openai

GPT-5.2 Pro

GPT-5.2 Pro is OpenAI's 2025 flagship reasoning model featuring Extended Thinking for SOTA performance in mathematics, coding, and expert knowledge work.

openai logoopenaiGPT-52025-12-11
Context
400Ktokens
Max Output
128Ktokens
Input Price
$21.00/ 1M
Output Price
$168.00/ 1M
Modality:TextImage
Capabilities:VisionToolsStreamingReasoning
Benchmarks
GPQA
93.2%
GPQA: Graduate-Level Science Q&A. A rigorous benchmark with 448 multiple-choice questions in biology, physics, and chemistry created by domain experts. PhD experts only achieve 65-74% accuracy, while non-experts score just 34% even with unlimited web access (hence 'Google-proof'). GPT-5.2 Pro scored 93.2% on this benchmark.
HLE
36.6%
HLE: High-Level Expertise Reasoning. Tests a model's ability to demonstrate expert-level reasoning across specialized domains. Evaluates deep understanding of complex topics that require professional-level knowledge. GPT-5.2 Pro scored 36.6% on this benchmark.
MMLU
90%
MMLU: Massive Multitask Language Understanding. A comprehensive benchmark with 16,000 multiple-choice questions across 57 academic subjects including math, philosophy, law, and medicine. Tests broad knowledge and reasoning capabilities. GPT-5.2 Pro scored 90% on this benchmark.
MMLU Pro
83%
MMLU Pro: MMLU Professional Edition. An enhanced version of MMLU with 12,032 questions using a harder 10-option multiple choice format. Covers Math, Physics, Chemistry, Law, Engineering, Economics, Health, Psychology, Business, Biology, Philosophy, and Computer Science. GPT-5.2 Pro scored 83% on this benchmark.
SimpleQA
45%
SimpleQA: Factual Accuracy Benchmark. Tests a model's ability to provide accurate, factual responses to straightforward questions. Measures reliability and reduces hallucinations in knowledge retrieval tasks. GPT-5.2 Pro scored 45% on this benchmark.
IFEval
88%
IFEval: Instruction Following Evaluation. Measures how well a model follows specific instructions and constraints. Tests the ability to adhere to formatting rules, length limits, and other explicit requirements. GPT-5.2 Pro scored 88% on this benchmark.
AIME 2025
100%
AIME 2025: American Invitational Math Exam. Competition-level mathematics problems from the prestigious AIME exam designed for talented high school students. Tests advanced mathematical problem-solving requiring abstract reasoning, not just pattern matching. GPT-5.2 Pro scored 100% on this benchmark.
MATH
100%
MATH: Mathematical Problem Solving. A comprehensive math benchmark testing problem-solving across algebra, geometry, calculus, and other mathematical domains. Requires multi-step reasoning and formal mathematical knowledge. GPT-5.2 Pro scored 100% on this benchmark.
GSM8k
98%
GSM8k: Grade School Math 8K. 8,500 grade school-level math word problems requiring multi-step reasoning. Tests basic arithmetic and logical thinking through real-world scenarios like shopping or time calculations. GPT-5.2 Pro scored 98% on this benchmark.
MGSM
92%
MGSM: Multilingual Grade School Math. The GSM8k benchmark translated into 10 languages including Spanish, French, German, Russian, Chinese, and Japanese. Tests mathematical reasoning across different languages. GPT-5.2 Pro scored 92% on this benchmark.
MathVista
70%
MathVista: Mathematical Visual Reasoning. Tests the ability to solve math problems that involve visual elements like charts, graphs, geometry diagrams, and scientific figures. Combines visual understanding with mathematical reasoning. GPT-5.2 Pro scored 70% on this benchmark.
SWE-Bench
84.5%
SWE-Bench: Software Engineering Benchmark. AI models attempt to resolve real GitHub issues in open-source Python projects with human verification. Tests practical software engineering skills on production codebases. Top models went from 4.4% in 2023 to over 70% in 2024. GPT-5.2 Pro scored 84.5% on this benchmark.
HumanEval
95%
HumanEval: Python Programming Problems. 164 hand-written programming problems where models must generate correct Python function implementations. Each solution is verified against unit tests. Top models now achieve 90%+ accuracy. GPT-5.2 Pro scored 95% on this benchmark.
LiveCodeBench
76%
LiveCodeBench: Live Coding Benchmark. Tests coding abilities on continuously updated, real-world programming challenges. Unlike static benchmarks, uses fresh problems to prevent data contamination and measure true coding skills. GPT-5.2 Pro scored 76% on this benchmark.
MMMU
82%
MMMU: Multimodal Understanding. Massive Multi-discipline Multimodal Understanding benchmark testing vision-language models on college-level problems across 30 subjects requiring both image understanding and expert knowledge. GPT-5.2 Pro scored 82% on this benchmark.
MMMU Pro
86.7%
MMMU Pro: MMMU Professional Edition. Enhanced version of MMMU with more challenging questions and stricter evaluation. Tests advanced multimodal reasoning at professional and expert levels. GPT-5.2 Pro scored 86.7% on this benchmark.
ChartQA
90%
ChartQA: Chart Question Answering. Tests the ability to understand and reason about information presented in charts and graphs. Requires extracting data, comparing values, and performing calculations from visual data representations. GPT-5.2 Pro scored 90% on this benchmark.
DocVQA
94%
DocVQA: Document Visual Q&A. Document Visual Question Answering benchmark testing the ability to extract and reason about information from document images including forms, reports, and scanned text. GPT-5.2 Pro scored 94% on this benchmark.
Terminal-Bench
46.8%
Terminal-Bench: Terminal/CLI Tasks. Tests the ability to perform command-line operations, write shell scripts, and navigate terminal environments. Measures practical system administration and development workflow skills. GPT-5.2 Pro scored 46.8% on this benchmark.
ARC-AGI
54.2%
ARC-AGI: Abstraction & Reasoning. Abstraction and Reasoning Corpus for AGI - tests fluid intelligence through novel pattern recognition puzzles. Each task requires discovering the underlying rule from examples, measuring general reasoning ability rather than memorization. GPT-5.2 Pro scored 54.2% on this benchmark.

