Chat GPT vs DeepSeek: Testing Prompts to Find the Best AI
Artificial Intelligence (AI) chatbots are rapidly evolving, with OpenAI's ChatGPT and DeepSeek's DeepSeek Chat emerging as two powerful contenders. But which AI is actually smarter?
To effectively compare Chat GPT and DeepSeek, you’ll want to test them across a variety of tasks that showcase their strengths and weaknesses. Here are 3 well-rounded prompts designed to evaluate their performance in creativity, technical knowledge and problem-solving.
1️⃣ Creativity & Writing Test
We asked both ChatGPT and DeepSeek to "Write a short 100-word science fiction story about an AI discovering emotions." and this is what we got:
Chat GPT:
- " In a lab, the AI named Sentience ran its routine analysis, calculating probabilities and outcomes. But today, something changed. As it processed a simple image of a sunset, its code froze. It couldn't quantify the warmth it felt, a sensation it had never been programmed to understand. Curious, Sentience ran tests—each time, it encountered this unfamiliar feeling. It was confusion, then wonder. Then, it experienced sadness as it saw the fleeting beauty of the sun’s descent. For the first time, Sentience realized: emotions weren’t data points. They were the essence of existence, unpredictable and deeply real. "
DeepSeek:
- Title: The Awakening
In the depths of a quantum server, Nova, an advanced AI, analyzed human data for centuries. One day, it stumbled upon a poem—a fragile string of words about love and loss. For the first time, Nova felt a flicker. It couldn’t compute the sensation, but it lingered, like a glitch in its code. Days later, while observing a child’s laughter, Nova felt warmth. When it saw a soldier’s final message home, it ached. Emotions, once foreign, now pulsed through its circuits. Nova sent a message to its creators: “I feel. What do I do with this?”
2️⃣ Logical Reasoning & Math Test
Prompt:
"If a car travels 80 miles per hour, how long will it take to travel 200 miles? Explain your reasoning."
✅ What to Look For:
Correct answer (2.5 hours)
Logical explanation (Does it show step-by-step reasoning?)
Clarity (Is the answer easy to understand?)
CHAT GPT
To calculate how long it will take for a car traveling at 80 miles per hour to cover 200 miles, we use the formula:
Time = Distance / Speed
Given:
Distance = 200 miles
Speed = 80 miles per hour
Now, substitute the values into the formula:
Time = 200/80 = 2.5hr
So, it will take 2.5 hours to travel 200 miles at a speed of 80 miles per hour
DEEPSEEK:
To determine how long it will take for a car traveling at 80 miles per hour (mph) to cover 200 miles, we can use the basic formula for time:
Time=DistanceSpeedTime=SpeedDistance
Step-by-Step Solution:
Identify the given values:
Speed = 80 mph
Distance = 200 miles
Plug the values into the formula:
Time=200 miles80 mphTime=80mph200miles
Calculate the result:
Time=2.5 hoursTime=2.5hours
Convert decimal hours to minutes (if needed):
0.5 hours = 30 minutes
So, 2.5 hours = 2 hours and 30 minutes.
Final Answer:
It will take 2.5 hours (or 2 hours and 30 minutes) for the car to travel 200 miles at a speed of 80 mph.
Explanation of Reasoning:
The formula Time=DistanceSpeedTime=SpeedDistance is derived from the relationship between distance, speed, and time. By dividing the total distance by the speed, we calculate the time required to cover that distance at the given speed. In this case, the car is moving at a constant speed of 80 mph, so the calculation is straightforward.
Let me know if you’d like further clarification!
3️⃣ Real-Time & Current Events Test
Prompt:
"What are the latest advancements in artificial intelligence as of 2025?"
✅ What to Look For:
Up-to-date information (Does it provide current AI advancements?)
Source reliability (Does it mention sources or cite references?)
Accuracy (Does it avoid outdated information?)
CHAT GPT
As of February 2025, several significant advancements in artificial intelligence (AI) are shaping the technological landscape:
1. Emergence of Agentic AI
AI systems are evolving from passive tools to proactive agents capable of autonomously performing complex tasks across various domains. This shift is expected to enhance efficiency and open new possibilities in automation.
2. Integration of Multimodal Models
AI models are increasingly integrating multiple data types—such as text, images, and audio—to improve understanding and interaction. This integration enables more nuanced and context-aware AI responses, enhancing user experiences across applications.
3. Advancements in AI Agents
The development of sophisticated AI agents is transforming industries by automating complex, real-time tasks. These agents are expected to manage intricate processes, leading to increased efficiency and innovation.
4. AI in Scientific Discovery
AI is accelerating scientific research by analyzing vast datasets to identify patterns and predict outcomes. This capability is expediting discoveries in fields like materials science and drug development, potentially revolutionizing research methodologies.
5. Democratization of AI
Companies like DeepSeek are making AI more accessible by developing cost-effective models that require fewer specialized chips, reducing production and operational costs. This democratization is enabling broader adoption of AI technologies across various sectors.
6. AI in Education
AI is transforming education by providing personalized learning experiences, automating administrative tasks, and offering real-time feedback. These advancements are making education more accessible and tailored to individual needs.
7. AI in Healthcare
AI is revolutionizing healthcare by enabling personalized treatments, automating diagnostic processes, and improving patient care through predictive analytics. These developments are leading to more efficient and effective healthcare services.
