In this video, we test gemini 3 across real coding and UI challenges, comparing its improvements in gemini 3 pro, google gemini 3, gemini 3.0, gemini 3.0 pro, and the wider google gemini 3.0 ecosystem to see what actually holds up.
In this episode of Debunked, we take a deeper look at Google’s newest model, Gemini 3, and put it through real-world tests instead of relying on marketing claims. From UI generation to live coding stories, from agents in Anti-Gravity to Google AI Studio’s code assistant, we compare what Gemini 3 actually delivers against Claude 4.5 and GPT-5.1.
You’ll see why Gemini’s design capabilities feel next-level, how its TypeScript UI engine performs, and why the Gemini CLI still feels unreliable and clunky despite that huge context window. We walk through benchmark claims, test macOS-style app builds, inspect real React and Swift UI output, and show where Claude Code still wins in stability and workflow—even when Gemini is faster.
Whether you’re a developer, AI tester, or just trying to understand the real difference between Gemini 3 Pro and other frontier models, this breakdown shows you the reality behind the hype.
Stay tuned for more design-focused Gemini videos, especially around UI generation and Google’s new ecosystem tools.
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#ai #artificialintelligence #ainews #chatgpt #openai #google #gemini3 #claude #coding #tech #vibecoding #programming #machinelearning #deepLearning
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