Скачать с ютуб ChatGPT Vs DeepSeek VS Qwen 2.5 Max: Who Wins? в хорошем качестве

ChatGPT Vs DeepSeek VS Qwen 2.5 Max: Who Wins?

Want to get more customers, make more profit & save 100s of hours with AI? Join me in the AI Profit Boardroom: https://go.juliangoldie.com/ai-profit... 🚀 Get a FREE SEO strategy Session + Discount Now: https://go.juliangoldie.com/strategy-... PLUS get 25% extra FREE on long term contracts! Want More Leads, Traffic & Sales with AI? 🚀 Automate your marketing, scale your business, and save 100s of hours with AI! 👉 https://www.skool.com/ai-profit-lab-7... 🤯 Want more money, traffic and sales from SEO? Join the SEO Elite Circle👇 https://go.juliangoldie.com/register Click below for FREE access to ✅ 50 FREE AI SEO TOOLS 🔥 200+ AI SEO Prompts! 📈 FREE AI SEO COMMUNITY with 2,000 SEOs ! 🚀 Free AI SEO Course 🏆 Plus TODAY's Video NOTES... https://go.juliangoldie.com/chat-gpt-... Join our FREE AI SEO Accelerator here:   / aiseomastermind   Need consulting? Book a call with us here: https://link.juliangoldie.com/widget/... DeepSeek-R1 VS ChatGPT VS Qwen 2.5 Max: Who Wins? DeepSeek R1 vs Qwen 2.5 Max vs ChatGPT: Comprehensive AI Model Comparison In this video, we compare three AI models: DeepSeek R1, Qwen 2.5 Max, and ChatGPT, to determine which one performs best in various tasks. We test capabilities like coding a snake game in HTML, real-time web search, image generation, video generation, and the ability to run locally. Qwen 2.5 Max excels in speed and accuracy, especially in coding games and real-time search. DeepSeek R1, while slower and less accurate, offers the advantage of running locally and providing a free API. ChatGPT shows strong performance in video generation but lacks some features unless upgraded to ChatGPT-4.0. Watch the full comparison to discover which AI model suits your needs best! 00:00 Introduction to AI Model Comparison 00:13 HTML Snake Game Test 01:45 Web Search Feature Test 03:31 Image Generation Showdown 06:29 Video Generation Capabilities 08:40 Local Hosting and API Access 11:56 Conclusion and Recommendations