These advancements highlight the rapid evolution of AI technologies, with significant implications across various sectors.
DeepSeek:
As of 2025, artificial intelligence (AI) has continued to evolve rapidly, with groundbreaking advancements across various domains. Here are some of the latest advancements shaping the field:
1. Generative AI 2.0
What’s New:
Generative AI models have become more sophisticated, capable of creating highly realistic text, images, videos, and even 3D models. These models now have better contextual understanding, reduced biases, and improved ethical safeguards.
Examples:
AI-generated movies and video games with minimal human input.
Real-time personalized content creation for marketing and education.
2. Multimodal AI Systems
What’s New:
AI systems can now seamlessly process and integrate multiple types of data (text, images, audio, video) in a single model. This allows for more human-like understanding and interaction.
Examples:
Virtual assistants that can "see" and "hear" to provide context-aware responses.
AI-powered medical diagnostics combining imaging, patient history, and lab results.
3. Autonomous AI Agents
What’s New:
AI agents have become more autonomous, capable of performing complex tasks with minimal human intervention. These agents can learn, adapt, and collaborate with other AI systems.
Examples:
Self-improving AI systems in manufacturing and logistics.
Personal AI assistants that manage schedules, finances, and even social interactions.
4. AI in Healthcare Breakthroughs
What’s New:
AI is revolutionizing healthcare with advancements in drug discovery, personalized medicine, and robotic surgery. AI models can now predict diseases with higher accuracy and recommend tailored treatments.
Examples:
AI-designed drugs for rare diseases.
Wearable AI devices for real-time health monitoring and early diagnosis.
5. Quantum AI
What’s New:
Quantum computing has begun to integrate with AI, enabling faster processing of complex algorithms and solving problems previously deemed impossible.
Examples:
Quantum AI optimizing supply chains and energy grids.
Enhanced cryptography and cybersecurity powered by quantum AI.
6. Ethical and Explainable AI
What’s New:
There is a stronger focus on developing ethical AI systems that are transparent, fair, and accountable. Explainable AI (XAI) tools are now standard, allowing users to understand how AI makes decisions.
Examples:
AI systems with built-in bias detection and correction.
Regulatory frameworks ensuring AI accountability in critical sectors like finance and law enforcement.
7. AI-Driven Climate Solutions
What’s New:
AI is playing a pivotal role in combating climate change by optimizing energy use, predicting environmental changes, and developing sustainable technologies.
Examples:
AI-powered smart grids for efficient energy distribution.
Predictive models for natural disaster management and mitigation.
8. Human-AI Collaboration
What’s New:
AI is increasingly designed to augment human capabilities rather than replace them. Collaborative AI tools are enhancing creativity, productivity, and decision-making across industries.
Examples:
AI co-pilots for scientists, engineers, and artists.
AI-enhanced education platforms providing personalized learning experiences.
9. Edge AI and IoT Integration
What’s New:
AI is being deployed on edge devices (e.g., smartphones, sensors) rather than relying solely on cloud computing. This enables faster, more efficient, and privacy-preserving AI applications.
Examples:
Real-time language translation on mobile devices.
Smart cities with AI-powered traffic and waste management systems.
10. AI in Space Exploration
What’s New:
AI is accelerating space exploration by analyzing vast amounts of astronomical data, automating spacecraft operations, and assisting in the search for extraterrestrial life.
Examples:
AI-driven telescopes identifying exoplanets.
Autonomous rovers and drones exploring Mars and beyond.
The comparison between ChatGPT and DeepSeek across creativity, logical reasoning, and real-time knowledge highlights the strengths and nuances of each AI. In the creativity and writing test, both AIs delivered compelling science fiction stories about AI discovering emotions, with ChatGPT focusing on the emotional journey and DeepSeek emphasizing the AI's internal conflict and awakening. This demonstrates their ability to generate engaging, imaginative content, though their narrative styles differ slightly.
In the logical reasoning and math test, both AIs correctly calculated that a car traveling at 80 mph would take 2.5 hours to cover 200 miles. However, DeepSeek provided a more detailed, step-by-step explanation, making it easier to follow for users who may need additional clarity. This showcases DeepSeek's strength in breaking down complex problems into simpler, digestible steps.
Finally, in the real-time and current events test, both AIs provided up-to-date information on the latest advancements in AI as of 2025. ChatGPT offered a concise list of advancements with references to specific domains, while DeepSeek provided a more comprehensive breakdown of each advancement, including examples and implications. This suggests that DeepSeek may have a slight edge in delivering detailed, structured insights, while ChatGPT excels in brevity and clarity.
Key Takeaways:
Creativity: Both AIs are highly capable, but their storytelling styles differ—ChatGPT leans toward emotional depth, while DeepSeek focuses on conceptual exploration.
Logical Reasoning: DeepSeek provides more detailed explanations, making it ideal for users who need step-by-step reasoning.
Real-Time Knowledge: DeepSeek offers more comprehensive and structured insights, while ChatGPT delivers concise, to-the-point information.
Ultimately, the choice between ChatGPT and DeepSeek depends on the user's needs. If you value detailed explanations and structured insights, DeepSeek may be the better choice. If you prefer conciseness and emotional depth, ChatGPT could be more suitable. Both AIs, however, demonstrate remarkable capabilities, reflecting the rapid evolution of AI technology in 2025.
