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GPT-5.3-Codex

GPT-5.3-Codex is a verified current AI model with official specs, pricing or access details, capabilities, best use cases and key limitations.

Code Generation ModelTextImage Paid
In plain English

What is this model and why does it matter?

GPT-5.3-Codex is OpenAI's agentic coding model for repository-scale software engineering and long-running code tasks.

Agentic codingRepository workBug fixingCodebase migrationSoftware engineering agents
Model overview

GPT-5.3-Codex: features, use cases and important details

GPT-5.3-Codex is a current AI model verified from first-party OpenAI sources.

GPT-5.3-Codex verified specifications

GPT-5.3-Codex is OpenAI’s agentic coding model for repository-scale software engineering and long-running code tasks. Its verified context or usage limit is 400000 tokens, with 128000 tokens maximum output.

GPT-5.3-Codex pricing and access

GPT-5.3-Codex costs $1.75 per 1M input tokens, $0.175 per 1M cached input tokens and $14 per 1M output tokens.

GPT-5.3-Codex best uses

Agentic coding, Repository work, Bug fixing, Codebase migration, Software engineering agents.

GPT-5.3-Codex limitations

Generated code must be tested, No fine-tuning, Can still make repository-level mistakes.

Get started

How to use this model

  1. Create an OpenAI API key.
  2. Call gpt-5.3-codex.
  3. Choose reasoning effort.
  4. Provide repository context and optional images.
  5. Use function tools or structured outputs for agent workflows.
Copy and try

Example prompts

  • Fix the failing tests in this repository.
  • Implement this feature across the relevant files.
  • Review this architecture and create a migration patch plan.
Capabilities

What it can do

  • 400K context
  • 128K output
  • Agentic coding
  • Image input
  • Function calling
  • Structured outputs
  • Reasoning controls
Best for

Practical use cases

  • Coding agents
  • Large repositories
  • Refactoring
  • Debugging
  • Software migration
Pricing

What does it cost?

GPT-5.3-Codex costs $1.75 per 1M input tokens, $0.175 per 1M cached input tokens and $14 per 1M output tokens.

Input$1.75 / 1M tokens
Output$14 / 1M tokens
Simple summaryCoding-focused pricing is $1.75/M input and $14/M output.

What stands out

  • Specialized for agentic coding
  • Large context
  • Competitive input price

Things to consider

  • Coding-specialized rather than general flagship
  • Proprietary
Limitations

Important restrictions and trade-offs

  • Generated code must be tested
  • No fine-tuning
  • Can still make repository-level mistakes
SimplifyAITools verdict

Our editorial take

A strong SEO target for developers comparing current Codex models and autonomous software-engineering agents.

References

Primary sources

  1. Open source 1 ↗
  2. Open source 2 ↗
  3. Open source 3 ↗
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