GPT API Access: Complete Guide to OpenAI GPT-4o and Beyond (2026)

Call GPT-4o, GPT-4o-mini, o1, and o3 from Python, Node.js, LangChain, Cursor, and any OpenAI-compatible tool — with a single API key.

The GPT API by OpenAI powers millions of applications worldwide, from chatbots to code generators to data analysis pipelines. But getting reliable access — especially if you are outside supported regions or want to avoid managing multiple provider accounts — can be a challenge. This guide walks you through everything you need to call the GPT API with practical, copy-paste-ready code.

What Is the GPT API?

The GPT API is OpenAI's HTTP API that lets developers send text (and images) to GPT models and receive AI-generated responses. It is the same technology behind ChatGPT, but exposed programmatically so you can integrate it into your own applications.

The API follows a simple pattern: you send a list of messages, specify a model, and receive a completion. The most popular endpoint is /v1/chat/completions, which has become the de facto standard across the AI industry.

Available GPT Models

OpenAI offers several model families, each optimized for different use cases:

Which Model Should You Choose?

• Default choice: GPT-4o for most tasks. It offers the best balance of quality, speed, and features.
• Cost optimization: GPT-4o-mini for simple tasks like classification, summarization, or chat — at roughly 1/15th the cost of GPT-4o.
• Hard problems: o1 or o3-mini for complex math, advanced coding, or multi-step logical reasoning where accuracy matters more than speed.

GPT API Pricing

Pricing is based on token usage. Tokens are roughly 4 characters of English text. You pay separately for input tokens (what you send) and output tokens (what the model generates).

Getting Started: Call GPT API in 3 Steps

Step 1: Get Your API Key

Sign up at Token1.US, top up your balance, and generate an API key from the dashboard. Your key starts with sk- and works with the standard OpenAI SDK.

Step 2: Install the OpenAI SDK

# Python
pip install openai

# Node.js
npm install openai

Step 3: Make Your First API Call

Python

from openai import OpenAI

client = OpenAI(
    api_key="your-token1-us-key",
    base_url="https://discount-token.com/v1"
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain how HTTP works in simple terms."}
    ],
    max_tokens=500
)

print(response.choices[0].message.content)
print(f"Tokens used: {response.usage.total_tokens}")

Node.js

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "your-token1-us-key",
  baseURL: "https://discount-token.com/v1",
});

const response = await client.chat.completions.create({
  model: "gpt-4o",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "What is the capital of France?" },
  ],
});

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

curl

curl https://discount-token.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-token1-us-key" \
  -d '{
    "model": "gpt-4o",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Advanced Features

Streaming Responses

Streaming lets you display tokens as they arrive, which dramatically improves perceived latency for chat interfaces:

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Write a Python web scraper."}],
    stream=True
)

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

Function Calling (Tool Use)

GPT-4o can call external functions based on your definitions. This enables agent-style workflows where the model decides when to fetch data or perform actions:

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
    tools=[{
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get current weather for a city",
            "parameters": {
                "type": "object",
                "properties": {
                    "city": {"type": "string", "description": "City name"}
                },
                "required": ["city"]
            }
        }
    }]
)

# The model returns a function call you execute
tool_call = response.choices[0].message.tool_calls[0]
print(f"Model wants to call: {tool_call.function.name}")
print(f"Arguments: {tool_call.function.arguments}")

Vision (Image Input)

GPT-4o accepts images as input, enabling visual question answering, OCR, and image analysis:

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "What's in this image?"},
            {"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}}
        ]
    }]
)

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

Structured Output (JSON Mode)

Force the model to return valid JSON — perfect for data extraction and API integration:

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Extract name, age, and email from: John Doe, 30, [email protected]"}],
    response_format={"type": "json_object"}
)

import json
data = json.loads(response.choices[0].message.content)
print(data)  # {"name": "John Doe", "age": 30, "email": "[email protected]"}

Using GPT API with Popular Tools

LangChain

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="gpt-4o",
    api_key="your-token1-us-key",
    base_url="https://discount-token.com/v1"
)

response = llm.invoke("What are the top 3 benefits of REST APIs?")

Cursor IDE

Open Cursor Settings → Models → set the OpenAI Base URL to https://discount-token.com/v1 and enter your Token1.US API key. Cursor will use GPT-4o for code generation and chat.

Dify / Open WebUI / Any OpenAI-compatible tool

Any tool that accepts a custom OpenAI base URL works with Token1.US. Just point it to https://discount-token.com/v1 and use your API key.

Troubleshooting Common GPT API Errors

Best Practices for GPT API Usage

• Cache responses: For identical queries, cache the output to save tokens and reduce latency.
• Use system prompts: Set the model's behavior once in a system message rather than repeating instructions.
• Implement retry logic: Network errors happen. Use exponential backoff for automatic retries.
• Monitor token usage: Track response.usage to understand your spending patterns.
• Choose the right model: Use GPT-4o-mini for 80% of tasks and reserve GPT-4o for complex reasoning.
• Use streaming for chat: Users perceive streaming as 3-5x faster than waiting for a full response.

GPT API vs Other AI APIs

While GPT-4o is excellent, it is not always the best choice for every task. Here is how it compares:

With Token1.US, you can switch between all of these models instantly — just change the model parameter. See our full model comparison for details.

Frequently Asked Questions

Related Guides

• What Is an AI API Gateway?
• How to Access the Claude API
• DeepSeek API Integration Guide
• AI Model Comparison: GPT vs Claude vs GLM vs DeepSeek
• Cheapest AI API: Cost Comparison
• 5-Minute Quick Start Tutorial
• AI API Cost Calculator