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200k

reasoning

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OpenAI

O3 API

OpenAI's o3 API provides access to its most advanced reasoning o3 model which support multimodal inputs, advanced function calling, structured outputs, and are optimized for complex tasks like coding, mathematics, and visual comprehension.
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  • Flexible Solution
  • Constant Updates
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.cometapi.com/v1",
    api_key="<YOUR_API_KEY>",    
)

response = client.chat.completions.create(
    model="o3",
    messages=[
        {
            "role": "system",
            "content": "You are an AI assistant who knows everything.",
        },
        {
            "role": "user",
            "content": "Tell me, why is the sky blue?"
        },
    ],
)

message = response.choices[0].message.content

print(f"Assistant: {message}")

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O3 API

OpenAI’s o3 API provides access to its most advanced reasoning o3 model which support multimodal inputs, advanced function calling, structured outputs, and are optimized for complex tasks like coding, mathematics, and visual comprehension.

o3 API

Key Features

Advanced Reasoning Capabilities

o3 introduces a “private chain of thought” mechanism, enabling the model to engage in multi-step logical reasoning. This approach allows model to plan and execute tasks that require intricate problem-solving skills, setting it apart from its predecessors.

Multimodal Integration

A significant enhancement in o3 is its ability to process and reason with visual inputs, such as images and diagrams. This multimodal capability enables the model to interpret and analyze visual data, expanding its applicability in fields like medical imaging and design.

Tool Autonomy

o3 can autonomously utilize various tools within the ChatGPT ecosystem, including web search, Python execution, image analysis, and file interpretation. This autonomy enhances its efficiency in handling complex tasks without constant human intervention.


Technical Specifications

Architecture and Design

o3 is built upon the Generative Pre-trained Transformer (GPT) architecture, incorporating enhancements that facilitate advanced reasoning and multimodal processing. The model employs reinforcement learning techniques to refine its decision-making processes, allowing for more accurate and context-aware responses.

Compute Configurations

To accommodate varying computational resources and task complexities, it offers three compute levels: low, medium, and high. Higher compute levels enable the model to perform more complex reasoning tasks but require increased computational power and time.


Evolution from Previous Models

Transition from o1 to o3

o3 serves as the successor to OpenAI’s o1 model, introducing significant improvements in reasoning capabilities and performance. Unlike o1, o3 can handle more complex tasks, thanks to its enhanced architecture and learning mechanisms.

Development Timeline

  • December 20, 2024: Announcement of o3’s development.
  • January 31, 2025: Release of o3-mini, a cost-effective variant.
  • April 16, 2025: Official release of the full o3 model.

o3

Benchmark Performance

o3 has demonstrated exceptional performance across a variety of benchmarks, showcasing its superiority over previous models like o1. Below are the key benchmark results:

Benchmarko3 Scoreo1 ScoreDescription
ARC-AGI87.5%32%Measures ability to solve novel, intelligent tasks without pre-trained knowledge
AIME 2024 (Mathematics)96.7%83.3%Tests advanced mathematical problem-solving skills
Codeforces Elo (Coding)27271891Competitive programming platform; 2727 is International Grandmaster level
SWE-bench Verified71.7%48.9%Evaluates coding skills
GPQA Diamond (Science)87.7%–Tests Ph.D.-level scientific reasoning

Technical Indicators

Codeforces Rating

In competitive programming, it achieved a Codeforces rating of 2727, placing it among the top human coders globally. This rating reflects the model’s ability to solve complex algorithmic problems efficiently

Token Processing Capacity

It can process up to 33 million tokens for a single task, enabling it to handle extensive and complex inputs. This capacity is crucial for tasks that require deep analysis and reasoning


See Also GPT-4.1 API

How to call o3 API from CometAPI

o3 API Pricing in CometAPI,20% off the official price:

  • Input Tokens: $8 / M tokens
  • Output Tokens: $32/ M tokens

Required Steps

  • Log in to cometapi.com. If you are not our user yet, please register first
  • Get the access credential API key of the interface. Click “Add Token” at the API token in the personal center, get the token key: sk-xxxxx and submit.
  • Get the url of this site: https://api.cometapi.com/

Useage Methods

  1. Select the “o3/ o3-2025-04-16” endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience.
  2. Replace <YOUR_API_KEY> with your actual CometAPI key from your account.
  3. Insert your question or request into the content field—this is what the model will respond to.
  4. . Process the API response to get the generated answer.

For Model lunched information in Comet API please see https://api.cometapi.com/new-model.

For Model Price information in Comet API please see https://api.cometapi.com/pricing.

API Usage Example

Developers can interact with o3 through CometAPI’s API, enabling integration into various applications. Below is a Python example :

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.cometapi.com/v1/chat/completions",
    api_key="<YOUR_API_KEY>",    
)

response = openai.ChatCompletion.create(
    model="o3",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain the concept of quantum entanglement."}
    ]
)

print(response['choices'][0]['message']['content'])

This script sends a prompt to the o3 model and prints the generated response, demonstrating how to utilize o3 for complex explanations.

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