University of Kwazulu-Natal

Gpt 5 2 Codex Vs Gemini 3 Pro Vs Claude 4 5 Ai Coding Model Comparison

Bonisiwe Shabane
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gpt 5 2 codex vs gemini 3 pro vs claude 4 5 ai coding model comparison

The Shifting Landscape: GPT-5.2’s Rise in Developer Usage December 2025 marks a pivotal moment in the AI coding assistant wars. Introduction: Navigating the AI Coding Model Landscape December 2025 brought an unprecedented wave of AI model releases that left developers Nvidia Makes Its Largest Acquisition Ever with Groq Purchase In a landmark move that reshapes the artificial intelligence chip landscape, Is your Apple Watch’s constant stream of notifications and daily charging routine dimming its appeal? As we look towards Elevate your summer look with 7 AI diamond rings that deliver 24/7 health tracking, heart rate, and sleep insights while matching your style.

Three flagship AI coding models launched within weeks of each other. Claude Opus 4.5 on November 24. Gemini 3.0 Pro on November 18. GPT 5.1 Codex-Max on November 19. All three claim to be the best model for complex coding tasks and agentic workflows. The benchmarks show they're neck-and-neck.

I wanted to see what that means for actual development work. So I gave all three the same prompts for two complex problems in my observability platform: statistical anomaly detection and distributed alert deduplication: same codebase, exact requirements, same IDE setup. Here. I compared all these models on some projects I was working on in my spare time. I've used the Tool router, which is beta, in the first test, which also helps in dogfood the product. Do check out if you're someone who wants to use tools with your agents but doesn't want to be bothered with context pollution.

Read more on the tool router here. SWE-bench Verified: Opus 4.5 leads at 80.9%, followed by GPT 5.1 Codex-Max at 77.9% and Gemini 3 Pro at 76.2% Terminal-Bench 2.0: Gemini 3 Pro tops at 54.2%, demonstrating exceptional tool use capabilities With GPT-5.2 now available, developers now have a tough decision to make between it, Claude Opus 4.5, and Gemini 3.0 Pro. Each model is pushing the limits of coding. And since these releases came so close together, many in the industry are calling this the most competitive period in commercial AI to date.

Recent benchmarks show Opus 4.5 leading on SWE-Bench Verified with a score of 80.9%, but GPT-5.2 claims to challenge it. But will it? Let’s find out in this detailed GPT-5.2 vs. Claude Opus 4.5 vs. Gemini 3.0 coding comparison. Let’s start with GPT-5.2.

OpenAI launched it recently, right after a frantic internal push to counter Google’s momentum. This model shines in blending speed with smarts, especially for workflows that span multiple files or tools. It feels like having a senior dev who anticipates your next move. For instance, when you feed it a messy repo, GPT-5.2 doesn’t just patch bugs; it suggests refactors that align with your project’s architecture. That’s thanks to its 400,000-token context window, which lets it juggle hundreds of documents without dropping the ball. And in everyday coding?

It cuts output tokens by 22% compared to GPT-5.1, meaning quicker iterations without the bill shock. But what makes it tick for coders? The Thinking mode ramps up reasoning for thorny problems, like optimizing a neural net or integrating APIs that fight back. Early testers at places like Augment Code rave about its code review agent, which spots subtle edge cases humans might gloss over. It’s not flawless, though. On simpler tasks, like whipping up a quick script, it can overthink and spit out verbose explanations you didn’t ask for.

Still, for production-grade stuff, where reliability trumps flash, GPT-5.2 feels like a trusty pair of noise-canceling headphones in a noisy office. It builds on OpenAI’s agentic focus, turning vague prompts into deployable features with minimal hand-holding. Each model brings distinct strengths to the table. GPT-5.2 Thinking scored 80% on SWE-bench Verified, essentially matching Opus 4.5’s performance after OpenAI declared an internal code red following Gemini 3’s strong showing. Gemini 3 Pro scored 76.2% on SWE-bench Verified, still an impressive result that represents a massive jump from its predecessor. These scores matter because SWE-bench Verified tests something beyond simple code generation: the ability to understand real GitHub issues, navigate complex codebases, implement fixes, and ensure no existing functionality breaks in the process.

A demo showcasing Claude Opus 4.5’s advanced coding capabilities: For a few weeks now, the tech community has been amazed by all these new AI models coming out every few days. 🥴 But the catch is, there are so many of them right now that we devs aren't really sure which AI model to use when it comes to working with code, especially as your daily... Just a few weeks ago, Anthropic released Opus 4.5, Google released Gemini 3, and OpenAI released GPT-5.2 (Codex), all of which claim at some point to be the "so-called" best for coding. But now the question arises: how much better or worse is each of them when compared to real-world scenarios?

If you want a quick take, here is how the three models performed in these tests: In 2025, the tech world is buzzing with comparisons between the leading AI models: GPT-5.2, Gemini 3.0, and Claude Opus 4.5. Each model shines in different aspects of coding and benchmark performance, but none takes the crown in every domain. Claude Opus 4.5 stands out in long autonomous coding, while GPT-5.2 is praised for real-world reliability, and Gemini 3.0 excels at speed in multimodal tasks. This article delves into their strengths, weaknesses, and what developers can expect in terms of coding improvements and innovations. ChatGPT 5.2, Claude Opus 4.5, and Gemini 3 represent the highest tier of capability within their respective ecosystems.

These are not speed-first assistants or lightweight productivity tools. They are flagship reasoning systems, designed for complex analysis, long-context synthesis, and professional decision support. This comparison examines how each model defines intelligence at the top end, and why their differences matter in real-world use. ChatGPT 5.2 is built to operate across a wide spectrum of tasks without forcing users to choose between modes or mental models. This software hasn't been reviewed yet. Be the first to provide a review:

AILLMEngineeringComparisonBenchmarkCursor Last month, I conducted a deep dive into AI frontend generators—vibe coding tools like v0 and Lovable. Since then, the landscape of AI-assisted software development has shifted again. With the release of Claude Opus 4.5 and the hype surrounding "engineering-grade" models, I wanted to move beyond frontend generation and test their capabilities as full-stack engineers. I took the three current heavyweights—GPT-5.1-Codex-Max, Gemini 3 Pro, and Claude Opus 4.5—and ran them through a rigorous MVP development cycle. Anthropic claims that "Claude Opus 4.5 is state-of-the-art on tests of real-world software engineering," citing a 74.4% score on SWE-bench.

Gemini 3 Pro is nipping at its heels at 74.2%. But do benchmark numbers translate to shipping products? Let's put it to the test. November 2025 was the most intense month in AI history: three tech giants released their flagship models within just six days of each other. We break down the benchmarks, pricing, and real-world performance to help you choose the right model for your needs. In an unprecedented week, all three major AI labs released their flagship models, creating the most competitive AI landscape we've ever seen:

Here's how the three models stack up on the most important benchmarks for developers and enterprises: Measures ability to solve actual GitHub issues from real software projects Tests advanced academic knowledge across physics, chemistry, and biology

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