🚀 Gemini 3.5 Flash is HERE — and honestly… Google might have just dropped one of the most impressive frontend + coding AI models yet.
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In this video, I fully test Gemini 3.5 Flash across insane coding benchmarks including:
🔥 3D Three.js simulations
🔥 Windows 95 recreation
🔥 Interactive operating systems
🔥 Procedural graphics & SVG generation
🔥 Agentic coding workflows
🔥 Physics simulations
🔥 Advanced frontend UI generation
🔥 Complex vibe-coding benchmarks
What shocked me most is how CLOSE this model gets to Claude Opus 4.7 and GPT-5.5 in certain coding and agentic tasks — while being dramatically faster. The frontend taste, architecture, visual polish, and systems thinking are genuinely impressive for a “Flash” tier model.
But… there’s a catch. 👀
Gemini 3.5 Flash is EXTREMELY token hungry and in many cases actually costs more to run than Gemini 3.1 Pro and even GPT-5.5 Medium on certain workloads. So is this really still a “Flash” model anymore?
We break down:
⚡ Real-world coding tests
⚡ Frontend/UI quality
⚡ Three.js & SVG capabilities
⚡ Agentic reasoning benchmarks
⚡ Cost vs performance
⚡ Token efficiency problems
⚡ Why Google’s frontend models are becoming scary good
Honestly, Gemini 3.5 Flash feels less like a lightweight fast model and more like a mini frontier model optimized for vibe coding and interactive web experiences.
👀 Full tests, benchmarks, and my honest thoughts inside.
[Time Stamps]:
0:00 – Introduction
0:52 – My Two Cents
1:35 – Benchmarks
2:04 – Kimi K2.6 Level?
2:24 – My Benchmark
2:54 – Token HUNGRY
4:03 – Best Use Cases
4:55 – How To Use
5:12 – Frontend Demos
6:47 – SVG Output
7:50 – BEST Generation
8:51 – MacOS Clone
9:37 – Three.js Demos
11:51 – Minecraft Clone
13:16 – Voxel Demo
13:26 – UI Quirk
14:47 – Conclusion
#gemini35 #googleai #ai #claudeai #gpt55 #threejs #Frontend #WebDev #CodingAI #geminiflash
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