GPT 5.2 Codex

Chat Completions

gpt-5.2-codex

OpenAI|Created Jan 15, 2026

Chat Completions

GPT-5.2-Codex is an enhanced version of GPT-5.1-Codex, optimized for software engineering and coding tasks. Designed for both interactive sessions and longer, independent execution, it excels at building projects, developing features, debugging, large-scale refactoring, and code review. Compared to its predecessor, 5.2-Codex follows developer instructions more closely and delivers cleaner, higher-quality code. It integrates seamlessly with developer tools—CLI, IDEs, GitHub, and cloud platforms—and adapts its reasoning effort based on task complexity, providing quick responses for simple tasks and maintaining extended performance for larger projects. The model supports structured code reviews, detects critical flaws, validates behavior against tests, and handles multimodal inputs like images for UI work. It is specifically tailored for agentic coding applications.

Overview Specifications Activity Performance Uptime Examples

Pricing-50%

Pay-as-you-go rates for this model. More details can be found here.

Input Tokens (1M)

$0.88

Cached Input Tokens (1M)

$0.09

Output Tokens (1M)

$7.00

Capabilities

Input Modalities

TextImage

Output Modalities

Text

Supported Parameters

Available parameters for API requests

Frequency PenaltyFunction CallFunctionsLogit BiasMax Completion TokensParallel Tool CallsPredictionPresence PenaltyReasoning EffortResponse FormatStopTool ChoiceToolsWeb Search Options

Usage Analytics

Token usage of this model on our platform

Throughput

Time-To-First-Token (TTFT)

Code Example

Example code for using this model through our API with Python (OpenAI SDK) or cURL. Replace placeholders with your API key and model ID.

Basic request example. Ensure API key permissions. For more details, see our documentation.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.naga.ac/v1",
    api_key="YOUR_API_KEY",
)

resp = client.chat.completions.create(
    model="gpt-5.2-codex",
    messages=[
        {"role": "user", "content": "What's 2+2?"}
    ],
    temperature=0.2,
)
print(resp.choices[0].message.content)