Since its debut, DeepSeek has been disrupting the AI market. Users have been wondering if DeepSeek is better than ChatGPT.
To settle the debate, I put both to the test in various projects, observing their performance in tasks like coding, math, writing, and more. I tracked their response speed, accuracy, functionality, and features to highlight key differences.
No technical jargon—just a clear, practical comparison based on hands-on experience. So, read on to learn from my own testing how DeepSeek stacks up against ChatGPT for coding, math, and more.
In this article
What Are DeepSeek and ChatGPT?
What is DeepSeek?
DeepSeek was launched in July 2023 by Liang Wenfeng, a former quantitative trader. Headquartered in Hangzhou, Zhejiang Province, and backed by the hedge fund High-Flyer, it has rapidly become a major AI force specializing in large language models (LLMs).
AI Models for Specific Needs
DeepSeek has developed models with targeted capabilities:
- DeepSeek-LLM: A general-purpose AI model.
- DeepSeek-Coder: Designed for coding, debugging, and optimization.
- DeepSeek-Math: Excels at solving complex mathematical problems.
- DeepSeek-R1: Competes with OpenAI and Meta’s models while using fewer resources.
DeepSeek-V3 has 671 billion parameters. However, only 37 billion are activated per token, which reduces computational strain. This makes it efficient even on standard machines.
What Sets DeepSeek Apart?
- Lower Costs - V3 was trained for $6 million, a fraction of OpenAI’s $100 million.
- Open-Source Approach - Models are freely available for public use.
- Optimized Hardware Use - Runs efficiently on standard machines, making AI more accessible.
Practical Applications
DeepSeek is already delivering value:
- Software Development - DeepSeek-Coder accelerates coding and debugging.
- Education - DeepSeek-Math helps with solving difficult equations.
- Research & Analysis - DeepSeek-LLM and DeepSeek-R1 support large-scale data processing.
What is ChatGPT?
ChatGPT, developed by OpenAI, generates text based on user input and continuously evolves. It started with GPT-3, advanced through GPT-4, and now includes models like o3 mini and o1, which improve reasoning.
Advancements in AI Models
- GPT-4o: A multimodal system processing text, images, and audio. Faster and more cost-efficient than GPT-4 Turbo.
- o1 Model: Designed for complex reasoning, improving performance in technical and analytical fields.
Why ChatGPT Stands Out?
- Multimodal Abilities: GPT-4o integrates multiple data types.
- Deeper Analysis: The o1 model enhances reasoning in logic-heavy tasks.
- Better Context Memory: Tracks conversations for more relevant replies.
- Flexible Interaction: Adjusts to user preferences for a natural conversation.
How Is It Used?
- Education: Helps with learning, lesson planning, and explanations.
- Business: Automates customer support and daily operations.
- Creative Work: Supports brainstorming, writing, and editing.
- Healthcare: Assists with research and patient communications.
- Marketing: Personalizes messaging and automates outreach.
DeepSeek vs. ChatGPT: Their Features
My approach was hands-on to test both the tools, and I worked through various specific tasks step by step.
Mathematics
I tested DeepSeek and ChatGPT on various math problems, from calculus to combinatorial puzzles. Their approaches differed significantly.
ChatGPT often offered concise explanations and produced correct answers for simpler tasks.
DeepSeek, however, took a more systematic approach, breaking each step down with greater detail.
For instance, ChatGPT's response to a complex calculus problem was clear. However, DeepSeek included extra steps that made verifying the solution easier.
Across multiple tests, I noticed a trade-off. DeepSeek’s step-by-step precision helped minimize errors in multi-step problems. ChatGPT responded more quickly when less reasoning was required.
Both models handled linear algebra and differential equations well. Yet, DeepSeek’s structured approach gave it a slight edge in problems requiring detailed verification.
Coding
I ran tests on both models with tasks such as Python code generation, debugging, and sorting algorithm optimization.
ChatGPT generated reliable code with few errors and provided straightforward explanations.
DeepSeek took a more thoughtful, analytical path.
For instance, both models solved a recursion problem, but DeepSeek included detailed notes on edge cases and alternative methods.
