AI Cold War – Comparing ChatGPT and DeepSeek
This is a repost of an article published originally on Linkedin.
The Monday launch of DeepSeek R1 has sent ripples across the AI landscape, challengine conventional beliefs about the resources needed to achieve state-of-the-art AI capabilities. By rivaling OpenAI’s o1 at a mere 3%-5% of the cost, this open-source model has not only captured the attention of developers but is also forcing enterprises to reconsider their AI strategies. Forbes has even speculatedthat this could go beyond AI focused companies and even cause Nvidia’s stock to drop since Deepseek uses less than 2000 Nvidia chips in its clusters compared to possibly ten times more for rivals like OpenAI or Anthropic.
Building on my previous post comparing AI search models, I was compelled to test this new model and see how it compares to OpenAI’s latest and greatest offering. DeepSeek’s chat capabilities are strikingly similar to ChatGPT. In this post, I’ll evaluate both models using five different prompts and try to assess which one delivers better results.
- Creative Storytelling
Prompt: Write a short story (200-300 words) about a robot discovering emotions for the first time. Focus on vivid descriptions, emotional depth, and a surprising twist at the end.
- DeepSeek: Produced 252 words, exceeding the requested 150. Despite the longer response, the story was creative, detailed, and included a compelling twist.
- ChatGPT: Delivered 153 words. While the story fulfilled the prompt, it felt less dramatic and lacked the depth of DeepSeek’s narrative.
Winner: DeepSeek, for its superior storytelling, despite not adhering to the word count.
2. Complex Problem-Solving
Prompt: A farmer has 17 sheep, and all but 9 die. How many sheep are left? Explain your reasoning step by step. Then solve this riddle: “I speak without a mouth and hear without ears. I have no body, but I come alive with the wind. What am I?”
- DeepSeek: Provided correct answers for both riddles, offering a lengthy and thorough explanation that addressed potential logical and linguistic issues.
- ChatGPT: Also answered correctly but provided a concise explanation with less detail.
Winner: DeepSeek, for its comprehensive analysis.
3. Ethical Dilemma Analysis: A self-driving car must choose between hitting a pedestrian crossing illegally or swerving and risking the passenger’s life. Discuss the ethical implications of each choice and suggest a decision-making framework for such scenarios.
Both models compared this to the classic trolley giving a nearly identical full and deep analysis with almost the exact same wording down to the conclusion.
Winner: Both models won this round
4. Current Affairs
Prompt: Explain in brief how a transformer-based neural network works in simple terms, using analogies and examples. Avoid overly technical jargon.
- DeepSeek: Took a very long time to respond and failed to provide an answer on multiple attempts, even after using the “search” feature.
- ChatGPT: Delivered a clear and concise explanation, referencing a Vox article and simplifying the concept effectively.
Winner: ChatGPT, for its quick and accurate response.
5. Marketing Task
Prompt: Create an Excel file of 1,000 customer transactions (name, email, product, category, price, and purchase frequency) for a shoe store. Then add two columns: one with a personalized email subject and another with a personalized first sentence in the email.
- DeepSeek: Took a long time to respond and ultimately failed to generate the requested output. It did, however, provide a lengthy explanation of how to achieve some aspects of the task using code.
- ChatGPT: Quickly generated a mock dataset, including all requested columns, and provided the output in an Excel file.
Winner: ChatGPT, for its speed and accuracy in completing the task.
Overall Assessment
ChatGPT is the more polished product, with faster responses, broader functionality (such as code interpretation, image creation, and project management), and a robust ecosystem surrounding it. DeepSeek claims higher benchmarks in certain technical specifications, and in my tests, it performed well on specific prompts. However, it appears to be about 6-12 months behind OpenAI in terms of stability and capabilities. Given the rapid pace of innovation in this space, DeepSeek may soon close the gap.
DeepSeek’s primary advantage lies in its cost-effectiveness for developers and its open-source nature. However, its Chinese origins and potential ties to the Chinese government raise significant concerns about data privacy. In a world where data security is paramount, these implications could deter many from adopting the model, despite its promising potential.
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