Author's Description
OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning and coding performance across benchmarks like AIME (99.5% with Python) and SWE-bench, outperforming its predecessor o3-mini and even approaching o3 in some domains. Despite its smaller size, o4-mini exhibits high accuracy in STEM tasks, visual problem solving (e.g., MathVista, MMMU), and code editing. It is especially well-suited for high-throughput scenarios where latency or cost is critical. Thanks to its efficient architecture and refined reinforcement learning training, o4-mini can chain tools, generate structured outputs, and solve multi-step tasks with minimal delay—often in under a minute.
Key Specifications
Supported Parameters
This model supports the following parameters:
Features
This model supports the following features:
Performance Summary
OpenAI o4-mini, created on April 16, 2025, is a compact reasoning model designed for fast, cost-efficient performance with strong multimodal and agentic capabilities. It demonstrates competitive response times, ranking in the 41st percentile for speed, and offers moderate pricing, placing it in the 21st percentile. Notably, o4-mini exhibits exceptional reliability, achieving a perfect 100th percentile, indicating minimal technical failures. The model excels across various benchmarks. It achieved outstanding accuracy in Coding (94.0%, 95th percentile), Instruction Following (76.0%, 91st percentile), and Reasoning (99.0%, 97th percentile). Its General Knowledge performance was perfect at 100.0% accuracy, making it the most accurate model at its price point and among models of similar speed. While its Email Classification (98.0%, 59th percentile) and Ethics (99.0%, 54th percentile) scores are strong, they are not as exceptionally high in percentile ranking as its other categories. Overall, o4-mini's key strengths lie in its high accuracy across STEM tasks, visual problem-solving, and code editing, making it well-suited for high-throughput scenarios where latency and cost are critical.
Model Pricing
Current Pricing
Feature | Price (per 1M tokens) |
---|---|
Prompt | $1.1 |
Completion | $4.4 |
Input Cache Read | $0.275 |
Price History
Available Endpoints
Provider | Endpoint Name | Context Length | Pricing (Input) | Pricing (Output) |
---|---|---|---|---|
OpenAI
|
OpenAI | openai/o4-mini-2025-04-16 | 200K | $1.1 / 1M tokens | $4.4 / 1M tokens |
Benchmark Results
Benchmark | Category | Reasoning | Free | Executions | Accuracy | Cost | Duration |
---|
Other Models by openai
|
Released | Params | Context |
|
Speed | Ability | Cost |
---|---|---|---|---|---|---|---|
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