GPT-5.2
GPT-5.2 is OpenAI's flagship model for professional tasks, featuring a 400K context window, elite coding, and deep multi-step reasoning capabilities.
openaiGPT-5December 11, 2025About GPT-5.2
Learn about GPT-5.2's capabilities, features, and how it can help you achieve better results.
GPT-5.2 is OpenAI’s flagship reasoning model designed for high-stakes professional knowledge work and autonomous engineering. Released on December 11, 2025, it marks a significant evolution from the GPT-4 and GPT-o1 series by integrating a dedicated Thinking mode with effort controls (Medium, High, Extra High). This allows the model to pause and verify multi-step logic before generating a response.
With a massive 400K context window and nearly 100% recall, it is engineered for senior-level code reviews, complex refactoring, and scientific research. The model architecture is built to support agentic workflows, featuring native tool-calling and multimodal vision that can process intricate technical diagrams and codebases simultaneously.
While it excels in logical precision and engineering benchmarks, hitting a 100% score on AIME 2025, it adopts a more formal, machine-like tone compared to competitors like Claude. It is currently priced at $1.75 per million input tokens and $14.00 per million output tokens, making it a cost-effective alternative for deep reasoning tasks that previously required high-compute human oversight.
Use Cases
Discover the different ways you can use GPT-5.2 to achieve great results.
Complex Engineering Refactors
Performing deep refactoring on performance-critical codebases while maintaining strict type invariants and architectural consistency.
Autonomous Terminal Tasks
Executing multi-step CLI workflows and managing complex cloud deployments through high performance on Terminal-Bench environments.
PhD-Level Knowledge Synthesis
Analyzing hundreds of technical sources and academic papers simultaneously to create comprehensive research reports on niche scientific topics.
Concurrency Bug Resolution
Identifying and fixing subtle race conditions or memory leaks that require high-level logical inference over long code segments.
Mechanical Code Processing
Handling large-scale, repetitive coding migrations across entire repositories without the laziness often observed in general-purpose LLMs.
Senior Technical Review
Acting as a virtual senior engineer to review design plans and identify edge cases in logic for production systems.
Strengths
Limitations
API Quick Start
openai/gpt-5.2
import OpenAI from 'openai';
const openai = new OpenAI();
async function solveCodeProblem() {
const response = await openai.chat.completions.create({
model: 'gpt-5.2',
messages: [{ role: 'user', content: 'Debug this race condition in my Rust service.' }],
reasoning_effort: 'high',
temperature: 0,
});
console.log(response.choices[0].message.content);
}
solveCodeProblem();Install the SDK and start making API calls in minutes.
Community Feedback
See what the community thinks about GPT-5.2
“GPT 5.2 in Codex is a very huge improvement, it's more willing to handle those mechanical tasks that would normally make models lazy.”
“The increased deliberation and time spent fact-checking its output is to be commended... the reliability is much improved.”
“The model powering deep research showcased a human-like approach by effectively seeking out specialized information when necessary.”
“OpenAI's focus on structured 'user care' feels like a corporate mask for a cold core compared to the natural discussions in Claude.”
“Finally a model that doesn't get lazy halfway through a 500-line refactor.”
“The reasoning effort parameter is the real MVP for complex logic problems.”
Related Videos
Watch tutorials, reviews, and discussions about GPT-5.2
“This is actually insane. Look at this one shot.”
“The design I'm not super impressed with with GPT 5.2... it did much worse than Gemini 3.”
“The context recall is nearly perfect across the whole 400k range.”
“It feels much more like a reasoning engine than a chatbot.”
“The latency is the only real dealbreaker for some real-time apps.”
“GPT 5.2 can now create fully formatted spreadsheets and slide decks directly inside chat GPT.”
“It's like the model finally grew up and started taking its job seriously.”
“Use the high reasoning setting only for logic-heavy tasks.”
“The hallucinations are down significantly compared to the 4o series.”
“Agentic workflows are finally viable without constant babysitting.”
“GPT 5.2 is actually 40% more expensive than 5.1, but it's still significantly cheaper than Opus.”
“GPT 5.2 took 11 minutes and 20 seconds [to build the app]. So double the amount of time [compared to Opus].”
“The output quality is much higher when you allow the thinking mode to run.”
“It handled the multi-file refactor without losing the type definitions.”
“If you need raw speed, this isn't the model for you.”
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Pro Tips
Expert tips to help you get the most out of GPT-5.2 and achieve better results.
Leverage Thinking Effort
Use the reasoning_effort parameter (medium, high, xhigh) to match the model's deliberation time to the complexity of the task.
Enable Codex for Persistence
When working on large repos, use the dedicated Codex environment to maintain active processing sessions for up to 150 minutes.
Spoon-feed Context
Provide rich background documentation in system prompts as the model performs best when interviewed about the context it needs.
Iterate on Requirements
Explicitly instruct the model to perform verification checks against the current codebase to ensure requirements are validated.
Testimonials
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Frequently Asked Questions
Find answers to common questions about GPT-5.2