Add `plan_model` Configuration for `/plan` Mode

What variant of Codex are you using?

App and IDE Extension

What feature would you like to see?

Feature Request: Add plan_model Configuration for /plan Mode

Summary

Currently, Codex allows configuring a dedicated review_model for
/review mode.\
However, /plan mode always uses the active session model and does not
support a separate model override.

This proposal suggests adding a plan_model configuration option,
similar to review_model, so that /plan mode can use a different
model from the main execution model.

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Problem

In practical engineering workflows, planning and execution have
different optimization goals:

• Planning benefits from stronger reasoning capability.
• Execution may prioritize speed, cost efficiency, or determinism.

At present, to use a stronger model for planning, users must:

1. Start a separate session with a different model, or
2. Manually switch models before entering /plan, then switch back

before execution.

This introduces operational friction and increases the chance of
mistakes.

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Proposed Solution

Introduce a configuration option:

``` to.ml
plan_model = "gpt-5.3-codex"

### Expected Behavior

-   When entering `/plan`, Codex uses `plan_model` if defined.
-   If `plan_model` is not defined, fallback to the current session
    model (existing behavior).
-   Normal execution continues to use the main `model`.
-   `/review` continues to use `review_model`.

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## Example Configuration

``` toml
model = "gpt-5.3-codex-spark"
plan_model = "gpt-5.3-codex"
review_model = "gpt-5.3-codex"

Resulting Behavior

• /plan → uses gpt-5.3-codex
• normal execution → uses gpt-5.3-codex-spark
• /review → uses gpt-5.3-codex

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Why This Matters

1. Enables separation of reasoning-heavy planning from cost-efficient

execution.

1. Reduces workflow friction (no manual model switching).
2. Achieves feature parity between /plan and /review.
3. Improves suitability for structured multi-phase engineering

workflows.

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Closing

This feature would significantly improve advanced workflows where
planning and execution have different optimization targets (reasoning
quality vs cost/latency).

Additional information

_No response_