After a small-scale test at the beginning of this month, OpenAI's programming large model GPT-5.3-Codex is now officially available worldwide for developers. Now, all users can directly call this most powerful agent-style programming tool through the official OpenAI API platform or third-party platforms such as OpenRouter.

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Differing from previous Codex versions, GPT-5.3-Codex is no longer just a code generator. Its core breakthrough lies in the deep integration of the extreme coding efficiency of GPT-5.2-Codex and the strong general reasoning capabilities of GPT-5.2. This means it not only writes code but also acts like a "senior architect" who understands business and thinks, capable of understanding complex development logic and providing professional advice.

AIbase learned that the model has achieved significant performance improvements. In multi-step complex agent tasks, its processing speed has increased by about 25%. What surprised developers the most was its "mid-task interaction guidance" feature: users can intervene at any time during task execution to modify the development direction or add new requirements, and the model can maintain context coherence perfectly without "memory gaps."

To adapt to modern large-scale engineering needs, GPT-5.3-Codex has expanded its context window to 400K Tokens, which is sufficient to handle ultra-large codebases in one go. Additionally, it performed exceptionally well in real-world engineering tests such as SWE-Bench Pro, covering mainstream programming languages such as Python, Java, and TypeScript. Currently, the official pricing strategy has been announced, supporting optimized usage costs through fine-grained control of reasoning intensity.

Summary:

  • 💻 Integration of Programming and Reasoning: No longer just generating code, but combining extreme coding capabilities with general reasoning to support more complex agent tasks.

  • ⚡ Double Upgrade in Performance and Interaction: Overall operation speed increased by 25%, and supports modifying development requirements at any time during task execution without losing context.

  • 📂 Ultra Large Memory Space: Equipped with a 400K Tokens context window, it can easily handle ultra-large projects and provides fine-grained reasoning intensity control options.