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Add plan_model Configuration for /plan Mode #13206

@yanun0323

Description

@yanun0323

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.


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.


Proposed Solution

Introduce a configuration option:

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.

Example Configuration

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

Why This Matters

  1. Enables separation of reasoning-heavy planning from cost-efficient
    execution.
  2. Reduces workflow friction (no manual model switching).
  3. Achieves feature parity between /plan and /review.
  4. Improves suitability for structured multi-phase engineering
    workflows.

Closing

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

Additional information

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