In debugging, ChatGPT quickly spotted syntax and logic errors, while DeepSeek broke down the code structure step by step.
ChatGPT is faster, but DeepSeek often adds depth by explaining optimizations and pitfalls. Choosing between them comes down to whether speed or detailed insights matter more.
Writing & Creativity
To assess how each model handles creative writing, I provided a flexible story prompt and observed their storytelling styles. Their differences quickly became clear.
ChatGPT produced a flowing, conversational story with natural transitions. The language felt organic and immersive, carrying emotional weight. Strong imagery made scenes feel vivid and alive.
DeepSeek took a more structured approach. Each section was carefully arranged, creating a steady and logical progression. It used precise descriptions and concrete details—like a "holographic map"—to anchor the narrative, ensuring clarity.
If storytelling is meant to be engaging and fluid, ChatGPT does it well. If the priority is logical flow and conciseness, DeepSeek is the stronger choice.
Both models excel in their own way—one prioritizes emotional connection, while the other values structure and clarity.
Chess and Logical Thinking
To test logical reasoning and chess skills, I challenged both models with mid-game positions. I asked them to suggest moves and justify their choices.
ChatGPT responded with sound chess principles, offering short but logical explanations and a quick read on possible opponent reactions.
DeepSeek, however, went further. It also examined multiple move options, explained counterplays, and provided a structured breakdown of its reasoning for all possible best moves.
For sequential puzzles, DeepSeek’s methodical step-by-step approach made it easier to track each stage of the solution. ChatGPT, while quicker, sometimes left out key reasoning steps.
If the goal is deep analysis, DeepSeek provides more transparency, while ChatGPT remains a reliable choice for fast responses.
Multilingual Capabilities
I tested ChatGPT and DeepSeek by translating English text into Urdu, French, and Chinese. The content was a mix of technical details and casual expressions to see how well each model balanced accuracy and fluency.
ChatGPT produced clear, structured translations. But it often leaned toward a literal approach, especially with idioms, sometimes missing cultural nuances.
DeepSeek felt more natural. It preserved tone and adapted idioms in a way that made more sense to native speakers.
Both models handled technical content well. But for informal phrases like "It's raining cats and dogs," DeepSeek provided a culturally adapted equivalent. But ChatGPT stuck to a more direct translation.
If technical accuracy is your priority, either model will work. But if fluency, cultural adaptation, and tone matter, DeepSeek does a better job.
Context Retention & Memory
To test memory, I fed both models long-form inputs and engaged in multi-turn conversations.
When asked to summarize previous discussions, ChatGPT recalled most key points but occasionally dropped minor details in longer exchanges.
DeepSeek showed stronger consistency, tracking essential elements throughout multiple interactions. In follow-up questions, it built on past responses in a structured, step-by-step way.
If you're working with complex, ongoing conversations and need a model that maintains context precisely, DeepSeek may be the better choice.
Summarization & Information Extraction
ChatGPT and DeepSeek take different approaches to text summarization. I uploaded a newsletter to both models and asked them to summarize it.
ChatGPT creates smooth, easy-to-read summaries with a natural flow. It captures the main ideas well but may skip some finer details.
DeepSeek, on the other hand, focuses on structure and detail. It breaks down key points clearly, making it ideal for long or technical content.
In my case, ChatGPT provided a concise and insightful overview, while DeepSeek maintained structure and completeness.
The ideal choice depends on whether you need a quick, conversational summary or a detailed breakdown.
DeepSeek & ChatGPT Pricing: Which One Should You Pay For?
Below is a simple cost overview for DeepSeek compared to ChatGPT. I have used both platforms to share a clear, concrete breakdown.
Is DeepSeek Free?
DeepSeek offers unlimited free access to its models through the web or mobile app. For business use, you turn to its API.
API Cost
- With the chat model (DeepSeek‑V3), cached input tokens are $0.07 per million tokens, while non‑cached inputs are $0.27 per million tokens. Output tokens cost $1.10 per million tokens.
- For reasoning tasks with DeepSeek‑R1, the fees are higher: $0.14 per million tokens for cached inputs, $0.55 per million for non‑cached inputs, and $2.19 per million for outputs.
