See how ChatGPT, Perplexity and Google AI Overviews describe you today
Free AI Visibility AuditGPT-5.6 Terra Pro is OpenAI's GPT-5.6 Terra served with its reasoning mode set to "pro", a higher-effort setting that trades speed and cost for better answers on complex work.
OpenAIVerified 24/09/2026Released 09/07/202601 / decision
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
$2.00
field median $0.42
Output / 1M tokens
$12.00
field median $1.68
Context
1,050K
field median 524K
02 / overview
Four questions, answered separately, because somebody arrives at one of them rather than at the top of the page.
The job it was built for, and the job it is not for.
GPT-5.6 Terra Pro is not a separate model. It is the same underlying GPT-5.6 Terra weights running with `reasoning.mode` set to `pro`, so OpenAI lets it think harder before it answers. That makes it a pick for genuinely hard, multi-step problems, and the wrong tool for high-volume classification, extraction or chat where the base setting already lands the answer.
Where it sits in its line, and when a sibling is the better pick.
GPT-5.6 Terra Pro was first seen on 9 July 2026, alongside the standard GPT-5.6 Terra it is derived from. Reach for it when a task has failed on the base model for reasoning rather than knowledge reasons: long analyses, code that has to hold together across many files, work where a wrong answer costs more than the extra tokens. If you are running the same prompt thousands of times, stay on standard Terra.
The API, the apps it powers, and what its limits let you do.
GPT-5.6 Terra Pro is reached through the OpenAI API and through OpenRouter, selected as its own model slug rather than configured by hand. It takes text, images and file input, and the very large context window means whole document sets, long transcripts or a sizeable codebase can go in one request, with room for a long structured answer coming back rather than a truncated one.
What changes because this exists, or why it does not.
GPT-5.6 Terra Pro turns reasoning effort into a deployment choice rather than a model migration. A team can run the cheap setting as its default and route only the hard cases to the pro setting, with identical prompts and identical behaviour underneath, which removes the usual work of evaluating and maintaining a second model for the difficult tail.
Follows GPT-5.6 Terra. Superseded by GPT-6 Astra. See the whole line.
03 / evidence
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 evidence04 / 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 evidence05 / capability
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 evidence06 / cost
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.
| Charge | Price | Unit | Read on | Source |
|---|---|---|---|---|
| Input | $2.00 | per 1M tokens | 2026-09-24 | Check |
| Output | $12.00 | per 1M tokens | 2026-09-24 | Check |
GPT-5.6 Terra Pro carries a premium on both input and output against the standard Terra setting, with output priced several times above input, which is the usual shape for a reasoning model that generates a lot of thinking before it answers. It sits in the mid range of frontier pricing, cheap enough to use as an escalation path but not as a default for volume work.
| Workload | Input / month | Output / month | Cost |
|---|---|---|---|
| A small product team | 20M tokens | 5M tokens | $100.00 |
| A busy support assistant | 200M tokens | 40M tokens | $880.00 |
| A document pipeline | 1000M tokens | 100M tokens | $3,200.00 |
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
As listed by the provider's own catalogue and re-read every few hours. Anything absent is absent there too.
| Context window | 1,050,000 tokens |
|---|---|
| Maximum output | 128,000 tokens |
| Modalities | file, image, text |
| Released | 09/07/2026 |
| Status | Current |
| Catalogue identifier | openai/gpt-5.6-terra-pro |
08 / lineage
What this model replaced, what replaced it, and what else its provider has in the field.
Also from OpenAI
09 / 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 TerraCame after
GPT-6 Astra →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
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
For a SaaS brand, the practical point is that the answer engines quoting you are increasingly running two settings of the same model, and the pro setting reads more of a source before it decides what to cite. Pages that hold up under a careful multi-step read, with claims that are attributable and internally consistent, do better here than pages tuned for a quick skim. Depth and structure now earn something they did not earn when every answer came from a fast pass.
Buyers meet GPT-5.6 Terra Pro mostly through products built on it rather than by name. It is an API and OpenRouter option, so it surfaces inside research assistants, coding tools and internal analysis workflows that route their harder requests to a higher reasoning setting, while the everyday chat traffic in those same products runs on the standard model.
Nothing published here yet. Changes appear within hours of a provider announcing them.
11 / questions
The things people ask about this model, answered from what is on this page rather than from anywhere else.
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.