OpenAI: o4 Mini

Overview

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.

Currency$USD

Input$1.10

Output$4.40

Context window200K

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Endpoint

POSThttps://api.indoxhub.com/api/v1/chat/completions

Configopenai/o4-mini

from indoxhub import Client
 
# Initialize the client
with Client(api_key="[LOGIN TO GET API KEY]") as client:
    # Generate a chat completion
    response = client.chat(
        messages=[{"role":"system","content":"You are a helpful assistant."},{"role":"user","content":"What is machine learning and why is it important?"}],
        model="openai/o4-mini",
        temperature:"0.7"
    )
 
    # Print the response
    print(response["data"])

ResourcesDocumentation Python SDK