In this video, I'll be comparing GPT 5.5, Deepseek V4, and Opus 4.7 across a series of coding and frontend benchmarks to see which model performs best in real-world tasks, how they handle complex UI generation, and whether the new Deepseek and OpenAI releases live up to the hype.

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Key Takeaways:

🚀 Deepseek V4 launches with a massive context window and very aggressive pricing.  
🤖 GPT 5.5 shows improvements in token efficiency and some coding tasks, but still has UI issues.  
🎨 Opus 4.7 performs the best overall on complex frontend and 3D tasks.  
🧪 KingBench 2.0 is designed to test models across multiple coding scenarios, not just agentic workflows.  
🏗️ The video includes tests like an elevator simulator, a ThreeJS contact lens case, and a folding table.  
🍔 The models are also tested on SVG generation, a bow and arrow simulator, and a math question.  
💸 A pricing breakdown shows how Deepseek is much cheaper than GPT 5.5 on API.  
🏆 Overall, Opus 4.7 comes out as the strongest model, while Deepseek underperforms and GPT 5.5 is mixed.

AICodeKing

A hands-on comparison of GPT-5.5, Deepseek V4 Pro, and Claude Opus 4.7 using a custom benchmark called KingBench 2.0, which tests models across coding, frontend, 3D rendering, and general tasks. Results show Opus 4.7 consistently outperforms the others on UI/frontend tasks like an elevator simulator, 3D contact lens case, and bow-and-arrow game. GPT-5.5 performs adequately on some tasks but retains UI design issues. Deepseek V4 Pro underperforms despite its massive 1.6 trillion parameter MoE architecture. Pricing analysis notes Deepseek is extremely cheap while GPT-5.5 is considered overpriced relative to its performance. The author concludes Opus 4.7 is the best overall model but notes usage limits in Claude Code are a growing concern.

GPT-5.5 VS Deepseek V4 Pro VS Opus 4.7: I tested THEM on My KingBench 2.0 Questions!