Native Multimodal Vision
Directly processes diagrams and UI screenshots within the thinking chain. Perfect for visual debugging and technical document extraction.
o4-mini / web-search
The openai o4 mini is a fast, cost-efficient reasoning model with 200k context. It bridges the gap between basic models and frontier reasoning, offering native multimodal logic and multi-step tool use for advanced STEM and coding tasks.
$ 0.99
$ 1.1
text
$ 3.96
$ 4.4
text
API
Web Search
curl --request POST "https://gptproto.com/v1/responses" \
--header "Authorization: Bearer $GPTPROTO_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"model": "o4-mini",
"tools": [
{
"type": "web_search_preview"
}
],
"input": [
{
"role": "user",
"content": [
{
"type": "input_text",
"text": "What are the latest breakthroughs in quantum computing and their potential applications?"
}
]
}
]
}'openai o4 Key Features & Capabilities
Discover the technical features that set openai o4 apart. It offers native multimodal processing, agentic autonomy, and elite performance in math and coding benchmarks for enterprise use.
Agentic Tool Autonomy
First mini model to support independent multi-step tool use, Python execution, and browsing. Build agents that actually get work done.
Massive 200K Context
Process long documents and complex codebases without losing track. The openai o4 supports 100k output tokens for deep, long-form generation.
Advanced STEM Logic
Outperforms 2024 models with 94% on AIME and 98.9% on MATH-500. The openai o4 handles complex equations and scientific reasoning with ease.
Build with o4 mini in Minutes
Follow these simple steps to set up your account, get credits, and start sending API requests to o4 mini via GPT Proto.
Sign up
Create your free GPT Proto account to begin. You can set up an organization for your team at any time.
Top up
Your balance can be used across all models on the platform, including o4 mini, giving you the flexibility to experiment and scale as needed.
Generate your API key
In your dashboard, create an API key — you'll need it to authenticate when making requests to o4 mini.
Make your first API call
Use your API key with our sample code to send a request to o4 mini via GPT Proto and see instant AI-powered results.
openai o4 FAQ: Reasoning & Use Cases
How does openai o4 handle visual reasoning tasks?
The openai o4 mini processes images and PDFs natively within its chain-of-thought logic. Unlike older models that use separate vision encoders, this integrated approach leads to a 35% reduction in visual logic errors. This makes it exceptionally reliable for interpreting UI screenshots, technical diagrams, and whiteboard sketches in production environments, providing a deeper understanding of spatial and logical relationships.
What makes the openai o4 model agentic?
It is the first mini-class model capable of multi-step tool use. It can independently browse the web, execute Python code in sandboxed environments, and perform recursive file analysis. This autonomy allows developers to build complex workflows where the openai o4 manages the task execution from start to finish, rather than just providing text responses, bridging the gap toward fully autonomous AI agents.
Can I control the reasoning depth in openai o4?
Yes, the model supports a reasoning_effort parameter with low, medium, and high settings. This allows you to balance speed and accuracy. Use high effort for difficult STEM problems or complex code logic, and low effort for faster, straightforward reasoning tasks. This flexibility ensures you only pay the latency cost when deep thinking is actually required for your specific application's success.
What are the pricing and context limits for openai o4?
The openai o4 mini features a massive 200k token context window and supports up to 100k output tokens. Pricing is set at $1.10 per 1M input tokens and $4.40 per 1M output tokens. GPTProto also offers a 50% discount on cached inputs and asynchronous batch processing. This pricing makes the openai o4 roughly 10x more cost-effective than larger frontier models while maintaining high-tier reasoning performance.
Is openai o4 suitable for real-time chat applications?
While powerful, the openai o4 has a higher Time-To-First-Token (TTFT) due to its internal thinking phase. It is not recommended for latency-sensitive customer support chatbots where instant replies are vital. However, for tasks where accuracy matters more than speed—such as technical tutoring or debugging—the trade-off is well worth it. For high-speed, simple chat, GPT-4o-mini remains a better choice.
How do I migrate my existing apps to openai o4?
Migration is simple. Just update your API model parameter to o4 mini-2025-04-16. Since it maintains feature parity with the Responses API, your existing function calls and structured output settings will work seamlessly. GPTProto provides unified billing and the same high rate limits, ensuring a smooth transition. Be sure to test the reasoning_effort settings to optimize the performance for your specific use case.
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