Gemini 3 vs ChatGPT 5.1: Google’s Shocking Leap Beyond OpenAI’s Best Model
Claude McKenzie
Last Updated 2025-11-20
Google’s new Gemini 3 Pro is such a massive leap forward that it feels like skipping an entire generation — as if it jumped straight past 2.5 Pro and landed somewhere near GPT‑5.1 (no joke).
In nearly every benchmark, the model now outperforms GPT‑5.1 e Claude 4.5, acing even the toughest AGI‑oriented tests like ARC‑AGI‑2 e il “final human exams.” Sul AIME 2025 math benchmark, it scored a perfect 100 with tools enabled, and it even broke the infamous LiveCodeBench Pro record — a test that had previously stumped every other major model.
In user‑voted AI arena rankings, the story’s the same. Elon Musk’s Grok 4.1 topped the charts just yesterday — and today, Gemini 3 Pro has already overtaken it.
Even Sam Altman e Musk couldn’t help giving it a nod of respect, both publicly liking and congratulating Google’s team.
From Simulating OS Interfaces to Building Real Software
During internal testing, Gemini 3 was seen simulating full Windows, macOS, e Linux interfaces. At first, people thought it was just a front‑end design demo — but it turned out the programs it created actually worked.
In one demo, it built a complete LEGO editor from scratch on the first try — designing the interface, the spatial logic system, and all core editing functions in one go.
And that was just the start.
In another showcase, Google used Gemini 3 Pro to design a playable game from scratch — and released it on YouTube. The AI had essentially built a mini‑version of “Small Game Hub” all by itself.
Smarter Agents, Real‑World Results
Gemini 3 Pro isn’t just a coding powerhouse — it’s also far better at long‑term planning and real‑world task simulation.
In one test, it simulated managing a vending machine business for an entire year, turning a $5,000 profit — the highest among all tested models.
From top to bottom: Gemini 3 Pro, Claude Sonnet 4.5, GPT-5.1, Gemini 2.5 Pro.
Launching at Full Company Scale
Starting today, Google announced it is releasing the entire Gemini 3 series “at company scale.” On day one, Gemini was:
Fully integrated into Ricerca su Google,
Given a standalone applicazione mobile, e
Accompanied by a new AI agent development platform.
And that’s not all — a more powerful Gemini 3 “Deep Think” mode is already on the way.
As for how such a huge capability jump was achieved, Google’s VP of Research Oriol Vinyals revealed only one clue:
“Pretraining isn’t finished yet — and post‑training still has plenty of room for improvement.”
The Evolution of Gemini: From Foundation to Fusion
Looking back, the Gemini series feels like a game character leveling up — each generation fixing the last one’s weaknesses, then polishing everything again for the next.
Gemini 1 laid the foundation — connecting multimodal understanding and ultra‑long context. It became the first model capable of handling million‑token contexts.
Gemini 2 gained agency — after mastering massive information retention, it began synthesizing and planning across that knowledge, laying the groundwork for true AI agent behavior.
Gemini 2.5 focused on reasoning — Google added a “thinking engine,” enabling deeper logical analysis, chain‑of‑thought reasoning, and human‑like step‑by‑step problem solving.
Gemini 3 is the culmination — not just raw scaling, but deep integration across modalities, reasoning, and agentic capabilities. Its motto could be: “You imagine it. I make it real.”
Most notably, Gemini 3 finally feels human‑aware — it “gets” what you mean, not just what you type.
You no longer need to stress over writing the perfect prompt. Just throw in your messy request, and it will grasp your intent, read the context, and reply with a clean, straightforward answer — no unnecessary fluff.
Multimodal Capabilities on Overdrive
Gemini 3’s multimodal understanding is on another level. It can now seamlessly process text, images, video, audio, and code all together.
For example, feed it a full sports match video, and it can summarize the strategy, analyze player techniques, and even teach you how to replicate their moves.
It’s not hard to imagine a near future where you could upload your own training footage — and Gemini 3 becomes your personal coach.
In search scenarios, it also goes beyond simply dumping links. Instead, it organizes real‑time information into interactive, usable content that directly answers your question.
Antigravity: Google’s New Agent‑First Development Platform
“Free developers from repetitive coding tasks and empower them to act as high‑level architects.”
During Google’s demo, Antigravity built a flight‑tracking app in under one minute.
Unlike AI IDEs such as Cursor, Antigravity elevates the AI agent to a standalone environment with full access to the editor, terminal, e browser. Agents can autonomously plan, code, test, and verify end‑to‑end software — all on behalf of the user.
A new Manager View lets users orchestrate multiple agents at once, each working semi‑autonomously.
Google’s ambition here is clear: this is not just a tool — it’s a new generation of AI‑driven software engineering.
Open Ecosystem and Developer Rush
Antigravity supports not only Gemini models but also third‑party ones like GPT-OSS e Claude.
It’s currently in public preview e free to use, with “generous rate limits” for Gemini 3 Pro. Unsurprisingly, developers rushed in to “farm” free usage the moment it launched.
For context, Claude Code already makes up about 21% of Anthropic’s total revenue, and OpenAI continues to expand around Codex‑based products.
It’s no surprise that AI coding tools are shaping up to be the next big battlefield.
Bottom line
Gemini 3 Pro represents a watershed moment — a model that doesn’t just think better, ma acts smarter. Combined with Antigravity, Google is clearly signaling its intent to lead not only the multimodal race but also the age of intelligent agents.
