Codex Usage
Last updated 13 Sep 2026

GPT-5.6 Luna Codex Usage Limits

GPT-5.6 Luna Codex usage draws from the same shared Work and Codex plan allowance as Terra, Sol, and Astra — OpenAI publishes estimated 5-hour local-message ranges of 250 to 2,000 on Plus and Business Standard, up to 5,000 to 40,000 on Pro $200 (20x). Luna also carries the lowest current token rates of the four models, making it OpenAI's fastest and lowest-cost GPT-5.6 option for cost-sensitive, high-volume work. These are OpenAI's estimates, not fixed message quotas — actual usage varies with the task, and weekly limits may also apply.

Plan TierLuna 5-Hour Estimate
ChatGPT Plus ($20/mo)250 to 2,000 local messages
ChatGPT Pro $100 (5x)1,250 to 10,000 local messages
ChatGPT Pro $200 (20x)5,000 to 40,000 local messages
Business Standard250 to 2,000 local messages
Business PremiumNo 5-hour limit (5x Standard included usage; weekly cap not published)

Weekly allowances are not published by OpenAI for any tier. Run /status in the CLI for your account's actual remaining percentages and reset times.

Does GPT-5.6 Luna Have Its Own Quota?

No. Standard Luna usage is not a separate quota — it draws from the same shared Work and Codex plan allowance that Terra, Sol, and Astra all draw from. Switching your active model to Luna does not unlock additional capacity; it changes how much of your existing allowance each message consumes.

The one genuinely separate Luna-specific allowance is Luna Reserve, a fallback capacity available only to select personal Plus and Pro accounts. Luna Reserve provides selected accounts additional Luna usage after regular usage is exhausted — it is not available in Business or Enterprise workspaces, and it has its own usage limit separate from the shared allowance covered on this page.

One Controlled Test: Luna's Measured 5-Hour Impact

In a controlled ChatGPT Plus experiment on one frozen coding task, GPT-5.6 Luna passed all 112 deterministic tests at Medium reasoning effort — the same result Sol and Astra achieved in the same run. Luna's run did not move the displayed 5-hour percentage at Codex Usage's 1-percentage-point resolution, while it took the longest to finish: about 28% slower than Sol and 8% slower than Astra.

This is one controlled run on one task, not a universal “Luna uses zero quota” claim. See the full first-party measurement across Luna, Sol, and Astra for the complete table and methodology.

Luna vs. Terra, Sol, and Astra: Published Message Estimates

OpenAI publishes substantially higher estimated 5-hour local-message ranges for Luna than for its other GPT-5.6 and GPT-6 models. Here is how all four compare, plan by plan.

Last updated: 13 Sep 2026. Figures are OpenAI's published estimates, not guaranteed caps.
Plan TierGPT-5.6 LunaGPT-5.6 TerraGPT-5.6 SolGPT-6 Astra
ChatGPT Plus ($20/mo)250 to 2,00025 to 20010 to 1005 to 45
ChatGPT Pro $100 (5x)1,250 to 10,000125 to 1,00050 to 50025 to 225
ChatGPT Pro $200 (20x)5,000 to 40,000500 to 4,000200 to 2,000100 to 900
Business Standard250 to 2,00025 to 20010 to 1005 to 45

Business Premium removes the 5-hour limit entirely for all models (5x Standard included usage, exact weekly cap not published). See ChatGPT Business Codex limits for details.

Why Luna Is OpenAI's Most Usage-Efficient Model

OpenAI publishes substantially higher estimated local-message ranges for Luna than for Terra, Sol, or Astra, and Luna also carries the lowest current token rates of the four models. These figures make Luna the most usage-efficient option in OpenAI's published model guidance, but they are not a fixed conversion formula for included subscription allowance.

Current Work & Codex Rate (per 1M tokens)InputCached InputOutput
GPT-5.6 Luna$0.20$0.02$1.20
GPT-5.6 Terra$2.00$0.20$12.00
GPT-5.6 Sol$4.00$0.40$20.00
GPT-6 Astra$10.00$1.00$50.00
Luna vs. Sol

Luna is 20x cheaper than Sol on input and cached input, and approximately 16.7x cheaper on output.

Luna vs. Astra

Luna is 50x cheaper than Astra on input and cached input, and approximately 41.7x cheaper on output.

These ratios describe metered token rates, not a compute-footprint explanation and not a guaranteed multiplier on included subscription allowance. Included plan usage and metered token billing are distinct: purchased credits and eligible token-based Work and Codex activity use the rate card above, while direct API usage is billed separately under usage-based API billing and API rate limits. See Codex credits, paid instant resets, banked resets, and API billing for how these fit together.

