OpenAI has just unveiled GPT-5.2 Codex - the most advanced AI model for programming that can work on complex projects for hours without supervision. This technology is changing how companies approach software development and code automation. What does this mean for regular programmers, businesses, and the future of software engineering?
What is GPT-5.2 Codex and Why is it Exceptional?
Imagine a programming colleague who never sleeps, never forgets details, and can work on your project for seven hours straight without losing concentration. That's exactly what GPT-5.2 Codex is - a special version of the GPT-5.2 model trained specifically on real-world software tasks.
Unlike ordinary AI assistants that just advise you or generate code snippets, GPT-5.2 Codex functions as a full-fledged autonomous agent. It's a step toward what experts at Apertia.ai call "agentic AI" - artificial intelligence that doesn't just answer questions but actively solves complex tasks from start to finish.
Key Capabilities of GPT-5.2 Codex
The model can autonomously handle a full spectrum of developer tasks
- Building projects from scratch - creates complete applications according to your specifications
- Adding new features - extends existing code with requested functionality
- Intelligent debugging - finds and fixes bugs independently, including testing
- Extensive refactoring - rewrites and reorganizes large portions of code for better structure
- Code review - checks code quality and finds potential issues before deployment
- Technology migration - converts projects from one language or framework to another
Comparison with Competition: GPT-5.2 vs Claude Opus 4.5 vs Gemini 3 Pro
In November and December 2025, an unprecedented competitive battle occurred between three tech giants. OpenAI, Anthropic (Claude), and Google (Gemini) released their most advanced models within a few weeks. How does GPT-5.2 Codex perform in direct comparison?
Key Benchmark Comparison Table
| Benchmark | GPT-5.2 Codex | Claude Opus 4.5 | Gemini 3 Pro | What it Measures |
|---|---|---|---|---|
| SWE-Bench Verified | 80.0% | 80.9% | 76.2% | Fixing real GitHub bugs |
| SWE-Bench Pro | 55.6% | - | - | Complex coding across languages |
| Terminal-Bench 2.0 | 47.6% | 59.3% | 54.2% | Terminal and CLI work |
| GPQA Diamond | 92.4% | 87.0% | 91.9% | PhD-level scientific questions |
| ARC-AGI-2 | 52.9% | 37.6% | 31.1% | Abstract logical reasoning |
| AIME 2025 | 100% | 100% | 95% | Math competition |
| MMMU (Vision) | 84.2% | 77.8% | 83.0% | Multimodal understanding |
| Input price | $1.25/1M tokens | $5/1M tokens | ~$0.80/1M tokens | Operating costs |
| Output price | $10/1M tokens | $25/1M tokens | ~$8/1M tokens | Generation costs |
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Practical Differences from a Developer's Perspective
According to independent tests from developer communities:
- GPT-5.2 creates code that follows common conventions and is easily readable even for juniors. It integrates well into existing workflows and reliably completes complex tasks. Sometimes it may add extra validations or features you didn't request.
- Claude Opus 4.5 generates more sophisticated solutions with better architectural separation. It's like a senior architect who thinks ahead. Sometimes solutions can be unnecessarily complex for simple tasks. Excellent for planning large projects.
- Gemini 3 Pro produces the most concise code with emphasis on performance. Great for prototyping and rapid iterations. Sometimes may skip edge cases or advanced features like rate limiting. Ideal for experienced developers who appreciate a minimalist approach.
How Does GPT-5.2 Codex Perform in Practice?
Benchmark Results
On the SWE-Bench Pro benchmark, which tests the ability to solve real programming tasks from production repositories, GPT-5.2 Codex achieved a success rate of 55.6%. This means it can solve more than half of complex tasks across four different programming languages (Python, JavaScript, TypeScript, and Go).
For comparison - just a year ago, the success rate of top AI models on similar benchmarks was around 20-30%. GPT-5.2 Codex represents nearly a twofold improvement.
Adaptive Thinking
What's even more important than mere numbers - the model can work efficiently and adaptively. For simple requests, it responds quickly (using 93.7% fewer tokens than GPT-5), while for complex refactoring and architectural changes, it takes time to think things through properly.
During OpenAI's internal testing, GPT-5.2 Codex managed to work for more than 7 hours on a single complex task, testing its solution, fixing bugs, and iterating on the implementation until it achieved a functional result.
A Secret Weapon in Cybersecurity
One of the most interesting and sensitive uses of GPT-5.2 Codex is in cybersecurity. Modern AI models are becoming powerful tools for both defense and, unfortunately, potentially for attack as well.
Real Case: Discovering a Vulnerability in React
Just on December 11, 2025, security engineer Andrew MacPherson from Privy used a previous version of the model (GPT-5.1-Codex-Max) and discovered a previously unknown vulnerability in the popular JavaScript library React. This bug could have led to application source code leakage.
MacPherson responsibly reported the vulnerability and the React team immediately fixed it. This incident showed how powerful a tool AI models are becoming for security research.
Enhanced Threat Detection Capabilities
GPT-5.2 Codex is even more capable in cybersecurity. The model achieves significantly higher accuracy in professional Capture-the-Flag (CTF) competitions that simulate real cyberattacks and test vulnerability finding abilities.
This improved performance in CTF environments directly translates to practice:
- Faster identification of security flaws
- Better threat analysis
- Automated penetration testing
- Assistance with code security audits
Responsible Deployment
OpenAI is well aware of the dual-use nature of such powerful tools - they can be used for both good and evil. Therefore, the company is implementing several protective measures:
- Trusted Access Pilot Program - Only vetted security professionals with a history of responsible vulnerability disclosure get access to the most capable versions of the model for defensive use.
- Advanced monitoring - OpenAI has implemented dedicated monitoring systems specifically for cybersecurity that detect and block suspicious activities. The company has already successfully blocked several attempts to misuse models for cyber operations.
- Gradual deployment - The model is being released gradually with continuous learning from real-world use and improvement of protective measures.
