Gemini 3 Pro Vs Claude Sonnet 4 5 Antigravity Ide Review

Bonisiwe Shabane

-Jan 2, 2026, 6:06 AM

gemini 3 pro vs claude sonnet 4 5 antigravity ide review

Google launched Antigravity and Gemini 3 two days ago. I’ve spent the last 48 hours testing both—and comparing Gemini 3 Pro vs Claude Sonnet 4.5 in real-world coding tasks. If you’ve been following the AI coding tool space, you’ve probably noticed Antigravity looks a lot like Windsurf. That’s because Google acquired the Windsurf team in July for $2.4 billion and licensed the technology. Internally at Google, this acquisition happened through DeepMind, where the Windsurf founders landed. I got my first look at Antigravity not long before the public did.

I tested Gemini 3 Pro through Gemini CLI on several coding tasks. In my unscientific but practical tests, Gemini 3 Pro shows more complete responses than Claude Sonnet 4.5, especially when paired with Gemini CLI. The model feels different. More thorough. Less likely to give you a partial solution and wait for you to ask for the rest. This aligns with what I saw in the internal Gemini 3 snapshots I tested before the public release on other Google platforms.

TechRadar ran a comparison where Gemini 3 Pro built a working Progressive Web App with keyboard controls without being asked. Claude struggled with the same prompt. The benchmark data backs this up. Gemini 3 Pro scored 2,439 on LiveCodeBench Pro compared to Claude Sonnet 4.5’s 1,418. ChatGPT Plus costs around BRL 100 per month in Brazil in 2026, reflecting the local equivalent of OpenAI’s standard $20/month ChatGPT Plus costs around ₹2000 per month in India in 2026, reflecting OpenAI’s global base pricing after conversion to Indian

Both Gemini 3 Pro (Google/DeepMind) and Claude Sonnet 4.5 (Anthropic) are 2025-era flagship models optimized for agentic, long-horizon, tool-using workflows — and both place heavy emphasis on coding. Claimed strengths diverge: Google pitches Gemini 3 Pro as a general-purpose multimodal reasoner that also shines at agentic coding, while Anthropic positions Sonnet 4.5 as the best coding/agent model in the world with particularly... Short answer up front: both models are top-tier for software engineering tasks in late 2025. Claude Sonnet 4.5 nudges ahead on some pure software-engineering bench metrics, while Google’s Gemini 3 Pro (Preview) is the broader, multimodal, agentic powerhouse—especially when you care about visual context, tool use, long-context work and... I currently use both models, and they each have different advantages in the development environment. I will now compare them in this article.

Gemini 3 Pro is only available to Google AI Ultra subscribers and paid Gemini API users. However, the good news is that CometAPI, as an all-in-one AI platform, has integrated Gemini 3 Pro, and you can try it for free. Gemini 3 Pro (available initially as gemini-3-pro-preview) is Google/DeepMind’s latest “frontier” LLM in the Gemini 3 family. It’s positioned as a high-reasoning, multimodal model optimized for agentic workflows (that is, models that can operate with tool use, orchestrate subagents, and interact with external resources). It emphasizes stronger reasoning, multimodality (images, video frames, PDFs), and explicit API controls for internal “thinking” depth. Google Gemini 3 (codename Antigravity) and Anthropic Claude Sonnet 4.5 are two of the most advanced AI models as of late 2025.

Gemini 3 is the latest flagship model from Google DeepMind’s collaboration, powering Google’s new AI offerings (including the Antigravity coding IDE and the revamped Gemini assistant app). Claude Sonnet 4.5 is Anthropic’s frontier model in the Claude series, building on their focus of creating helpful, harmless AI with strong coding and reasoning abilities. Both models push the boundaries of what AI can do, but they come with different strengths and design philosophies. This report provides a comprehensive comparison across key dimensions: from raw reasoning prowess and coding skills to multimodal capabilities, long-context memory, tool use, user experience, pricing, and more. We’ll also highlight feedback from users and experts, and note any unique architectural or safety features. The goal is to understand where each model shines and how they differ, helping you choose the right AI for specific needs.

