Skip to main content
OpenAIFastUltra

GPT-4o

OpenAI's flagship multimodal model. Industry-leading performance in reasoning, coding, and creative tasks with native vision capabilities and structured output support.

3 credits
per 1K tokens (avg)
Native multimodal (text + vision + audio)
128K context window
16K max output tokens
Function calling & JSON mode
Structured outputs
Image understanding & analysis

Run it right now

Test this model instantly in the Console Playground โ€” no code required

Sign in to try

Use with AI Assistant

Copy usage instructions for Claude, ChatGPT, or other AI

llms.txt

Model Specifications

Context Window
128K
tokens
Max Output
16K
tokens
Training Cutoff
2023-10
Compatible SDK
OpenAI

Capabilities

Vision
Function Calling
Streaming
JSON Mode
System Prompt

Token Pricing (per 1M tokens)

Token TypeCreditsUSD Equivalent
Input Tokens2,500$2.50
Output Tokens10,000$10.00
Cached Tokens1,250$1.25

* 1 credit โ‰ˆ $0.001 (actual charges may vary based on usage)

Quick Start

curl -X POST "https://api.core.today/llm/openai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer cdt_your_api_key" \
  -d '{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "system",
      "content": "You are a helpful assistant."
    },
    {
      "role": "user",
      "content": "Explain quantum computing in simple terms."
    }
  ],
  "temperature": 0.7,
  "max_tokens": 1000
}'

Parameters

ParameterTypeRequiredDefaultDescription
messagesarrayYes-Array of message objects with role and content
modelstringYesgpt-4oModel identifier
temperaturefloatNo1.0Sampling temperature (0-2). Lower = more focused, higher = more creative
max_tokensintegerNo4096Maximum tokens in response (up to 16384)
streambooleanNofalseEnable Server-Sent Events streaming
response_formatobjectNo-Format of response: { type: 'json_object' } for JSON mode
toolsarrayNo-List of tools (functions) the model can call
top_pfloatNo1.0Nucleus sampling threshold (0-1)

Examples

Basic Chat

Simple conversation with the model

curl -X POST "https://api.core.today/llm/openai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer cdt_your_api_key" \
  -d '{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "system",
      "content": "You are a helpful assistant."
    },
    {
      "role": "user",
      "content": "Explain quantum computing in simple terms."
    }
  ],
  "temperature": 0.7,
  "max_tokens": 1000
}'

Code Generation

Generate Python code with explanation

curl -X POST "https://api.core.today/llm/openai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer cdt_your_api_key" \
  -d '{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "system",
      "content": "You are an expert Python developer. Write clean, well-documented code."
    },
    {
      "role": "user",
      "content": "Write a Python class for a binary search tree with insert, search, and delete methods."
    }
  ],
  "temperature": 0.3,
  "max_tokens": 2000
}'

JSON Mode

Get structured JSON output

curl -X POST "https://api.core.today/llm/openai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer cdt_your_api_key" \
  -d '{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "system",
      "content": "You are a data extraction assistant. Always respond with valid JSON."
    },
    {
      "role": "user",
      "content": "Extract the following info from this text: 'John Smith, 35 years old, software engineer at Google, living in San Francisco'. Return as JSON with fields: name, age, job, company, city"
    }
  ],
  "response_format": {
    "type": "json_object"
  },
  "max_tokens": 500
}'

Vision Analysis

Analyze images with GPT-4o

curl -X POST "https://api.core.today/llm/openai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer cdt_your_api_key" \
  -d '{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "What's in this image? Describe it in detail."
        },
        {
          "type": "image_url",
          "image_url": {
            "url": "https://example.com/image.jpg"
          }
        }
      ]
    }
  ],
  "max_tokens": 1000
}'

Function Calling

Use tools/functions with the model

curl -X POST "https://api.core.today/llm/openai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer cdt_your_api_key" \
  -d '{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "user",
      "content": "What's the weather like in Seoul today?"
    }
  ],
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_weather",
        "description": "Get current weather for a location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "City name"
            },
            "unit": {
              "type": "string",
              "enum": [
                "celsius",
                "fahrenheit"
              ]
            }
          },
          "required": [
            "location"
          ]
        }
      }
    }
  ]
}'

Tips & Best Practices

1Use system messages to set behavior and constraints
2Lower temperature (0.1-0.3) for factual/coding tasks
3Higher temperature (0.7-1.0) for creative writing
4Enable JSON mode for structured data extraction
5Use function calling for tool integration
6Vision works with URLs or base64-encoded images
7Streaming reduces time-to-first-token significantly

Use Cases

Complex reasoning and analysis
Code generation and debugging
Content creation and editing
Data extraction from documents/images
Multi-step task automation
Customer support chatbots