About GPT-5.2 Pro

Learn about GPT-5.2 Pro's capabilities, features, and how it can help you achieve better results.

A New Standard in Reasoned Intelligence

GPT-5.2 Pro represents the high-compute tier of OpenAI's reasoning-focused models. It is specifically engineered for enterprise workflows that require PhD-level scientific research and complex logical inference. Unlike standard language models, it utilizes a sophisticated inference-time compute architecture that allows users to scale the model's thinking effort. This enables the system to internally decompose problems, verify its own logic, and override statistical priors that often lead to errors in smaller models.

Specialized for Technical Precision

While sharing core training with the broader GPT-5 family, the Pro variant is distinguished by its massive 400,000 token context window and significantly lower hallucination rates. It has been documented as a reliable collaborator in theoretical physics and high-stakes mathematical proofs. Its performance on contamination-resistant benchmarks like ARC-AGI-2 and GPQA Diamond establishes it as a primary process engine for autonomous agents that must handle multi-step, technical instructions without human intervention.

Enterprise Performance and Output

The model is characterized by its strict adherence to complex instructions and professional conversational tone. It is the first model to consistently outperform human industry experts with over 14 years of experience on specialized work task benchmarks. With a generation capacity of up to 128,000 tokens, it marks a significant shift away from the laziness observed in previous generations, making it capable of producing entire code modules or exhaustive research reports in a single pass.

GPT-5.2 Pro

Use Cases

Discover the different ways you can use GPT-5.2 Pro to achieve great results.

Autonomous Software Engineering

Resolving complex, multi-file GitHub issues and executing full-module refactoring with an 84.5% success rate on SWE-Bench Verified.

Olympiad Mathematics

Solving 100% of AIME 2025 competition problems and contributing original proofs to open questions in statistical learning theory.

Enterprise Agent Orchestration

Functioning as a high-compute process engine that can sequence dozens of tools to handle multi-step financial modeling and logistics.

PhD-Level Science Research

Analyzing physics, chemistry, and biology problems with a 93.2% GPQA score, surpassing many human subject-matter experts.

Long-Context Document Synthesis

Ingesting up to 400,000 tokens of archival data to generate comprehensive legal reports or technical manuals.

Interactive 3D Simulation

Generating multi-thousand line 3D simulations in Three.js or C++, including complex particle physics and mechanical logic.

