OpenAI: o4 Mini High

openai/o4-mini-high

Description

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, 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 efficiency 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.

How this model compares

Overall covers the full catalog. By plan covers only models available on that tier (same rules as available models in your list). Position on min–average–max. Prices use the higher of prompt or completion per token, shown per 1M tokens.

Price (per 1M tokens)

Min
Max
This model
336 models in this groupPrice (per 1M tokens)
Min
$0.04
Avg
$12.385977
Max
$750.00
This model: $4.40 / 1M tokens

Context length (tokens)

Min
Max
This model
336 models in this groupContext length (tokens)
Min
4,095 tokens
Avg
382,115.467 tokens
Max
10,000,000 tokens
This model: 200,000 tokens

Capabilities

text+image+file->textContext: 200,000 tokens
Input:
ImageTextFile
Output:
Text