University of Kwazulu-Natal

Gemini 3 Pro Vs Claude Sonnet 4 5 Coding Thinking Mode Test

Bonisiwe Shabane
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gemini 3 pro vs claude sonnet 4 5 coding thinking mode test

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 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.

Google Gemini 3 and Claude Sonnet 4.5 represent two distinct approaches to AI-assisted coding, with Gemini focusing on speed, multimodal flexibility, and agentic workflows and Claude prioritizing correctness, structured reasoning, and production-grade code reliability. Their differences become clear when observing how each model performs in debugging, refactoring, benchmark evaluations, multimodal tasks, and multi-file engineering scenarios. Gemini 3 is structured around an agentic architecture capable of interpreting mixed inputs, coordinating multi-step actions, and interacting across editor, terminal, and browser environments, making it effective for rapidly evolving or visually influenced projects. The model provides quick responses during debugging, supports multimodal comprehension for diagrams and UI images, and integrates naturally with Google-native tools and cloud services. Its speed and responsiveness make it an efficient engine for prototyping interfaces, modifying frontend elements, and coordinating tasks across multiple workspace components. Claude 4.5 vs GPT-5.1 vs Gemini 3 Pro — and what Claude 5 must beat

November 2025 saw a seismic shift in the LLM market. GPT-5.1 (Nov 13) and Gemini 3 Pro (Nov 18) launched within days of each other, dramatically raising the bar for Claude 5. Here's what Anthropic is up against: With 77.2% on SWE-bench Verified—the highest score ever achieved—Claude Sonnet 4.5 is the undisputed king of coding AI. It achieved 0% error rate on Replit's internal benchmark, demonstrating unprecedented reliability for production code. Gemini 3 Pro scored 31.1% on ARC-AGI-2 (the 'IQ test' for AI), a 523% improvement over its predecessor.

It won 19 out of 20 benchmarks against Claude 4.5 and GPT-5.1, with a massive 1M token context window. GPT-5.1 achieved 76.3% on SWE-bench and 94% on AIME 2025 (top 0.1% human performance in mathematics). Its adaptive reasoning feature dynamically adjusts thinking time, providing 30% better token efficiency than GPT-5. 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: 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. 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. One silly web game and a surprising result When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. I've dreamed of this silly game for years, and only Gemini 3 could bring it partially to life.

Google unveiled its powerful new Gemini 3 models this week, and I decided to take Gemini 3 Pro for a test drive on one of my pet projects: Thumb Wars, a digital version of... You know the one, where you grasp each other's hands and then use just your thumbs to battle it out or "wrestle". To win, you simply have to "pin" the opponent's thumb under your own. For the digital version, I envisioned a virtual ring and some floating thumbs all controlled by screen taps or keyboard controls. With the release of a far smarter Gemini, I thought I would let it try its hand, er, virtual thumb at it. Comparing 2 AI models · 5 benchmarks · Google, Anthropic

Gemini 3 Pro Preview (high) offers the best value at $2.00/1M, making it ideal for high-volume applications and cost-conscious projects. Gemini 3 Pro Preview (high) leads in reasoning capabilities with a 90.8% GPQA score, excelling at complex analytical tasks and problem-solving. Gemini 3 Pro Preview (high) achieves a 62.3 coding index, making it the top choice for software development and code generation tasks. All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.

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