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OpenAI: o4 Mini High

Other
Input: image
Input: text
Input: file
Output: text
Released: Apr 16, 2025Updated: Apr 23, 2025

OpenAI o4-mini-high is the same model as o4-mini with reasoning_effort set to high.

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.

200,000 Token Context

Process and analyze large documents and conversations.

Hybrid Reasoning

Choose between rapid responses and extended, step-by-step processing for complex tasks.

Advanced Coding

Improved capabilities in front-end development and full-stack updates.

Agentic Workflows

Autonomously navigate multi-step processes with improved reliability.

Vision Capabilities

Process and understand images alongside text inputs.

Available On

ProviderModel IDContextMax OutputInput CostOutput CostThroughputLatency
OpenAIopenAi200K100K$1.10/M$4.40/M92.9 t/s8100 ms
Standard Pricing
Input Tokens
$0.0000011

per 1K tokens

Output Tokens
$0.0000044

per 1K tokens

Image Processing
$0.0008415

per image

Input Cache Read
$0.000000275

per 1K tokens

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