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GPT-5.2 Codex

ان پٹ:$1.4/M
آؤٹ پٹ:$11.2/M
سیاق و سباق:400,000
زیادہ سے زیادہ آؤٹ پٹ:128,000
جاری کیا گیا:Jan 18, 2026

GPT-5.2-Codex is an upgraded version of GPT-5.2 optimized for agentic coding tasks in Codex or similar environments. GPT-5.2-Codex supports low, medium, high, and xhigh reasoning effort settings.

نیا
تجارتی استعمال

GPT-5.2 Codex کے لیے Playground

GPT-5.2 Codex کا Playground دریافت کریں — ماڈلز کو ٹیسٹ کرنے اور حقیقی وقت میں سوالات چلانے کے لیے ایک متحرک ماحول۔ پرامپٹس آزمائیں، پیرامیٹرز ایڈجسٹ کریں، اور فوری طور پر دہرائیں تاکہ ترقی کو تیز کریں اور استعمال کے معاملات کی تصدیق کریں۔

Technical specifications of GPT 5.2 Codex

ItemGPT-5.2-Codex (public specs)
Model familyGPT-5.2 (Codex variant — coding/agentic optimized).
Input typesText, Image (vision inputs for screenshots/diagrams).
Output typesText (code, explanations, commands, patches).
Context window400,000 tokens (very long-context support).
Max output tokens128,000 (per call).
Reasoning effort levelslow, medium, high, xhigh (controls internal reasoning/compute allocation).
Knowledge cutoffAugust 31, 2025 (model’s training cutoff).
Parent family / variantsGPT-5.2 family: gpt-5.2 (Thinking), gpt-5.2-chat-latest (Instant), gpt-5.2-pro (Pro); Codex is an optimised variant for agentic coding.

What is the GPT-5.2-Codex

GPT-5.2-Codex is a purpose-built derivative of the GPT-5.2 family engineered for professional software engineering workflows and defensive cybersecurity tasks. It extends GPT-5.2’s general-purpose enhancements (improved long-context reasoning, tool-calling reliability, and vision understanding) with extra tuning and safety controls for real-world agentic coding: large refactorings, repository-scale edits, terminal interaction, and interpreting screenshots/diagrams commonly shared during engineering.

Main features of GPT-5.2 Codex

  • Very long context handling: 400k token window makes it feasible to reason across whole repositories, long issue histories, or multi-file diffs without losing context.
  • Vision + code: Generates, refactors, and migrates code across multiple languages; better at large refactorings and multi-file edits compared with prior Codex variants. Improved vision lets the model interpret screenshots, diagrams, charts, and UI surfaces shared in debugging sessions — useful for front-end debugging and reverse engineering UI bugs.
  • Agentic/terminal competence: Trained and benchmarked for terminal tasks and agent workflows (compiling, running tests, installing dependencies, making commits). Demonstrated ability to run compilation flows, orchestrate package installs, configure servers, and reproduce dev env steps when given terminal context. Benchmarked on Terminal-Bench.
  • Configurable reasoning effort: xhigh mode for deep, multi-step problem solving (allocate more internal compute/steps when the task is complex).

Benchmark performance of GPT-5.2 Codex

OpenAI reporting cite improved benchmark outcomes for agentic coding tasks:

  • SWE-Bench Pro: ~56.4% accuracy on large real-world software engineering tasks (reported post-release for GPT-5.2-Codex).
  • Terminal-Bench 2.0: ~64% accuracy on terminal/agentic task sets.

(These represent reported aggregate task success rates on complex, repository-scale benchmarks used to evaluate agentic coding capabilities.)

How GPT-5.2-Codex compares to other models

  • vs GPT-5.2 (general): Codex is a specialized tuning of GPT-5.2: same core improvements (long context, vision) but additional training/optimization for agentic coding (terminal ops, refactoring). Expect better multi-file edits, terminal robustness, and Windows environment compatibility.
  • vs GPT-5.1-Codex-Max: GPT-5.2-Codex advances Windows performance, context compression, and vision; benchmarks reported for 5.2 show improvements on SWE-Bench Pro and Terminal-Bench relative to predecessors.
  • vs competing models (e.g., Google Gemini family): GPT-5.2 competitive with or ahead of Gemini 3 Pro on many long-horizon and multimodal tasks. The practical edge for Codex is its agentic coding optimizations and IDE integrations; however, leaderboard positioning and winners depend on task and evaluation protocol.

Representative enterprise use cases

  1. Large-scale refactors and migrations — Codex can manage multi-file refactors and iterative testing sequences while preserving high-level intent across long sessions.
  2. Automated code review & remediation — Codex’s ability to reason across repositories and run/validate patches makes it suitable for automated PR reviews, suggested fixes, and regression detection.
  3. DevOps / CI orchestration — Terminal-bench improvements point to reliable orchestration of build/test/deploy steps in sandboxed flows.
  4. Defensive cybersecurity — Faster vulnerability triage, exploit reproduction for validation, and defensive CTF work in controlled, audited environments (note: requires strict access control).
  5. Design → prototype workflows — Convert mocks/screenshots into functional front-end prototypes and iterate interactively.

How to access GPT-5.2 Codex 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.

cometapi-key

Step 2: Send Requests to GPT 5.2 Codex API

Select the “gpt-5.2-codex” 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 is Responses

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.

اکثر پوچھے جانے والے سوالات

GPT-5.2 Codex کی قیمتیں

[ماڈل کا نام] کے لیے مسابقتی قیمتوں کو دریافت کریں، جو مختلف بجٹ اور استعمال کی ضروریات کے مطابق ڈیزائن کیا گیا ہے۔ ہمارے لچکدار منصوبے اس بات کو یقینی بناتے ہیں کہ آپ صرف اسی کے لیے ادائیگی کریں جو آپ استعمال کرتے ہیں، جس سے آپ کی ضروریات بڑھنے کے ساتھ ساتھ اسکیل کرنا آسان ہو جاتا ہے۔ دریافت کریں کہ [ماڈل کا نام] کیسے آپ کے پروجیکٹس کو بہتر بنا سکتا ہے جبکہ اخراجات کو قابو میں رکھتا ہے۔

Comet Price (USD / M Tokens)Official Price (USD / M Tokens)Discount
ان پٹ:$1.4/M
آؤٹ پٹ:$11.2/M
ان پٹ:$1.75/M
آؤٹ پٹ:$14/M
-20%

GPT-5.2 Codex کے لیے نمونہ کوڈ اور API

GPT-5.2 Codex کے لیے جامع نمونہ کوڈ اور API وسائل تک رسائی حاصل کریں تاکہ آپ کے انضمام کے عمل کو آسان بنایا جا سکے۔ ہماری تفصیلی دستاویزات قدم بہ قدم رہنمائی فراہم کرتی ہیں، جو آپ کو اپنے پروجیکٹس میں GPT-5.2 Codex کی مکمل صلاحیت سے فائدہ اٹھانے میں مدد کرتی ہیں۔

# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

curl https://api.cometapi.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "gpt-5.2-codex",
    "input": "Write a short Python function that checks if a string is a palindrome."
  }'

cURL Code Example

# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

curl https://api.cometapi.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "gpt-5.2-codex",
    "input": "Write a short Python function that checks if a string is a palindrome."
  }'

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-codex",
    input="Write a short Python function that checks if a string is a palindrome.",
)

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,
});

const response = await client.responses.create({
  model: "gpt-5.2-codex",
  input: "Write a short Python function that checks if a string is a palindrome.",
});

console.log(response.output_text);