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GPT-5.4 pro

Input:$24/M
Output:$144/M
๋งฅ๋ฝ:1,050,000
์ตœ๋Œ€ ์ถœ๋ ฅ:128,000
์ถœ์‹œ์ผ:Mar 5, 2026

seedance-2-0

์ƒˆ๋กœ์šด
์ธ๊ธฐ
์ƒ์—…์  ์‚ฌ์šฉ

GPT-5.4 pro์˜ Playground

GPT-5.4 pro์˜ Playground๋ฅผ ํƒ์ƒ‰ํ•˜์„ธ์š” โ€” ๋ชจ๋ธ์„ ํ…Œ์ŠคํŠธํ•˜๊ณ  ์‹ค์‹œ๊ฐ„์œผ๋กœ ์ฟผ๋ฆฌ๋ฅผ ์‹คํ–‰ํ•˜๋Š” ๋Œ€ํ™”ํ˜• ํ™˜๊ฒฝ์ž…๋‹ˆ๋‹ค. ํ”„๋กฌํ”„ํŠธ๋ฅผ ์‹œ๋„ํ•˜๊ณ , ๋งค๊ฐœ๋ณ€์ˆ˜๋ฅผ ์กฐ์ •ํ•˜๋ฉฐ, ์ฆ‰์‹œ ๋ฐ˜๋ณตํ•˜์—ฌ ๊ฐœ๋ฐœ์„ ๊ฐ€์†ํ™”ํ•˜๊ณ  ์‚ฌ์šฉ ์‚ฌ๋ก€๋ฅผ ๊ฒ€์ฆํ•˜์„ธ์š”.

Technical Specifications of GPT-5.4-Pro

ItemGPT-5.4-Pro
ProviderOpenAI
Model familyGPT-5.4
Model tierPro (high-compute reasoning variant)
Input typesText, Image
Output typesText
Context window1,050,000 tokens
Max output tokens128,000 tokens
Knowledge cutoffAug 31, 2025
Reasoning levelsmedium, high, xhigh
Tool supportWeb search, file search, code interpreter, image generation
API supportResponses API (recommended)
ReleaseMarch 2026

What is GPT-5.4-Pro?

GPT-5.4-Pro is the highest-capability API variant of the GPT-5.4 model family, designed for extremely complex reasoning, research, coding, and enterprise automation tasks.

Compared with the standard GPT-5.4 model, GPT-5.4-Pro uses significantly more internal compute to โ€œthink harderโ€ before producing responses, which leads to more accurate and reliable outputs for difficult problems.

The model is optimized for professional workloads such as financial analysis, software engineering, scientific research, and large-scale document reasoning.


Main Features of GPT-5.4-Pro

  • Extreme reasoning performance: Uses additional compute to produce more precise answers on complex tasks.
  • 1.05M token context window: Enables analysis of extremely large documents, datasets, or entire repositories.
  • Configurable reasoning depth: Developers can control reasoning effort levels (medium, high, xhigh).
  • Advanced tool orchestration: Works with web search, file retrieval, and other tools through the Responses API.
  • Long-running reasoning support: Complex tasks may take minutes to complete due to deeper compute allocation.
  • Enterprise reliability: Designed for high-stakes workflows requiring maximum answer accuracy.

Benchmark Performance

OpenAI reports significant improvements in professional reasoning benchmarks with GPT-5.4 models:

BenchmarkGPT-5.4GPT-5.2
GDPval (knowledge work)83.0%70.9%
OfficeQA68.1%63.1%
Investment Banking Modeling87.3%71.7%

These improvements highlight GPT-5.4โ€™s stronger performance on complex professional knowledge tasks and analytical reasoning workflows.

GPT-5.4-Pro further improves reliability by allocating more reasoning compute than the standard GPT-5.4 model.


GPT-5.4-Pro vs Comparable Models

ModelContext WindowKey Strength
GPT-5.4-Pro1.05M tokensMaximum reasoning accuracy
GPT-5.41.05M tokensBalanced speed and capability
o3-proSmallerEfficient reasoning
Gemini 3 Pro~1M tokensStrong multimodal capabilities

Key takeaway:
Use GPT-5.4-Pro when maximum reasoning accuracy matters more than latency or cost.

Limitations

  • Higher latency due to deeper reasoning compute
  • More expensive than standard GPT-5.4
  • No audio or video generation
  • Some long tasks may take minutes to complete

How to access GPT-5.4 pro API

Step 1: Sign Up for API Key

Log in toย cometapi.com. If you are not our user yet, please register first. Sign into yourย CometAPI console. Get the access credential API key of the interface. Click โ€œAdd Tokenโ€ at the API token in the personal center, get the token key: sk-xxxxx and submit.

cometapi-key

Step 2: Send Requests to GPT-5.4 pro API

Select the โ€œgpt-5.4-proโ€ 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. base url isย Responses.

Insert your question or request into the content fieldโ€”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.

