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OpenAI model°

GPT-5.1

GPT-5.1 is OpenAI's frontier general-purpose model, the current head of the GPT-5 series, built for reasoning, instruction adherence and a more natural conversational register than GPT-5.

OpenAIVerified 24/09/2026Released 13/11/2025

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 126 models we track, not against an absolute standard.

Capability

Not measured

No published benchmark scores yet

Input / 1M tokens

$1.25

field median $0.30

Output / 1M tokens

$10.00

field median $1.25

Context

400K

field median 524K

02 / overview

What GPT-5.1 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-5.1 is a general-purpose frontier model rather than a specialist one, intended to handle reasoning, long-document work and everyday conversation from the same endpoint. OpenAI describes it as using adaptive reasoning, so it varies how much thinking it applies to a request instead of treating every prompt the same way. It is not a cheap high-volume classifier and it is not an audio or video model, it takes text, images and files in and returns text.

When it arrived, and when to use it

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

GPT-5.1 was first seen in November 2025 as the latest entry in the GPT-5 series, sitting above GPT-5 on general reasoning, instruction following and conversational quality. It is the right pick when a task needs careful reasoning over a large body of material, or when tone and instruction adherence matter because the output goes in front of a customer. It is the wrong pick for simple, repetitive, high-volume calls where a smaller sibling does the same job for a fraction of the spend.

How you reach it

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

GPT-5.1 is reached through the OpenAI API and powers ChatGPT, so the same model sits behind both a developer integration and a consumer chat product. The context window is large enough to hold a full documentation set, a long contract bundle or a codebase excerpt in a single request, and the output ceiling is high enough to return a complete long-form document rather than a fragment. Image and file input mean you can pass screenshots, scanned pages and uploaded documents alongside the prompt instead of pre-extracting the text.

Why it matters

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

The combination of a very large input window and a very large output allowance removes a lot of chunking and stitching work that used to sit around the model. Adaptive reasoning means one endpoint can serve both a quick reply and a long analytical task without the team routing between two models. Otherwise this is an incremental step on GPT-5 rather than a change in what is possible.

Follows GPT-5 Pro. Superseded by GPT-5.1-Codex. 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-5.1 API pricingSurge45°
ChargePriceUnitRead onSource
Input$1.25per 1M tokens2026-09-24Check
Output$10.00per 1M tokens2026-09-24Check

Input is cheap enough that filling the context window with supporting documents is a reasonable habit rather than a cost decision, while output costs several times more, so the expensive requests are the ones that generate long documents rather than the ones that read them. That puts it in the usual frontier bracket, well above small fast models but not at the premium end of the market.

What a month costsSurge45°
WorkloadInput / monthOutput / monthCost
A small product team20M tokens5M tokens$75.00
A busy support assistant200M tokens40M tokens$650.00
A document pipeline1000M tokens100M tokens$2,250.00

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 window400,000 tokens
Maximum output128,000 tokens
Modalitiesimage, text, file
Released13/11/2025
StatusCurrent
Catalogue identifieropenai/gpt-5.1

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 Pro

Came after

GPT-5.1-Codex →
  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-6 Astra04/09/2026
  14. 14GPT-6 Astra Pro04/09/2026
  15. 15GPT-6 Luna22/09/2026
  16. 16GPT-6 Luna Pro22/09/2026
  17. 17GPT-6 Sol22/09/2026
  18. 18GPT-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

A model with this much context can read a long page in full, so depth is no longer penalised the way it was with tighter windows, a thorough comparison page or documentation set can be taken in whole. Stronger instruction adherence also means the model follows the shape of a user's question closely, so the brands cited are the ones whose material answers that exact question rather than the ones with the most general authority. If your pricing, integrations and use cases are only clear to a human reading the page in order, they are unlikely to survive the summary.

Where buyers meet this model

Most buyers meet GPT-5.1 inside ChatGPT, where it answers questions about categories, shortlists and vendors in conversation rather than in a list of links. Developers meet it through the OpenAI API, and it also sits behind products built on that API, so a buyer can be reading GPT-5.1 output without knowing which model produced it.

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.

How is GPT-5.1 different from GPT-5?
OpenAI positions GPT-5.1 as the stronger of the two on general reasoning and instruction adherence, with a more natural conversational style. It also uses adaptive reasoning, varying the effort it spends depending on the request.
What can GPT-5.1 take as input?
Text, images and files. That means you can pass screenshots, scanned pages and uploaded documents directly alongside your prompt instead of extracting the text first.
When should I use something smaller instead?
For high-volume, repetitive tasks such as classification, tagging or short routine replies, where a smaller model in the family gives you the same result at a much lower cost per call.
Does GPT-5.1 affect how my SaaS brand appears in AI answers?
Yes, it is the model behind ChatGPT answers, so how it reads and summarises your pages determines whether you are cited. Its large context window means long, detailed pages can be read in full rather than truncated.
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Is GPT-5.1 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.

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