Unlock exclusive introductory pricing for the newly launched Gemini 3.5 Flash.
O

GPT-5.2 Chat

입력:$1.4/M
출력:$11.2/M
맥락:128,000
최대 출력:16,384
출시일:Dec 11, 2025

gpt-5.2-chat-latest is the Chat-optimized snapshot of OpenAI’s GPT-5.2 family (branded in ChatGPT as GPT-5.2 Instant). It is the model for interactive/chat use cases that need a blend of speed, long-context handling, multimodal inputs and reliable conversational behaviour.

새로운
인기
상업적 사용

GPT-5.2 Chat의 Playground

GPT-5.2 Chat의 Playground를 탐색하세요 — 모델을 테스트하고 실시간으로 쿼리를 실행하는 대화형 환경입니다. 프롬프트를 시도하고, 매개변수를 조정하며, 즉시 반복하여 개발을 가속화하고 사용 사례를 검증하세요.

What is gpt-5.2-chat-latest

gpt-5.2-chat-latest is the ChatGPT-aligned snapshot of OpenAI’s GPT-5.2 family, offered as the recommended chat model for developers who want the ChatGPT experience in the API. It combines large-context chat behavior, structured outputs, tool/function calling, and multimodal understanding in a package tuned for interactive conversational workflows and applications. It is intended for most chat use cases where a high-quality, low-friction conversational model is required.

Basic information

  • Model name (API): gpt-5.2-chat-latest — described by OpenAI as the chat-oriented snapshot used by ChatGPT; recommended for chat use cases in the API.
  • Family / variants: Part of the GPT-5.2 family (Instant, Thinking, Pro). gpt-5.2-chat-latest is the ChatGPT snapshot optimized for chat-style interactions, while other GPT-5.2 variants (e.g., Thinking, Pro) trade latency for deeper reasoning or higher fidelity.
  • Input: Standard tokenized text for prompts and messages via the Chat/Responses API; supports function/tool calling (custom tools and constrained function-like outputs) and multimodal inputs where enabled by the API. Developers pass chat messages (role + content) or the Responses API inputs; the model accepts arbitrary text prompts and structured tool-call instructions.
  • Output: Tokenized natural language responses, structured JSON/function outputs when function-calling is used, and (where enabled) multimodal replies. The API supports parameters for reasoning effort/verbosity and structured return formats.
  • Knowledge cutoff: August 31, 2025 .

Main features (user-facing capabilities)

  • Chat-optimized dialog — tuned for interactive conversational flows, system messages, tool calls and low-latency responses appropriate to chat UIs.
  • Large long-context support for chat — 128k token context to support long conversations, documents, codebases, or agent memory. Useful for summarization, long-doc Q&A and multi-step agent workflows.
  • Improved tool & agent reliability — support for allowed-tools lists, custom tools, and stronger tool-calling reliability for multi-step tasks.
  • Reasoning controls — support for configurable reasoning effort levels (none, medium, high, xhigh on some GPT-5.2 variants) to trade latency and cost for deeper internal reasoning. Chat snapshot expects lower latency defaults.
  • Context compaction / Compact API — new APIs and compaction utilities to summarize and compress conversation state for long-running agents while preserving important facts. (Helps reduce token costs while keeping context fidelity).
  • Multimodality & vision improvements: enhanced image understanding and chart/screenshot reasoning compared with earlier generations (GPT-5.2 family is promoted for stronger multimodal capability).

Representative production use cases (where chat-latest shines)

  • Interactive assistants for knowledge workers: long conversation continuity (meeting notes, policy drafting, contract Q&A) that need preserved context across many turns (128k tokens).
  • Customer support agents & internal tools: chat-first deployments that require tool calls (search, CRM lookups) with allowed-tools safety controls.
  • Multimodal help desks: image + chat workflows (e.g., screenshot triage, annotated diagrams) using images-as-input capability.
  • Coding helpers embedded in IDEs: fast, chat-oriented code completions and debugging help (use chat snapshot for low-latency interactions, Thinking/Pro for heavyweight verification).
  • Long-document summarization & review: legal or technical documents spanning many pages—compact API and 128k context help keep context fidelity and reduce token costs.

How to access and use GPT-5.2 chat API

Step 1: Sign Up for API Key

Log in to cometapi.com. If you are not our user yet, please register first. Sign into your CometAPI console. 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.

Step 2: Send Requests to GPT-5.2 chat API

Select the “gpt-5.2-chat-latest” 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. Replace <YOUR_API_KEY> with your actual CometAPI key from your account.Compatibility with the Chat/Responses-style APIs.

Insert your question or request into the content field—this is what the model will respond to . Process the API response to get the generated answer.

Step 3: Retrieve and Verify Results

Process the API response to get the generated answer. After processing, the API responds with the task status and output data.

See also Gemini 3 Pro Preview API

자주 묻는 질문

GPT-5.2 Chat 가격

[모델명]의 경쟁력 있는 가격을 살펴보세요. 다양한 예산과 사용 요구에 맞게 설계되었습니다. 유연한 요금제로 사용한 만큼만 지불하므로 요구사항이 증가함에 따라 쉽게 확장할 수 있습니다. [모델명]이 비용을 관리 가능한 수준으로 유지하면서 프로젝트를 어떻게 향상시킬 수 있는지 알아보세요.

Comet Price (USD / M Tokens)Official Price (USD / M Tokens)Discount
입력:$1.4/M
출력:$11.2/M
입력:$1.75/M
출력:$14/M
-20%

GPT-5.2 Chat의 샘플 코드 및 API

gpt-5.2-chat-latest is OpenAI’s Instant/Chat-tuned snapshot of the GPT-5.2 family (the ChatGPT-facing “Instant” variant) optimized for conversational/chat workloads, low-latency developer use, and broad ChatGPT integration.

curl https://api.cometapi.com/v1/responses \
     --header "Authorization: Bearer $COMETAPI_KEY" \
     --header "content-type: application/json" \
     --data \
'{
    "model": "gpt-5.2-pro",
    "input": "How much gold would it take to coat the Statue of Liberty in a 1mm layer?",
    "reasoning": {
        "effort": "high"
    }
}'

cURL Code Example

curl https://api.cometapi.com/v1/responses \
     --header "Authorization: Bearer $COMETAPI_KEY" \
     --header "content-type: application/json" \
     --data \
'{
    "model": "gpt-5.2-pro",
    "input": "How much gold would it take to coat the Statue of Liberty in a 1mm layer?",
    "reasoning": {
        "effort": "high"
    }
}'

Python Code Example

from openai import OpenAI
import os

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/v1"

client = OpenAI(base_url=BASE_URL, api_key=COMETAPI_KEY)

response = client.responses.create(
    model="gpt-5.2-chat-latest",
    input="How much gold would it take to coat the Statue of Liberty in a 1mm layer?",
)

print(response.output_text)

JavaScript Code Example

import OpenAI from "openai";

// Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
const COMETAPI_KEY = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const BASE_URL = "https://api.cometapi.com/v1";

const client = new OpenAI({
  apiKey: COMETAPI_KEY,
  baseURL: BASE_URL,
});

async function main() {
  const response = await client.responses.create({
    model: "gpt-5.2-chat-latest",
    input: "How much gold would it take to coat the Statue of Liberty in a 1mm layer?",
  });

  console.log(response.output_text);
}

main();