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Codex CLI Reasoning Effort: Set a Per-Run Override

Use Codex CLI’s --config model_reasoning_effort= option for a one-off override. Supported values and defaults depend on the selected model.
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To change reasoning effort for a Codex CLI run, pass --config model_reasoning_effort=<value> in the invocation. For example, the OpenAI Cookbook demonstrates low: codex exec ... --config model_reasoning_effort=low. The available values depend on the selected model, so check its documentation before choosing one.

How to set reasoning effort for one CLI invocation

  1. Check which model Codex CLI is using and which reasoning-effort values that model supports.

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  2. Add the override to the command: --config model_reasoning_effort=<supported-value>. For example: codex exec ... --config model_reasoning_effort=low.

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  3. Run the command. If the CLI rejects the value or the setting does not behave as expected, consult help or documentation for your installed CLI version and selected model.

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The OpenAI Cookbook documents this form in an example that pins @openai/[email protected]; it is a concrete example for that version context, not confirmation that every later release has identical syntax or precedence. See Build iterative repair loops with Codex.

Which reasoning-effort value should you use?

OpenAI says supported values are model-dependent and can include none, minimal, low, medium, high, xhigh, and max. That list does not mean every model accepts every value. For example, the reasoning guide says GPT-6 Astra does not support none, and GPT-6.1 Sol does not support none or minimal; it identifies medium as GPT-6.1 Sol’s default.

Effort choice When it may fit Trade-off described by OpenAI
low When speed and token economy matter more than deeper reasoning. Lower effort generally favors faster responses and lower token use.
medium A balanced starting point for many workloads, if supported by the model. Balances speed and token use against reasoning depth; it is not a universal default.
high Harder reasoning tasks where more latency and token use are acceptable. Higher effort allows more complete reasoning, with greater latency and token use.
xhigh or max Demanding cases where additional latency and token use are justified, if supported. Higher effort allows more complete reasoning; outcomes vary by model and task.

These are qualitative trade-offs, not measured guarantees for a particular workload. Confirm the selected model’s supported values and defaults in the OpenAI reasoning guide.

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Do not confuse the CLI setting with API parameters

For Codex CLI, the documented configuration key in the Cookbook example is model_reasoning_effort. OpenAI’s API uses different names: Responses requests use reasoning.effort, while Chat Completions requests use reasoning_effort. These are settings for different interfaces; do not substitute API request syntax for the CLI option. See the reasoning guide, Codex Cookbook example, and Using GPT-6 migration guidance.

The migration guidance also describes a configuration_update input item for changing effort on later turns in supported standard, single-agent mode with successive GPT-6-family Responses API requests. That is an API mechanism, not the one-off Codex CLI override.

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What if the override does not work?

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