See how ChatGPT, Perplexity and Google AI Overviews describe you today

Free AI Visibility Audit
Surge45°
OpenAI model°

GPT-5.6 Luna Pro

GPT-5.6 Luna Pro is OpenAI's GPT-5.6 Luna served with its reasoning mode set to "pro", a higher-effort configuration of the same underlying model aimed at complex tasks.

OpenAIVerified 24/09/2026Released 09/07/2026

01 / decision

Decision snapshot

Each figure sits next to the middle of the field, so it can be read as dear or cheap, wide or narrow, rather than floating on its own. Compared against the 152 models we track, not against an absolute standard.

Capability

Not measured

No published benchmark scores yet

Input / 1M tokens

$0.20

field median $0.42

Output / 1M tokens

$1.20

field median $1.68

Context

1,050K

field median 524K

02 / overview

What GPT-5.6 Luna Pro is, and when to reach for it

Four questions, answered separately, because somebody arrives at one of them rather than at the top of the page.

What it is

The job it was built for, and the job it is not for.

GPT-5.6 Luna Pro is not a separate model, it is GPT-5.6 Luna running at a higher reasoning setting, so the weights and the knowledge are identical and only the response quality on hard problems changes. It is built for work where the answer needs to hold up: multi-step analysis, long documents, tasks where a first-pass answer is usually wrong. It is not the right tool for high-volume routine calls, where the standard Luna setting does the same job.

When it arrived, and when to use it

Where it sits in its line, and when a sibling is the better pick.

GPT-5.6 Luna Pro was first seen on 9 July 2026, arriving alongside the standard GPT-5.6 Luna as the "pro" reasoning mode of the same release. Pick it when a task is genuinely complex and the cost of a wrong answer is higher than the cost of the extra reasoning. Pick plain GPT-5.6 Luna for classification, extraction, short rewrites and anything you run thousands of times a day.

How you reach it

The API, the apps it powers, and what its limits let you do.

You reach GPT-5.6 Luna Pro through the OpenAI API, either by calling the Pro variant directly or by setting `reasoning.mode` to `pro` on GPT-5.6 Luna, which is documented in OpenAI's reasoning guide. It takes text, images and files, so you can hand it a contract, a spreadsheet export or a screenshot and reason over it in place. The context window runs to seven figures and the output ceiling is generous, which means whole document sets go in and full reports come back out in one pass rather than being chunked and stitched.

Why it matters

What changes because this exists, or why it does not.

Because the Pro setting is a flag rather than a different model, teams can route by difficulty inside one codebase: cheap mode for the bulk of traffic, pro mode for the requests that need it, with no prompt rewriting or evaluation redo between the two. That removes the usual awkwardness of maintaining two models with different behaviour just to buy better reasoning on a minority of calls.

Follows GPT-5.6 Luna. Superseded by GPT-5.6 Sol. See the whole line.

03 / evidence

How much of this is verified

Split by category, so a strong number never hides a thin evidence base. Verified means we read it on the benchmark's own published results; a provider's claim about its own model is shown and labelled rather than dropped.

No published benchmark scores for this model yet.

We publish a score only where we can link the result to where it was published. Until a benchmark result for this model exists in a source we read, this section stays empty rather than being filled with a provider's marketing figure.

How we decide what counts as evidence

04 / ledger

Benchmark ledger

Every published row, grouped by category, each compared with the best published score on the same benchmark. 'Is 64% good' is a question nobody can answer; '26 points behind the leader' is one anybody can.

Nothing in the ledger yet.

Each row here carries a score, the benchmark it came from, what the leading model scored on the same test, and a link to the published result. Rows appear as results are published and read.

How we decide what counts as evidence

05 / capability

Capability shape

Where this model is strong, and against how many peers. Ranks are against models with evidence in that category, not against everything we track: ranking against models nobody tested would rank who published, not who is better.

No category scores to shape yet.

A category score is the weighted mean of the benchmarks published for it. With no published rows there is nothing to average, and an empty chart drawn at zero would say something false.

How we decide what counts as evidence

06 / cost

What it costs

List API rates as last read from the provider, with the source on every row, plus every change we have recorded since we started tracking it.

GPT-5.6 Luna Pro API pricingSurge45°
ChargePriceUnitRead onSource
Input$0.20per 1M tokens2026-09-24Check
Output$1.20per 1M tokens2026-09-24Check

GPT-5.6 Luna Pro is priced at the low end of the current field for a frontier-family model, with output costing several times input, which is the normal shape. The real cost driver is not the rate but the reasoning mode itself, since pro spends more tokens thinking before it answers, so budget on observed token use rather than on the headline rate.

