openai

OpenAI: GPT-5.2

openai/gpt-5.2

Our take

AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.

OpenRouter lists openai/gpt-5.2 as an OpenAI GPT-5-series model exposed through the canonical variant openai/gpt-5.2-20251211. The catalog describes text output with text, image and file inputs, a 400,000-token context window, tool calling, structured outputs, seed, response formatting and verbosity controls. Reasoning is optional with adjustable effort, including none. OpenRouter's description claims stronger agentic and long-context performance than GPT-5.1, but that is source-reported rather than independently validated here; the only evidence is the catalog listing.[1]

Strengths

Catalog-reported multimodal input: accepts text, image and file inputs while emitting text.[1]
Advertised 400,000-token context window may suit long documents or extended agent traces.[1]
Optional tunable reasoning plus tools and structured outputs suggests workflow and agent integration.[1]

Limitations

Evidence is catalog-only; an independent model card was not available in this source pack.[1]
No measured accuracy, latency, safety, license or hardware data is supplied, so workload validation is needed.[1]
Arena benchmark entries appear in the catalog, but they are contextual signals rather than a capability guarantee.[1]

Where to use it

Pilot for long-context document or agentic coding workflows where multimodal inputs and tools matter.[1]
Try when configurable reasoning effort should be lowered or disabled for faster calls.[1]
Do not treat as proven for regulated or safety-critical tasks until separately evaluated.[1]

Sources

[1] OpenRouter catalog · OpenAI: GPT-5.2Sources checked: Nov 13, 2026

About this model

Description below is the original text supplied by OpenRouter, shown in the source language.

GPT-5.2 is the latest frontier-grade model in the GPT-5 series, offering stronger agentic and long context perfomance compared to GPT-5.1. It uses adaptive reasoning to allocate computation dynamically, responding quickly...

Specifications

Model ID: openai/gpt-5.2
Canonical ID: openai/gpt-5.2-20251211
Creator: openai
Added to OpenRouter: 10.12.2025
Context length: 400,000
Modality: text+image+file->text
Input modalities: file, image, text
Output modalities: text
Token pricing: USD per 1M tokens: in $1.75 / out $14
Knowledge cutoff: —
Expiration date: —

Tasks and capabilities

A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.

Task	Grade	Source-declared capability
General quality	No measurement	reasoning: optional · default medium · efforts: xhigh, high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort
Coding	No measurement	—
Agents	No measurement	parameters: structured_outputs, tool_choice, tools
Writing	No measurement	output: text
Reasoning	No measurement	reasoning: optional · default medium · efforts: xhigh, high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort
Document analysis	No measurement	input: file
Vision	No measurement	input: image
Image generation	No measurement	—
Audio	No measurement	—
Video	No measurement	—
Embeddings	No measurement	—

Evaluations

Source	Benchmark	Value	Grade	Data retrieved
Design Arena	models · websitewin rate 54.4% · rank 69	1,187Elo	BB — next 30% of the cohort	13.11.2026
Design Arena	agents · androidnativewin rate 49.1% · rank 38	1,045Elo	CC — below the B band	13.11.2026
Design Arena	agents · fullstackwin rate 44.3% · rank 39	1,020Elo	CC — below the B band	13.11.2026
Design Arena	agents · godotgamedevwin rate 48.1% · rank 22	1,142Elo	BB — next 30% of the cohort	13.11.2026
Design Arena	agents · mobileappswin rate 46.8% · rank 43	1,088Elo	CC — below the B band	13.11.2026
Design Arena	agents · webappswin rate 45.5% · rank 41	1,068Elo	CC — below the B band	13.11.2026
Design Arena	models · 3dwin rate 41.5% · rank 106	1,062Elo	CC — below the B band	13.11.2026
Design Arena	models · codecategorieswin rate 49.6% · rank 80	1,160Elo	CC — below the B band	13.11.2026
Design Arena	models · datavizwin rate 56.1% · rank 59	1,202Elo	BB — next 30% of the cohort	13.11.2026
Design Arena	models · gamedevwin rate 56% · rank 63	1,185Elo	BB — next 30% of the cohort	13.11.2026
Design Arena	models · uicomponentwin rate 51.3% · rank 70	1,181Elo	BB — next 30% of the cohort	13.11.2026
Design Arena	models · asciiartwin rate 50.7% · rank 45	1,147Elo	CC — below the B band	13.11.2026
Design Arena	models · svgwin rate 53.7% · rank 59	1,129Elo	CC — below the B band	13.11.2026

How grades work

Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.

S — S — top 10% of the cohort
A — A — next 20% of the cohort
B — B — next 30% of the cohort
C — C — below the B band

Providers

Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.

Provider	Context length	Price in /1M	Price out /1M	Latency p50 (30m, s)	Throughput p50 (30m, tok/s)	Uptime (30m)
OpenAI	400,000	$0.875	$7	—	—	—
Azure	400,000	$1.75	$14	—	—	100%
OpenAI	400,000	$1.75	$14	—	—	100%
OpenAI	400,000	$3.5	$28	—	—	100%

Provider data retrieved: 13.11.2026

No published articles identify this model yet.