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Free AI Visibility AuditGPT-5.2 is OpenAI's frontier model in the GPT-5 series, built for agentic work and long-context reasoning across text, images and uploaded files. It uses adaptive reasoning, spending more computation on hard requests and answering quickly on simple ones.
OpenAIVerified 24/09/2026Released 10/12/202501 / 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 126 models we track, not against an absolute standard.
Capability
Not measured
No published benchmark scores yet
Input / 1M tokens
$1.75
field median $0.30
Output / 1M tokens
$14.00
field median $1.25
Context
400K
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-5.2 is a general-purpose frontier model aimed at agentic tasks, the kind where a model has to plan, call tools and keep track of a long job rather than answer one question. It handles text, images and files in the same request, so document-heavy work sits in scope. It is not a small, cheap classifier or a high-volume routing model, and it is not a dedicated image or audio generator.
Where it sits in its line, and when a sibling is the better pick.
GPT-5.2 first appeared on 10 December 2025 as the newest entry in the GPT-5 line, positioned above GPT-5.1 on agentic and long-context work. Pick it when a task runs long, spans many documents, or needs a chain of tool calls to hold together. For short, high-volume calls where the answer is obvious, a smaller sibling will do the same job for less.
The API, the apps it powers, and what its limits let you do.
GPT-5.2 is reached through the OpenAI API and sits behind OpenAI's consumer and developer products. The context window is large enough to hold a substantial corpus of documentation, transcripts or code in a single request, and the output ceiling allows long reports, migrations and full drafts in one pass. File and image input mean PDFs, screenshots and diagrams can go in alongside the prompt without a separate extraction step.
What changes because this exists, or why it does not.
The practical change is in jobs that used to need orchestration: chunking a large document set, stitching partial outputs together, or babysitting an agent that lost the thread halfway through. With this much context and adaptive reasoning, more of that fits in one call. Teams already running GPT-5.1 agents get a straightforward upgrade path rather than a rebuild.
Follows GPT-5.1-Codex-Max. Superseded by GPT-5.2 Pro. 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 | $1.75 | per 1M tokens | 2026-09-24 | Check |
| Output | $14.00 | per 1M tokens | 2026-09-24 | Check |
GPT-5.2 is priced as a frontier model, with output costing several times more than input, which is the usual shape for reasoning-heavy models. It is not the model to point at every request in a high-volume pipeline, so route the simple traffic to something smaller and save this one for work where the long context and tool use actually earn the cost.
| Workload | Input / month | Output / month | Cost |
|---|---|---|---|
| A small product team | 20M tokens | 5M tokens | $105.00 |
| A busy support assistant | 200M tokens | 40M tokens | $910.00 |
| A document pipeline | 1000M tokens | 100M tokens | $3,150.00 |
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 | 400,000 tokens |
|---|---|
| Maximum output | 128,000 tokens |
| Modalities | file, image, text |
| Released | 10/12/2025 |
| Status | Current |
| Catalogue identifier | openai/gpt-5.2 |
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-5.1-Codex-MaxCame after
GPT-5.2 Pro →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
A larger context window means the answer engine can read more of your site before it decides what you do, so thin or fragmented pages get less benefit of the doubt than they did. Depth and internal consistency across your documentation, pricing and comparison pages matter more, because the model can hold all of it at once and notice where the story does not line up. If your product only makes sense when a human reads three pages in order, write the page that says it once.
Buyers meet GPT-5.2 mostly through ChatGPT, where OpenAI's newest frontier model is what the assistant reaches for on harder requests. Developers meet it directly through the OpenAI API, and indirectly through the many SaaS products and AI search tools that build on OpenAI models rather than their own.
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.