(Throughout this report, “Gemini 3” refers to Google’s Gemini 3 Pro model unless otherwise specified, and “Claude 4.5” refers to Anthropic’s Claude Sonnet 4.5.) Reasoning Abilities: Both Gemini 3 and Claude 4.5 are top-tier general intelligence models capable of complex reasoning tasks. They can solve difficult problems step-by-step, answer nuanced questions, and exhibit “chain-of-thought” reasoning far beyond earlier AI generations. In everyday use, you can ask either model to analyze an argument, solve a logic puzzle, or plan a strategy, and you’ll get a coherent, often insightful answer. However, Gemini 3 has been explicitly engineered to excel at deep, structured reasoning. Google has introduced a special “Deep Think” mode for Gemini 3 that allows it to take extra computation time on hard queries.

In challenging scenarios (like multi-step logic or tricky word problems), Deep Think mode lets Gemini methodically work through the problem, resulting in extremely detailed solutions. Users report that Gemini in Deep Think will sometimes pause briefly as if “pondering” and then produce an answer with exhaustive justification. This gives it an edge on the absolute hardest questions. Claude 4.5 has also improved in reasoning over its predecessors (Anthropic emphasizes its “longer-horizon” thinking), but it doesn’t have a distinct user-triggered mode for deep reasoning – it tends to automatically maintain a consistent,... In practice, Claude is very good at logical consistency and often double-checks its answers, but when faced with the most complex puzzles or academic questions, Gemini (especially with extra time) can pull ahead with... Knowledge and Understanding: Both models were trained on vast amounts of text and code, giving them a broad base of world knowledge.

By late 2025, they also have access to up-to-date information when needed. Gemini 3 is deeply integrated with Google’s ecosystem, including real-time search: it can seamlessly pull in current facts from the web. This means Gemini is less likely to hallucinate outdated info – if you ask about a recent event or a niche fact, it can perform a quick internal search and give you an answer... Claude 4.5 does not have a built-in web search by default, but it was trained on a diverse corpus (likely up to 2025 data), and Anthropic continually fine-tunes it, so it has strong general... On common subjects (history, science basics, general trivia), both are extremely proficient. For esoteric or very recent queries, Gemini’s integration with Google Search gives it a practical advantage – it will literally fetch the latest data.

Claude can be connected to the web through external tools or plugins (and Anthropic provides a browser extension for Claude to do autonomous web browsing when allowed), but that is an optional setup rather... After three caffeine-fueled nights comparing Gemini 3.0 Pro against Claude 4.5 Sonnet across real coding tasks, here’s what I learned: Google’s latest model delivers stunning results when it works, but comes with frustrating quirks. Let’s cut through the hype and see how these AI heavyweights actually perform for development work. When I threw a complex React/TypeScript dashboard project at both models: // Gemini’s TypeScript example – notice the strict typing interface DashboardProps { metrics: RealTimeMetric[]; onUpdate: (payload: MetricPayload) => void; // This specificity prevents bugs } The responsive e-commerce card test revealed:

After smashing my keyboard through 65% failed CLI attempts: This YouTube insight note was created with LilysAI. Sign up free and get 10× faster, deeper insights from videos. This content offers crucial AI model comparison by benchmarking the new Gemini 3 Pro against rivals like Claude 4.5 and GPT-5.1. It provides actionable coding insights by demonstrating how each model handles complex Next.js development tasks, third-party libraries, and UI design prompts. You will discover which large language model excels in real-world full-stack web development and advanced glass morphism styling.

Introduction of Gemini 3 Pro Launch and Comparison Context [0] Benchmarking Methodology and SWV Bench Results [9] Massive Performance Gap in Screen Understanding [16] 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: Google launched Gemini 3 and Antigravity IDE two days ago. I've been testing Gemini 3 since before launch. I got to see Antigravity about the same time the public did. Three things most reviews won't tell you: 1. Capacity issues are real.

Gemini 3 Pro Vs Claude Sonnet 4 5 Antigravity Ide Review

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