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How to Access GPT-5 and GPT-5.2 via API - Complete Developer Guide

Learn how to access OpenAI's latest GPT-5, GPT-5.2, and o3-pro models through a unified API. Step-by-step guide with Python, Node.js, and curl examples.

Crazyrouter Team

January 22, 2026 / 689 views

How to Access GPT-5 and GPT-5.2 via API - Complete Developer Guide

Crazyrouter

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OpenAI has released its most powerful models yet: GPT-5, GPT-5.2, and the reasoning-focused o3-pro. This guide shows you how to access these cutting-edge models through Crazyrouter's unified API.

Supported OpenAI Models#

Crazyrouter provides access to the complete OpenAI model lineup:

Model	Input ($/1M tokens)	Output ($/1M tokens)	Best For
gpt-5.2	$1.75	$14.00	Latest flagship, complex tasks
gpt-5.2-pro	$3.50	$28.00	Enhanced reasoning
gpt-5	$1.25	$10.00	General tasks
gpt-5-pro	$2.50	$20.00	Advanced analysis
gpt-5-mini	$0.25	$2.00	Cost-effective
gpt-5-nano	$0.05	$0.40	High-volume tasks
o3-pro	$20.00	$80.00	Complex reasoning
o3-mini	$1.10	$4.40	Efficient reasoning
o4-mini	$1.10	$4.40	Latest reasoning model

Quick Start#

1. Get Your API Key#

Visit Crazyrouter Console
Navigate to "Token Management"
Click "Create Token"
Copy your API key (starts with sk-)

2. Make Your First Request#

Using Python (Recommended)#

python

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://crazyrouter.com/v1",
    default_headers={
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
    }
)

response = client.chat.completions.create(
    model="gpt-5.2",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain quantum computing in simple terms."}
    ],
    temperature=0.7,
    max_tokens=1000
)

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

Using Node.js#

javascript

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'sk-your-api-key',
  baseURL: 'https://crazyrouter.com/v1',
  defaultHeaders: {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
  }
});

async function main() {
  const response = await client.chat.completions.create({
    model: 'gpt-5.2',
    messages: [
      { role: 'system', content: 'You are a helpful assistant.' },
      { role: 'user', content: 'Explain quantum computing in simple terms.' }
    ],
    temperature: 0.7
  });

  console.log(response.choices[0].message.content);
}

main();

Using curl#

bash

curl https://crazyrouter.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36" \
  -d '{
    "model": "gpt-5.2",
    "messages": [{"role": "user", "content": "Hello, GPT-5.2!"}],
    "temperature": 0.7
  }'

Streaming Responses#

For real-time output, enable streaming:

python

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://crazyrouter.com/v1",
    default_headers={
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
    }
)

stream = client.chat.completions.create(
    model="gpt-5.2",
    messages=[{"role": "user", "content": "Write a short story about AI."}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Using Reasoning Models (o3-pro)#

The o3-pro model excels at complex reasoning tasks:

python

response = client.chat.completions.create(
    model="o3-pro",
    messages=[
        {"role": "user", "content": "Solve this step by step: If a train travels 120 miles in 2 hours, then stops for 30 minutes, then travels another 90 miles in 1.5 hours, what is the average speed for the entire journey including the stop?"}
    ]
)

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

GPT-5 Codex Models#

For code generation tasks, use the specialized codex models:

python

response = client.chat.completions.create(
    model="gpt-5-codex",
    messages=[
        {"role": "user", "content": "Write a Python function to implement binary search"}
    ]
)

Available codex variants: gpt-5-codex, gpt-5-codex-high, gpt-5-codex-medium, gpt-5-codex-low, gpt-5.2-codex

Best Practices#

Choose the right model: Use gpt-5-nano for simple tasks, gpt-5.2 for complex ones
Set appropriate temperature: Lower (0.1-0.3) for factual tasks, higher (0.7-1.0) for creative tasks
Use streaming: For better user experience in chat applications
Handle errors gracefully: Implement retry logic for rate limits