Choose a model
In the ChatGPT desktop app, use the model and reasoning control beneath the composer to choose an available model and adjust its reasoning effort.
Higher reasoning effort can improve results for complex tasks, but it takes longer and uses more tokens. Start with the default effort and increase it when the task needs deeper planning or analysis.
Ultra mode goes beyond a single-agent run. It uses subagents to accelerate complex work, making it useful for larger tasks that can be split across subagents.
Choose a model
These recommendations apply to ChatGPT Work on the web. Use the model and reasoning control beneath the composer to choose an available model and adjust its reasoning effort.
Higher reasoning effort can improve results for complex tasks, but it takes longer and uses more tokens. Start with the default effort and increase it when the task needs deeper planning or analysis.
Ultra mode goes beyond a single-agent run. It uses subagents to accelerate complex work, making it useful for larger tasks that can be split across subagents.
Choose a model
In an interactive CLI session, use /model to switch models or adjust
reasoning effort. You can also choose a model when you launch Codex with
--model or its -m alias:
codex --model gpt-5.6The same option works with non-interactive runs. For example:
codex exec -m gpt-5.6 "Review the current changes"Higher reasoning effort can improve results for complex tasks, but it takes longer and uses more tokens. Start with the default effort and increase it when the task needs deeper planning or analysis.
Ultra mode goes beyond a single-agent run. It uses subagents to accelerate complex work, making it useful for larger tasks that can be split across subagents.
Select Reasoning Level for gpt-5.6-sol
Press enter to confirm or esc to go back
Choose a model
Use the model switcher below the composer to choose an available model and reasoning effort.
Higher reasoning effort can improve results for complex tasks, but it takes longer and uses more tokens. Start with the default effort and increase it when the task needs deeper planning or analysis.
Ultra mode goes beyond a single-agent run. It uses subagents to accelerate complex work, making it useful for larger tasks that can be split across subagents.
Recommended models
Our most capable model for complex work across code, apps, and research, combining advanced reasoning, computer use, and stronger judgment.
The most capable GPT-5.6 model for complex coding, computer use, research, and cybersecurity.
Balanced GPT-5.6 model for everyday work, with performance competitive with GPT-5.5 at a lower cost.
Fast and affordable GPT-5.6 model that delivers strong capability at the lowest cost in the family.
Text-only research preview model optimized for near-instant, real-time coding iteration. Available to ChatGPT Pro users.
Availability depends on the rollout, your sign-in method, and your client. See pricing for plan access and usage, and workspace model availability for Enterprise access.
Start with the default Power setting available to your account. Move toward
Smarter for deeper reasoning or Faster for faster, lower-cost work.
Open Advanced when you want gpt-5.6-luna or a specific model, reasoning
effort, or speed.
The picker illustrations show GPT-5.6 controls. For eligible Pro, Business ($100), and Enterprise accounts, the Astra rollout updates the Power options to Terra Light, Sol Light, Sol Medium, Astra Light, Astra Medium, and Astra Extra High. Options can differ by plan and rollout stage.
Experimental context management
On supported Codex clients, users signed in with ChatGPT Plus or Pro can opt in to experimental context management. Astra keeps notes across context windows and can search earlier messages and tool results from the same task. This experiment is off by default and isn't available with Business, Enterprise, or API-key sign-in at launch.
To opt in, set features.context_management.experimental_mode = true in your
config.toml, then start a new task. See the configuration reference
for the setting and configuration basics
for the file location. Workspace requirements still apply.
Choosing Astra, Sol, Terra, and Luna
Choose Astra when a task needs the strongest capability across multiple steps and tools. Sol offers depth and polish, Terra suits everyday work, and Luna suits clear, repeatable tasks.
Where each model shines
- Astra, for the hardest end-to-end work. Choose Astra for complete workflows across code, apps, and research that need sustained reasoning and judgment. Give it the sources, templates, constraints, and checks that define a useful result. Astra is better at asking focused questions and incorporating your guidance while keeping the original goal and constraints in view.
- Sol, for complex, open-ended work. Choose Sol for ambiguous, difficult, or high-value tasks that need extra analysis, judgment, or polish, such as complex code changes, deep research, or polished documents. For narrower tasks, define what done looks like to keep the work focused.
- Terra, the pragmatic all-rounder. Choose Terra for everyday work that needs strong reasoning and tool use when you do not need Sol's full depth. It is a natural starting point for work you previously gave GPT-5.5.
- Luna, for clear, repeatable tasks. Choose Luna for specific, high-volume tasks when you know what a good result looks like, such as extraction, classification, transformation, and structured summaries.
Pick a reasoning effort
Use the lowest reasoning effort that produces the result you need. Increase it for tasks that need more planning, analysis, or checking.
- Light in the ChatGPT desktop app, ChatGPT Work on the web, and IDE extension, or Low in the CLI, suits quick, well-scoped tasks.
- Medium balances speed and depth for tasks that need more planning.
- High and Extra High suit difficult work with multiple steps, sources, or tradeoffs.
There is no exact mapping from GPT-5.5 reasoning efforts to GPT-5.6. Try a familiar task at a lower setting and adjust based on the result.
Know when to use Max or Ultra
Max gives the selected model more time to reason about a single task. Use it for the hardest problems, when depth matters more than speed or usage. If you don't see Max in your options, you'll have to enable it in your app settings.
Ultra uses subagents to handle separate parts of a complex task in parallel. Choose it when you can divide the work into meaningful parts. Most tasks do not need Max or Ultra.
If Ultra doesn't appear in the desktop app's model slider, go to Settings > Configuration, then turn on Ultra in model picker slider.
Other models
When you sign in with ChatGPT, Codex works best with the recommended models listed above.
GPT-5.4 and GPT-5.4 mini retire from Codex on August 31, 2026.
If you sign in with ChatGPT, replace gpt-5.4 with gpt-5.6-terra and
gpt-5.4-mini with gpt-5.6-luna in saved configurations, custom agents, and
scheduled tasks. The OpenAI API and Codex authenticated with your own API key
aren't affected.
View other models
Previous-generation flagship model for complex coding, computer use, knowledge work, and research workflows.
Flagship model for professional work with strong coding, reasoning, tool use, and agentic workflow capabilities.
Fast, efficient mini model for responsive coding tasks and subagents.
You can also point Codex at any model and provider that supports either the Chat Completions or Responses APIs to fit your specific use case.
Support for the Chat Completions API is deprecated and will be removed in future releases of Codex.
Deprecated Codex models
The gpt-5.4 and gpt-5.4-mini models retire from Codex with ChatGPT sign-in
on August 31, 2026. Replace gpt-5.4 with gpt-5.6-terra and
gpt-5.4-mini with gpt-5.6-luna in workspace defaults, saved model
settings, managed configurations, custom agents, and scheduled tasks.
The gpt-5.2 and gpt-5.3-codex models are already deprecated in Codex when
you sign in with ChatGPT. Update scripts, configuration files, and
codex exec --model commands that still reference those models.
The OpenAI API and Codex authenticated with your own API key aren't affected by the GPT-5.4 retirement. For current API model availability, see the API models page.
Configure your default local model
The ChatGPT desktop app, Codex CLI, and IDE extension use the same config.toml
configuration file. To specify a model, add a
model entry to your configuration file. If you don't specify a model, the
ChatGPT desktop app, Codex CLI, or IDE extension uses a recommended model.
model = "gpt-5.6"Choose a model for cloud chats
Currently, you can't change the default model for Codex cloud chats.