GPT-5.3 Codex AI Chat Assistant

Use GPT-5.3 Codex for difficult debugging in large codebases, complex implementation plans, high-stakes review, regression hunting, and agent-style engineering tasks with long context. It is unnecessary for a small isolated code question.

On Rivya, GPT-5.3 Codex currently runs as a chat project that can also work from image inputs.

Provide repository context, the failing behavior, logs or tests, relevant files, constraints, and the commands that define success. For implementation work, state which changes are allowed and which areas must remain untouched.

Rivya currently bills 140 input credits and 1120 output credits per million tokens. That tier fits large or high-risk engineering tasks where a shallow plan could create expensive rework.

Choose GPT-5.3 Codex for large-codebase debugging and complex implementation planning. Choose a lower Codex tier for bounded edits, or a general chat model for non-implementation research and writing.

Start here when the first response should test multi-file debugging, refactor analysis, technical planning, or codebase-level reasoning on one specific Codex model. That gives you a contained first turn to check the prompt, direction, and response quality before moving into a longer project.

This page is set up as the public chat entry for GPT-5.3 Codex. That helps when hard debugging in large codebases depends on screenshots, charts, or other visual evidence from the first turn.

On GPT-5.3 Codex, it matters more to frame the code goal, the existing context, and the output shape than to hunt for extra controls. If the first turn already contains the repo background, acceptance criteria, and constraints, the model usually gets useful much faster on hard debugging in large codebases.

The page is publicly visible, but the actual first send is still gated behind sign in. Rivya currently bills this by usage: 140 input credits and 1120 output credits per million tokens. You can use this page to frame the question and choose the model first, then sign in when you are ready to start the live thread.

Stay on this page while the job is still a first conversation and you are testing whether GPT-5.3 Codex can get traction on hard debugging in large codebases from the first turn. Open the full Studio once the work needs saved context, attached files, follow-up rounds, or a thread you know you will keep expanding.