Add a Smart model picker option that automatically routes each task to the right Codex model

What variant of Codex are you using?

Codex App, CLI, and ChatGPT Work

What feature would you like to see?

The problem

Choosing a model is an unnecessary decision point on every task. Frequent Codex users have to guess whether a task needs the strongest model or whether a lighter model would be enough. The result is either spending premium usage on simple work or underpowering a complex task and needing retries.

Proposed feature

Add Smart as an option in the model picker, plus an optional /smart prompt command for one-off use.

Before a task is dispatched, Smart would select the best available model and reasoning level from task signals such as task type, repository scope, ambiguity, expected tool use, and estimated complexity. It should be available consistently in the Codex App, CLI, and ChatGPT Work.

Important behavior

• The routing decision should not consume a separate user turn or meaningful extra usage. A lightweight local/rule-based classifier or platform-side router could make the choice.
• Respect user controls: a maximum-cost/maximum-capability setting, a default preference, and an easy per-task override.
• Show a small, non-intrusive explanation after routing (for example, “Smart chose GPT-5.6 Terra — focused code change in a small repo”) so the choice is understandable.
• Escalate only when justified, rather than silently using the most expensive model by default.
• If Smart is uncertain, choose a sensible default and let the user change it before or after the task.

Why this matters

This would make Codex easier to trust for everyday use: users can focus on their actual work, conserve their limited premium usage for work that genuinely needs it, and still get stronger reasoning for difficult multi-file, debugging, or agentic tasks. It is especially valuable for students, individual developers, and teams that use Codex frequently but do not want to become experts in model tradeoffs.

Additional information

I started exploring this as a standalone “Smart Model Selector,” but the product itself is the right place for it because only Codex has the full context on model availability, capacity, and usage economics. The ideal experience is a durable Smart picker setting for all tasks, with /smart as a convenient one-off override.

Start by locating the model-picker and task-dispatch entry points for the Codex App, CLI, and ChatGPT Work, along with the proposed /smart command. Define how routing, user limits, overrides, explanations, and uncertainty handling should work across those surfaces. Done means Smart can select an appropriate available model without a separate turn and users can understand or override the choice.