| Benchmark | Score |
|---|---|
|
AIME 2024
American math olympiad problems
|
|
|
GPQA Diamond
PhD-level science questions (biology, physics, chemistry)
|
|
|
HLE
Questions that challenge frontier models across many domains
|
|
|
LiveCodeBench
Real-world coding tasks from recent competitions
|
|
|
MATH-500
Undergraduate and competition-level math problems
|
|
|
MMLU-Pro
Expert knowledge across 14 academic disciplines
|
|
|
SciCode
Scientific research coding and numerical methods
|
Resources & Documentation
Official model cards, release notes, docs, and other references synced from the source page.
Official Product Page
Other
→
GPT-4o mini: advancing cost-efficient intelligence
Announcements
→
OpenAI API Documentation
Documentation
→
OpenAI Playground
Playground
→
OpenAI Pricing Page
Other
→
Official Website
→
Usage Policies
→
Enterprise privacy at OpenAI
→
OpenAI Status Page
→
OpenRouter Model Page
OpenRouter
→
Community discussion
What people think about GPT-4o Mini
GPT-4o Mini discussions are most active in r/LocalLLaMA, r/OpenAI, r/singularity. Top Reddit threads cluster around benchmark and model-comparison threads, coding workflow discussions.
The strongest match in this snapshot has 1433 upvotes and 766 comments.
If you've been debating between using API calls with OpenAI, Claude, or Gemini, versus running a local private AI model, this is the moment to try the local route. Qwen 2.5 paired with Ollama is the first local model I've found reliable enough to replace API-driven options. It handles everything smoothly, and I’ve made it my default voice assistant at home. If you’ve been waiting for a local solution that actually works, this is it!
Currently running the default 7b Q4 from ollama : [https://ollama.com/library/qwen2.5](https://ollama.com/library/qwen2.5)
https://i.redd.it/aljzyqurzupd1.gif
FAQ
Common questions about GPT-4o Mini
What is the context window size for GPT-4o Mini?
GPT-4o Mini supports a context window of 128,000 tokens, allowing large amounts of text or conversation history to be passed in a single request.
What is the knowledge cutoff date for GPT-4o Mini?
GPT-4o Mini has a training data cutoff of October 2023, meaning it does not have knowledge of events that occurred after that date.
What types of inputs does GPT-4o Mini support?
GPT-4o Mini supports text inputs and also has multimodal reasoning capabilities, meaning it can process image inputs alongside text.
Is GPT-4o Mini suitable for production applications with high request volumes?
Yes. GPT-4o Mini is designed for low cost and low latency, making it well-suited for high-volume production use cases such as real-time customer interactions or batch processing tasks.
Does GPT-4o Mini support function calling and structured outputs?
Yes. GPT-4o Mini supports function calling and JSON mode, which allow developers to receive structured, predictable outputs for use in automated pipelines and integrations.
More models from OpenAI
Continue browsing adjacent models from the same provider.