์ž์ฃผ ๋ฌป๋Š” ์งˆ๋ฌธ

GPT-5.4 pro ๊ฐ€๊ฒฉ

[๋ชจ๋ธ๋ช…]์˜ ๊ฒฝ์Ÿ๋ ฅ ์žˆ๋Š” ๊ฐ€๊ฒฉ์„ ์‚ดํŽด๋ณด์„ธ์š”. ๋‹ค์–‘ํ•œ ์˜ˆ์‚ฐ๊ณผ ์‚ฌ์šฉ ์š”๊ตฌ์— ๋งž๊ฒŒ ์„ค๊ณ„๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์œ ์—ฐํ•œ ์š”๊ธˆ์ œ๋กœ ์‚ฌ์šฉํ•œ ๋งŒํผ๋งŒ ์ง€๋ถˆํ•˜๋ฏ€๋กœ ์š”๊ตฌ์‚ฌํ•ญ์ด ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ์‰ฝ๊ฒŒ ํ™•์žฅํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. [๋ชจ๋ธ๋ช…]์ด ๋น„์šฉ์„ ๊ด€๋ฆฌ ๊ฐ€๋Šฅํ•œ ์ˆ˜์ค€์œผ๋กœ ์œ ์ง€ํ•˜๋ฉด์„œ ํ”„๋กœ์ ํŠธ๋ฅผ ์–ด๋–ป๊ฒŒ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š”์ง€ ์•Œ์•„๋ณด์„ธ์š”.

ModelTierConditionComet Price (USD / M Tokens)Official Price (USD / M Tokens)Discount
gpt-5.4-proshort_contextlen <= 272000
Input:$24.0000/M
Output:$144.0000/M
Input:$30.0000/M
Output:$180.0000/M
-20%
long_context-
Input:$48.0000/M
Output:$216.0000/M
Input:$60.0000/M
Output:$270.0000/M
-20%
gpt-5.4-pro-2026-03-05short_contextlen <= 272000
Input:$24.0000/M
Output:$144.0000/M
Input:$30.0000/M
Output:$180.0000/M
-20%
long_context-
Input:$48.0000/M
Output:$216.0000/M
Input:$60.0000/M
Output:$270.0000/M
-20%

GPT-5.4 pro์˜ ์ƒ˜ํ”Œ ์ฝ”๋“œ ๋ฐ API

[๋ชจ๋ธ ์ด๋ฆ„]์˜ ํฌ๊ด„์ ์ธ ์ƒ˜ํ”Œ ์ฝ”๋“œ์™€ API ๋ฆฌ์†Œ์Šค์— ์•ก์„ธ์Šคํ•˜์—ฌ ํ†ตํ•ฉ ํ”„๋กœ์„ธ์Šค๋ฅผ ๊ฐ„์†Œํ™”ํ•˜์„ธ์š”. ์ž์„ธํ•œ ๋ฌธ์„œ๋Š” ๋‹จ๊ณ„๋ณ„ ๊ฐ€์ด๋“œ๋ฅผ ์ œ๊ณตํ•˜์—ฌ ํ”„๋กœ์ ํŠธ์—์„œ [๋ชจ๋ธ ์ด๋ฆ„]์˜ ๋ชจ๋“  ์ž ์žฌ๋ ฅ์„ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ๋•์Šต๋‹ˆ๋‹ค.

curl https://api.cometapi.com/v1/responses \
     --header "Authorization: Bearer $COMETAPI_KEY" \
     --header "content-type: application/json" \
     --data \
'{
    "model": "gpt-5.4-pro-2026-03-05",
    "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-5.4-pro-2026-03-05",
    "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-5.4-pro-2026-03-05",
    input="How much gold would it take to coat the Statue of Liberty in a 1mm layer?",
    reasoning={"effort": "high"},
)

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-5.4-pro-2026-03-05",
        input: "How much gold would it take to coat the Statue of Liberty in a 1mm layer?",
        reasoning: {
            effort: "high",
        },
    });

    console.log(response.output_text);
}

main();

GPT-5.4 pro์˜ ๋ฒ„์ „

GPT-5.4 pro์— ์—ฌ๋Ÿฌ ์Šค๋ƒ…์ƒท์ด ์กด์žฌํ•˜๋Š” ์ด์œ ๋Š” ์—…๋ฐ์ดํŠธ ํ›„ ์ถœ๋ ฅ ๋ณ€๋™์œผ๋กœ ์ธํ•ด ์ผ๊ด€์„ฑ์„ ์œ ์ง€ํ•˜๊ธฐ ์œ„ํ•ด ์ด์ „ ์Šค๋ƒ…์ƒท์„ ๋ณด๊ด€ํ•˜๊ฑฐ๋‚˜, ๊ฐœ๋ฐœ์ž์—๊ฒŒ ์ ์‘ ๋ฐ ๋งˆ์ด๊ทธ๋ ˆ์ด์…˜์„ ์œ„ํ•œ ์ „ํ™˜ ๊ธฐ๊ฐ„์„ ์ œ๊ณตํ•˜๊ฑฐ๋‚˜, ๊ธ€๋กœ๋ฒŒ ๋˜๋Š” ์ง€์—ญ๋ณ„ ์—”๋“œํฌ์ธํŠธ์— ๋”ฐ๋ผ ๋‹ค์–‘ํ•œ ์Šค๋ƒ…์ƒท์„ ์ œ๊ณตํ•˜์—ฌ ์‚ฌ์šฉ์ž ๊ฒฝํ—˜์„ ์ตœ์ ํ™”ํ•˜๊ธฐ ์œ„ํ•œ ๊ฒƒ ๋“ฑ์ด ํฌํ•จ๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ฒ„์ „ ๊ฐ„ ์ƒ์„ธํ•œ ์ฐจ์ด์ ์€ ๊ณต์‹ ๋ฌธ์„œ๋ฅผ ์ฐธ๊ณ ํ•ด ์ฃผ์‹œ๊ธฐ ๋ฐ”๋ž๋‹ˆ๋‹ค.

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