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
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Check which model Codex CLI is using and which reasoning-effort values that model supports.
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Add the override to the command:
--config model_reasoning_effort=<supported-value>. For example:codex exec ... --config model_reasoning_effort=low.Recommended Free Tools
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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.
Rank #2
| 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.
What if the override does not work?
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Verify the exact value against the selected model’s documentation; a value listed for other models may not be accepted.
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Check the installed CLI version’s help and documentation if the command rejects the option or the behavior differs from expectations.
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Do not assume a universal precedence rule between this flag, saved configuration, environment variables, or aliases. The cited CLI example does not establish one for every release.
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