What a month costsSurge45°
WorkloadInput / monthOutput / monthCost
A small product team20M tokens5M tokens$10.00
A busy support assistant200M tokens40M tokens$88.00
A document pipeline1000M tokens100M tokens$320.00

List API rates, no caching and no batch discount, which both providers offer and which change the answer a great deal. Treat these as the ceiling, not the bill.

07 / specs

Specifications

As listed by the provider's own catalogue and re-read every few hours. Anything absent is absent there too.

SpecificationSurge45°
Context window1,050,000 tokens
Maximum output128,000 tokens
Modalitiesfile, image, text
Released09/07/2026
StatusCurrent
Catalogue identifieropenai/gpt-5.6-luna-pro

08 / lineage

Lineage

What this model replaced, what replaced it, and what else its provider has in the field.

Also from OpenAI

09 / line

The line

Every model in this family in release order, so a page from eight months ago says in one glance that two newer ones exist.

Came before

← GPT-5.6 Luna

Came after

GPT-5.6 Sol →
  1. 01GPT-4.114/04/2025
  2. 02GPT-4.1 Mini14/04/2025
  3. 03GPT-4.1 Nano14/04/2025
  4. 04GPT-507/08/2025
  5. 05GPT-5 Mini07/08/2025
  6. 06GPT-5 Nano07/08/2025
  7. 07GPT-5 Pro06/10/2025
  8. 08GPT-5.113/11/2025
  9. 09GPT-5.1-Codex13/11/2025
  10. 10GPT-5.1-Codex-Max04/12/2025
  11. 11GPT-5.210/12/2025
  12. 12GPT-5.2 Pro10/12/2025
  13. 13GPT-5.6 Luna09/07/2026
  14. 14GPT-5.6 Luna Pro09/07/2026
  15. 15GPT-5.6 Sol09/07/2026
  16. 16GPT-5.6 Sol Pro09/07/2026
  17. 17GPT-5.6 Terra09/07/2026
  18. 18GPT-5.6 Terra Pro09/07/2026
  19. 19GPT-6 Astra04/09/2026
  20. 20GPT-6 Astra Pro04/09/2026
  21. 21GPT-6 Luna22/09/2026
  22. 22GPT-6 Luna Pro22/09/2026
  23. 23GPT-6 Sol22/09/2026
  24. 24GPT-6 Sol Pro22/09/2026

Ordered by release date and worked out from the naming, so a new member slots in as soon as its page exists. A retired model keeps its page and its place in the line.

10 / notes

Our notes

What this model changes for a brand trying to be cited in AI answers, and every change we have logged since it launched.

What it changes for you

When an assistant escalates to a pro reasoning mode, it reads more sources and cross-checks them, so thin pages that survive a quick answer get dropped from a considered one. For a SaaS brand that means the pages worth investing in are the ones that hold up under scrutiny: specific numbers, named limitations, comparisons that admit where you lose. The long context also means a model can hold your whole documentation set at once, so consistency across your pages now matters as much as the quality of any single one.

Where buyers meet this model

Buyers mostly meet GPT-5.6 Luna Pro through the API, either directly or inside a product that has routed a hard request to it. There is no separate consumer app for the Pro setting, it surfaces as the deeper answer inside whatever assistant or research tool the buyer is already using, including AI search surfaces built on OpenAI models.

Change log

Nothing published here yet. Changes appear within hours of a provider announcing them.

11 / questions

Questions

The things people ask about this model, answered from what is on this page rather than from anywhere else.

Is GPT-5.6 Luna Pro a different model from GPT-5.6 Luna?
No. It is the same underlying model, served with the reasoning mode set to pro. The difference is how much effort it spends on a response, not what it knows.
When should I use the pro reasoning mode instead of the standard one?
Use it for complex, multi-step tasks where response quality matters more than latency or cost. For routine, high-volume calls the standard GPT-5.6 Luna setting gives you the same model at lower effort.
What inputs does GPT-5.6 Luna Pro accept?
Text, images and files, so documents and screenshots can go straight into the prompt without a separate extraction step.
Surge45°

Is GPT-5.6 Luna Pro recommending you?

Models change what gets cited. We measure whether AI answers name your brand or your competitors across every assistant, and show you what to change.

Free AI visibility audit Book a call