o3-mini

Approved Data Classifications

Description

The o3-mini model from OpenAI is a streamlined, cost-effective AI solution designed to enhance reasoning capabilities, particularly in STEM fields such as mathematics and coding. Released in December 2024 as a smaller reasoning model, o3-mini focuses on delivering efficient problem-solving without the extensive resource requirements of larger models. It excels at handling logical tasks and coding challenges, making it ideal for users who need quick responses and straightforward solutions. With its user-friendly interface and zero cost for access, o3-mini democratizes advanced AI technology, allowing a broader audience to leverage its capabilities for various applications while maintaining a strong emphasis on effective reasoning and analysis.

Capabilities

Model	Knowledge Cutoff	Input	Output	Context Length	Cost (per 1 million tokens)
o3-mini	May 2024	Text	Text	200,000	$1.10/1M input $4.40/1M output

info

• 1M represents 1 Million Tokens
• All prices listed are based on 1 Million Tokens

Availability

Cloud Provider

Usage

curl

curl -X POST https://api.ai.it.ufl.edu/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <API_TOKEN>" \
-d '{
    "model": "o3-mini",
    "messages": [
        {
            "role": "system",
            "content": "You are a helpful assistant."
        },
        {
            "role": "user",
            "content": "Write a haiku about an Alligator."
        }
    ]
}'

python

from openai import OpenAI
  client = OpenAI(
      api_key="your_api_key",
      base_url="https://api.ai.it.ufl.edu/v1"
  )

  response = client.chat.completions.create(
      model="o3-mini", # model to send to the proxy
      messages = [
          { role: "system", content: "You are a helpful assistant." },
          {
              "role": "user",
              "content": "Write a haiku about an Alligator."
          }
      ]
  )

  print(response.choices[0].message)

javascript

import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: 'your_api_key',
  baseURL: 'https://api.ai.it.ufl.edu/v1'
});

const completion = await openai.chat.completions.create({
    model: "o3-mini",
    messages: [
        { role: "system", content: "You are a helpful assistant." },
        {
            role: "user",
            content: "Write a haiku about an Alligator.",
        },
    ],
});

print(completion.choices[0].message)

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References

1. OpenAI
   https://openai.com/
2. LLM Stats
   https://llm-stats.com
3. Artificial Analysis
   https://artificialanalysis.ai