gpt-4-search

Technical Specifications of gpt-4-search

What is gpt-4-search?

gpt-4-search is CometAPI’s platform identifier for a GPT-4-class search-capable model designed for answering questions that require fresh information from the web. In OpenAI’s public documentation, the closest corresponding capability is its search-specialized GPT model and the web search tool used in ChatGPT search and the API. These systems are built to retrieve current web information, synthesize it into an answer, and surface references so users can verify the response.

This makes gpt-4-search especially suitable for use cases such as news summaries, market monitoring, product research, fact-checking, travel planning, and other workflows where a standard static-knowledge model may be insufficient. OpenAI also states that the same search model powers ChatGPT search, reinforcing that this class of model is optimized for timely, citation-backed responses rather than purely closed-book generation.

Main features of gpt-4-search

• Live web retrieval: The model is intended for queries that need up-to-date information from the public web, rather than relying only on training data.
• Citation-backed answers: Search-enabled responses can include links or references to sources, helping users inspect where information came from.
• Search-specialized behavior: OpenAI describes its search preview model as specialized for understanding and executing web search queries.
• Large context handling: With a 128k context window, the model can manage longer prompts and richer retrieved context than many smaller models.
• High factual QA utility: OpenAI reports strong benchmark performance for its search-enabled models on short factual question answering, indicating usefulness for research and verification workflows.
• Good fit for agents and assistants: OpenAI positions web search as a core tool for building assistants such as shopping, research, and travel agents that depend on timely information.
• Text-focused interaction: The publicly documented search-preview model is text-in/text-out, which aligns well with chat, analysis, and retrieval-driven API tasks.

How to access and integrate gpt-4-search

Step 1: Sign Up for API Key

Sign up on CometAPI and create an API key from the dashboard. After that, store the key as an environment variable such as COMETAPI_API_KEY so your application can authenticate securely with the API.

Step 2: Send Requests to gpt-4-search API

Use CometAPI’s OpenAI-compatible endpoint and specify the model as gpt-4-search.

curl https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_API_KEY" \
  -d '{
    "model": "gpt-4-search",
    "messages": [
      {
        "role": "user",
        "content": "Summarize the latest major AI news and include the most important takeaways."
      }
    ]
  }'

Step 3: Retrieve and Verify Results

Parse the JSON response and read the generated assistant message from the choices[0].message.content field. Because gpt-4-search is intended for search-backed answers, you should also review any returned citations, source references, or related metadata in the response payload when available, and verify important claims before using them in production workflows.