Strengths

Limitations

Perfect Mathematics Accuracy: Achieves a flawless 100% solve rate on the AIME 2025 benchmark, exhausting the signal in modern contest-level math exams.
Prohibitive Pricing: At $168 per million output tokens, the model is roughly 16x more expensive than GPT-5.1, limiting its use to high-stakes workflows.
State-of-the-Art Coding: Reaches an 84.5% solve rate on SWE-Bench Verified, effectively functioning as a junior engineer capable of owning non-trivial bug backlogs.
Missing Memory Features: Lacks support for Saved Memories and Reference Chat History, features that are standard in the lower-tier ChatGPT 5.2 models.
Advanced Abstract Reasoning: Triple the ARC-AGI-2 performance of its predecessor (54.2% vs 17.6%), indicating a breakthrough in handling novel rule-induction tasks.
Significant Latency: Deep internal reasoning can cause the model to spin for over 15 minutes on a single prompt, especially in xhigh effort mode.
Massive 128K Output Capacity: Designed to generate entire books, code repositories, or exhaustive scientific reports in a single inference pass.
Frame Selection Errors: Occasional failure to override statistical priors in common-sense tasks, even when correctly identifying logical constraints in thought traces.

API Quick Start

openai/gpt-5.2-pro

View Documentation
openai SDK
import OpenAI from 'openai';

const openai = new OpenAI();

async function main() {
  const completion = await openai.chat.completions.create({
    model: 'gpt-5.2-pro',
    messages: [{ role: 'user', content: 'Design a leveraged buyout model for a take-private project.' }],
    reasoning_effort: 'xhigh',
    stream: true,
  });

  for await (const chunk of completion) {
    process.stdout.write(chunk.choices[0]?.delta?.content || '');
  }
}

main();

Install the SDK and start making API calls in minutes.

Community Feedback

See what the community thinks about GPT-5.2 Pro

The reasoning was present; the conclusion simply didn’t follow. If that doesn’t make you pause, it should.
Ok_Entrance_4380
reddit
GPT-5.2 Pro derived a new result in theoretical physics that survived expert scrutiny, something 5.1 couldn't do.
kevinweil
twitter
GPT-5.2 Pro is beginning to look like a junior engineer that can own a non-trivial slice of the issue tracker.
Due_Woodpecker2882
reddit
OpenAI admits the Pro model lacks memory. It's devastating for me as an academic.
Oldschool728603
hackernews
The logic is flawless but the latency makes it feel like I'm collaborating with a very slow genius.
User123
reddit
Finally, a model that doesn't hallucinate its way through a simple tensor contraction.
PhysicsProf
hackernews

Related Videos

Watch tutorials, reviews, and discussions about GPT-5.2 Pro

rumored Mensa Norway IQ scores between 145 and 147

produced over 24,000 lines of code

inclusion of a selectable thinking time option

the Pro tier pricing is strictly for enterprise budgets

this model solved my entire dev backlog in one afternoon

30% reduction in hallucination

layout overall is shockingly good compared to where we were with 5.1

Exactly 300 words. This is the very first time I gave it a word count and it hit it to the exact number

The vision capabilities on architectural blueprints are unmatched

It feels significantly colder and more robotic than 5.1

$200 GPT5 Pro thought for 25 minutes and 36 seconds

assigning twice the inference compute

converted a complicated problem... into a different kind of machinery from a field called complex analysis

it's effectively a PhD in a box for $200 a month

the thinking trace shows it's actually verifying its own steps

More than just prompts

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Pro Tips

Expert tips to help you get the most out of GPT-5.2 Pro and achieve better results.

Scale Reasoning Effort

Use the reasoning_effort API parameter and set it to xhigh for tasks where logical consistency is more important than generation speed.

Address Statistical Priors

If the model falls into common-sense traps, provide a context nudge to activate its active reasoning layer and override its base training.

Utilize Massive Output

Request entire project directories or complete documentation files in one prompt to take advantage of the 128K output budget.

Leverage Tool Integration

Always enable function calling for vision tasks; the model's multimodal performance jumps when it can use tools to verify visual data.

Testimonials

What Our Users Say

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Mohammed Ibrahim

Mohammed Ibrahim

CEO, qannas.pro

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Ben Bressington

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Sarah Chen

Head of Growth, ScaleUp Labs

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David Park

Founder, DataDriven.io

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Frequently Asked Questions

Find answers to common questions about GPT-5.2 Pro