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Benchmarking ChatGPT, Qwen, and DeepSeek on Real-World AI Tasks
.................................. This article was originally published here: https://decodebuzzing.medium.com/qbenchmarking-chatgpt-qwen-and-deepseek-on-real-world-ai-tasks-75b4d7040742 ................................... The wealthy tech giants in the U.S. once dominated the AI market but DeepSeek’s release caused waves in the industry, sparking massive hype. However, as if that wasn’t enough, Qwen 2.5 emerged — surpassing DeepSeek in multiple areas. Like other reasoning models such as DeepSeek-R1 and OpenAI’s O1, Qwen 2.5-Max operates in a way that conceals its thinking process, making it harder to trace its decision-making logic This article puts ChatGPT, Qwen, and DeepSeek through their paces with a series of key challenges ranging from solving calculus problems to debugging code. Whether you’re a developer hunting for the perfect AI coding assistant, a researcher tackling quantum mechanics, or a business professional, today I will try to reveal which model is the smartest choice for your needs (and budget) Comparative Analysis of AI Model Capabilities:- 1. Chatgpt ChatGPT, developed by OpenAI still remains a dominant force in the AI space, built on the powerful GPT-5 architecture and fine-tuned using Reinforcement Learning from Human Feedback (RLHF). It’s a reliable go-to for a range of tasks, from creative writing to technical documentation, making it a top choice for content creators, educators, and startups However, it’s not perfect. When it comes to specialized fields, like advanced mathematics or niche legal domains, it can struggle. On top of that, its high infrastructure costs make it tough for smaller businesses or individual developers to access it easily ChatGPT, built with a hefty $3B+ investment, is a massive infrastructure model, while DeepSeek achieved similar performance with just $5.6M — classic China moment huh? 2. Deepseek Out of nowhere, DeepSeek emerged as a dark horse in the AI race challenging established giants with its focus on computational precision and efficiency. Unlike its competitors, it’s tailored for scientific and mathematical tasks and is trained on top datasets like arXiv and Wolfram Alpha, which helps it perform well in areas like optimization, physics simulations, and complex math problems. DeepSeek’s real strength is how cheap it is ( no china pun intended
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This article was originally published here: https://decodebuzzing.medium.com/qbenchmarking-chatgpt-qwen-and-deepseek-on-real-world-ai-tasks-75b4d7040742
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The wealthy tech giants in the U.S. once dominated the AI market but DeepSeek’s release caused waves in the industry, sparking massive hype. However, as if that wasn’t enough, Qwen 2.5 emerged — surpassing DeepSeek in multiple areas. Like other reasoning models such as DeepSeek-R1 and OpenAI’s O1, Qwen 2.5-Max operates in a way that conceals its thinking process, making it harder to trace its decision-making logic
This article puts ChatGPT, Qwen, and DeepSeek through their paces with a series of key challenges ranging from solving calculus problems to debugging code. Whether you’re a developer hunting for the perfect AI coding assistant, a researcher tackling quantum mechanics, or a business professional, today I will try to reveal which model is the smartest choice for your needs (and budget)
Comparative Analysis of AI Model Capabilities:-
1. Chatgpt
ChatGPT, developed by OpenAI still remains a dominant force in the AI space, built on the powerful GPT-5 architecture and fine-tuned using Reinforcement Learning from Human Feedback (RLHF). It’s a reliable go-to for a range of tasks, from creative writing to technical documentation, making it a top choice for content creators, educators, and startups However, it’s not perfect. When it comes to specialized fields, like advanced mathematics or niche legal domains, it can struggle. On top of that, its high infrastructure costs make it tough for smaller businesses or individual developers to access it easily
ChatGPT, built with a hefty $3B+ investment, is a massive infrastructure model, while DeepSeek achieved similar performance with just $5.6M — classic China moment huh?
2. Deepseek
Out of nowhere, DeepSeek emerged as a dark horse in the AI race challenging established giants with its focus on computational precision and efficiency.
Unlike its competitors, it’s tailored for scientific and mathematical tasks and is trained on top datasets like arXiv and Wolfram Alpha, which helps it perform well in areas like optimization, physics simulations, and complex math problems. DeepSeek’s real strength is how cheap it is ( no china pun intended
