openai/gpt-5.3-codex
128K context · $0.88 / M input tokens · $7.00 / M output tokens
GPT-5.3 Codex is OpenAI's code-optimized frontier model, designed for software engineering tasks including code generation, debugging, and agentic coding workflows.
Pricing
Pay-per-use
No upfront costs, pay only for what you use
API Usage
API Access Guide
Code examples
ourtoken.ai is OpenAI-compatible. This means your API key can be used with the OpenAI SDK. Just replace base_url with your ourtoken.ai address. See the examples below:
import openai
client = openai.OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.ourtoken.ai/v1"
)
response = client.chat.completions.create(
model="gpt-5.3-codex",
messages=[
{
"role": "user",
"content": "Hello!"
}
]
)
print(response.choices[0].message.content)Model Introduction
OpenAI gpt-5.3-codex
GPT-5.3 Codex is OpenAI's code-optimized frontier model, designed for software engineering tasks including code generation, debugging, and agentic coding workflows.
GPT-5.3 Codex is purpose-built for software engineering, delivering high-quality code generation, debugging, and refactoring across a wide range of programming languages and frameworks. It offers an accessible price point at $0.88 input / $7.00 output per million tokens, making it the most cost-effective option in the GPT-5 series for code-heavy workloads.
Why It Looks Great
- Optimized for code generation, debugging, and software engineering workflows.
- 128K token context window suitable for large codebases and multi-file tasks.
- Most cost-effective model in the GPT-5 series at $0.88 / $7.00 per million tokens.
- Supports function calling for tool-assisted agentic coding pipelines.
- Accessible via the same OurToken unified API endpoint as other OpenAI models.
Key Features
- Context Window: 128000 tokens
- Max Output: 32000 tokens
- Function Calling: Supported
- Input: Text
- Output: Text
- Optimized for: Code generation and software engineering
Specifications
GPT 5.3 Codex API Features for Developers
Use GPT 5.3 Codex API on OurToken for code generation, debugging, agentic workflows, lower-cost routing, and GPT Codex evaluations.
Code Generation
Use GPT 5.3 Codex API to generate production-ready code across common languages, frameworks, and repository patterns. Teams evaluating GPT 5.3 Codex can test frontend changes, backend logic, scripts, and implementation plans in one coding workflow.
Debugging and Refactoring
Apply GPT 5.3 Codex to bug analysis, refactoring, test repair, and code review tasks that require precise reasoning over existing files. The GPT Codex focus makes it useful when developer teams need deeper code edits without moving to a larger general model.
Agentic Coding
Build coding agents that plan tasks, inspect context, write patches, run checks, and iterate on feedback. GPT 5.3 Codex API is especially relevant for teams comparing 5.3 Codex with newer OpenAI models for autonomous software engineering.
Large Codebase Context
Use the 128K context window for large files, multi-file prompts, architecture notes, and extended coding sessions. GPT 5.3 Codex helps teams keep enough project context available while controlling prompt size and coding pipeline cost.
Cost-Efficient Coding
At $0.88 input and $7.00 output per million tokens on OurToken, GPT 5.3 Codex is positioned for code-heavy pipelines that need affordable volume. This gives teams a practical reason to compare gpt 5.3 codex vs 5.4 before scaling.
Unified API Access
Route GPT 5.3 Codex API requests through the same OurToken API used for other supported OpenAI models. Developers can compare gpt 5.4 vs gpt 5.3 codex in one integration instead of maintaining separate provider-specific code.
How to Use GPT 5.3 Codex API on OurToken
Create an API key, choose GPT 5.3 Codex API, provide code context, connect tools, and compare GPT 5.3 Codex vs GPT 5.4.
Generate API Key
Create an OurToken API key and store it in a secure server-side environment variable. This gives your backend a stable way to call GPT 5.3 Codex API without exposing credentials in browser or client-side code.
01Select Model ID
Use gpt-5.3-codex as the model value when sending chat completions requests. Keep your documentation clear for developers searching GPT 5.3 Codex, 5.3 Codex, or GPT Codex access through a unified API.
02Provide Code Context
Include relevant files, function signatures, failing tests, coding conventions, and acceptance criteria in the prompt. GPT 5.3 Codex API performs best when the model can see the constraints that define a correct patch.
03Define Output Style
Use system prompts to define language preferences, formatting rules, patch style, and whether the answer should explain changes or only return code. This keeps GPT Codex workflows predictable for repeated development tasks.
04Connect Coding Tools
Expose only the file, test, shell, or repository tools your agent actually needs. GPT 5.3 Codex API can then support multi-step coding loops that inspect code, draft changes, run checks, and revise output.
05Compare with GPT 5.4
Benchmark GPT 5.3 Codex vs GPT 5.4 on your own coding tasks, including debugging, refactoring, code generation, and tool use. This also answers gpt 5.4 vs 5.3 codex searches with practical evaluation criteria.
06GPT 5.3 Codex API FAQ
Answers about GPT 5.3 Codex API access, GPT Codex coding workflows, pricing, model ID, and GPT 5.3 Codex vs GPT 5.4 comparisons.