When to Use Luna Instead of Terra, Sol, or Astra

OpenAI describes Luna as its fastest and lowest-cost GPT-5.6 model, optimized for cost-sensitive, high-volume workloads. Editorially, that fits clearly-scoped, repeatable tasks where you already know what a good result looks like — formatting, extraction, test scaffolding, routine repository discovery, and other repetitive work are illustrative examples, not an official OpenAI task list. For ambiguous, high-value, or reasoning-heavy work, OpenAI's own guidance points toward Sol or Astra instead. See the full Codex recommended model and Power presets guide for OpenAI's model-by-model positioning and how to select Luna explicitly.

What OpenAI Has Not Published About Luna

1. Estimated Ranges vs Fixed Caps:OpenAI publishes estimated local-message ranges for Luna by plan. It has not published guaranteed fixed prompt caps — actual usage varies with task complexity, reasoning settings, context size, and tools.
2. No Weekly Message Cap:OpenAI does not publish a numeric weekly message ceiling for any model or plan tier, including Luna.
3. No Internal Allowance Formula:OpenAI publishes token rate cards for metered credit consumption, but it does not publish the internal formula converting token usage into included 5-hour and weekly percentage allowances.
4. No Architectural Efficiency Explanation:OpenAI does not publish a technical explanation (such as a lighter model architecture) for why Luna's published ranges are higher and its token rates lower. The figures are published; the underlying mechanism is not.

How to Check Your Remaining Codex Quota

Because Luna draws from your overall Work and Codex allowance, check your live 5-hour and weekly percentages by running the status command in the terminal:

Check your usage
/status

Displays your current 5-hour and weekly remaining percentages and reset times. Run it in your own CLI session for your actual numbers.

You can also check the official ChatGPT usage settings page or use our free local Codex Usage desktop monitoring tool. Neither OpenAI nor the local tool attributes usage specifically to Luna on a per-prompt or token level.

Frequently Asked Questions

What is GPT-5.6 Luna in Codex?

GPT-5.6 Luna is OpenAI's fastest and lowest-cost GPT-5.6 model, optimized for cost-sensitive, high-volume workloads. In Codex and ChatGPT Work, it is one of four selectable models alongside Terra, Sol, and GPT-6 Astra, all drawing from the same shared Work and Codex plan allowance.

How many messages do I get with Luna on my plan?

OpenAI publishes official 5-hour local-message estimates: 250 to 2,000 on Plus and Business Standard, 1,250 to 10,000 on Pro $100 (5x), and 5,000 to 40,000 on Pro $200 (20x). These are OpenAI's estimated ranges, not fixed message quotas — actual usage varies with the task, input and output size, reasoning settings, speed settings, and tools. Weekly limits may also apply.

Does Luna have its own separate quota?

No. Standard Luna usage draws from the same shared Work and Codex plan allowance as Terra, Sol, and Astra — it is not a separate quota. The one Luna-specific allowance that is separate is Luna Reserve, a fallback capacity available to select personal Plus and Pro accounts after regular usage is exhausted. See the Luna Reserve guide for that distinct feature.

Is Luna actually cheaper than Sol and Astra?

Yes, on OpenAI's published current Work and Codex token rates. Luna is 20x cheaper than Sol on input and cached input, and about 16.7x cheaper on output. Luna is 50x cheaper than Astra on input and cached input, and about 41.7x cheaper on output. These are metered token rates for purchased credits and eligible token-based activity — not a formula for converting into included subscription allowance. See the Codex credits and billing guide for how included usage and metered billing differ.

What kinds of tasks is Luna best for?

OpenAI positions Luna for cost-sensitive, high-volume workloads. Editorially, that tends to fit clearly-scoped, repeatable tasks such as formatting, extraction, test scaffolding, routine repository discovery, and other repetitive work where you already know what a good result looks like — these are illustrative examples, not an official OpenAI task list. For ambiguous or high-stakes work, OpenAI's own guidance points toward Sol or Astra instead.

How is Luna different from Luna Reserve?

Luna (this page) is one of the four selectable Codex models, and ordinary usage of it draws from your regular shared Work and Codex allowance. Luna Reserve is a separate, additional fallback allowance available only to select personal Plus and Pro accounts, which activates after your regular usage is exhausted and can only run GPT-5.6 Luna. See the dedicated Luna Reserve guide for eligibility and troubleshooting.

How do I select Luna instead of the default model?

Open Advanced in the model picker and choose gpt-5.6-luna, run /model in an active Codex CLI session, pass --model gpt-5.6-luna as a launch flag, or set model = "gpt-5.6-luna" in config.toml. See the recommended model guide for the full list of selection methods.

Limits by plan
Other models and fallback capacity
Resets and billing