Your cost is simply the token count multiplied by the rate, deducted from your balance.
What Is the Price of ChatGPT?
ChatGPT includes a free tier, featuring GPT‑4o mini, web search, and basic file uploads.
- A $20 monthly Plus plan increases limits and adds features like extended messaging and image generation.
- The Pro plan, at $200 per month, unlocks unlimited access to all reasoning models and offers advanced research and voice/media tools.
- Teams and Enterprise plans provide extra features for collaboration and security.
Which Is Cost-effective?
DeepSeek is free, but it comes with a very cost‑effective API, particularly for reasoning tasks. ChatGPT, on the other hand, offers a solid free base with subscription upgrades for more features.
DeepSeek vs. ChatGPT: Performance
Comparing DeepSeek and ChatGPT requires concrete data and practical observations. This analysis relies on public benchmarks, technical specifications, and response behavior.
Which One Responds Faster & More Accurately?
Response Speed and Efficiency
ChatGPT
- Typically responds quickly to standard queries, thanks to its optimized infrastructure.
- Behavior: Simple text generation and information retrieval tasks usually take only a few seconds.
DeepSeek
- Response times vary by model type (e.g., DeepSeek-Coder, DeepSeek-Math) and task complexity.
- Behavior: Handles complex calculations and code generation more thoroughly, sometimes taking longer for deeper analysis.
Accuracy and Performance in Specific Domains
ChatGPT
- Excels in general language comprehension.
- Performance in specialized fields depends on the task—strong overall but not as precise as domain-specific models.
- Benchmarking: Performs well in general-purpose language tests.
DeepSeek
- Built for technical domains, with models like DeepSeek-Coder and DeepSeek-Math.
- DeepSeek-Coder: Scores highly on public code generation benchmarks, including HumanEval, with strong problem-solving ability.
- DeepSeek-Math: Excels in complex mathematical benchmarks, offering step-by-step solutions.
- Behavior: DeepSeek-Coder provides detailed code explanations and handles edge cases, while DeepSeek-Math focuses on detailed proofs and calculations.
Which AI Knows More?
- ChatGPT: Broad knowledge from a vast dataset, making it useful for general tasks.
- DeepSeek: Prioritizes specialized expertise, leading to greater accuracy in targeted fields.
How Deepseek & ChatGPT Score In Industry-standard AI Benchmarks?
Model Architecture and Specialization
- ChatGPT uses a transformer-based architecture for general language tasks like conversation, text generation, and research.
- DeepSeek adopts specialized architectures for coding and mathematics, enhancing accuracy in technical domains.
Key Considerations
- These benchmarks depend on datasets and testing conditions.
- Factors like model size, training data, and hardware impact performance.
- AI models are constantly evolving, making version comparisons essential.
Should You Use DeepSeek or ChatGPT?
From my experience, DeepSeek is the better pick when precision matters, especially for coding and math-heavy work. But when time is short, ChatGPT is still the fastest way to generate ideas or spark creativity. Using both has given me the flexibility I need.
Here’s a quick table of comparison to help you choose the best AI.
| Feature | DeepSeek | ChatGPT |
| Math | Step-by-step, structured problem-solving with high accuracy. | Fast but skips steps, increasing error risk. |
| Coding | Explains logic, edge cases, and alternative solutions. | Quickly generates functional code, ideal for prototyping. |
| Writing | Clear, structured content with a logical flow. | Fluid, engaging narratives for storytelling. |
| Logical Reasoning | Deep analysis, structured decision-making (e.g., chess, strategy). | Fast but lacks depth in complex reasoning. |
| Translations | Adapts idioms and cultural nuances for a natural flow. | More literal, sometimes rigid in casual contexts. |
| Context Retention | Tracks details well in long conversations. | Occasionally loses minor points over time. |
| Summarization | Detailed, structured breakdowns. | Smooth, conversational overviews. |
| Speed | Slightly slower due to the depth of analysis. | Faster, making it ideal for quick responses. |
| Best For | Precision, structured reasoning, and deep analysis (math, coding, translations). | Speed, creativity, and casual writing (storytelling, quick summaries). |
Alternatives to DeepSeek and ChatGPT
Many think of AI as just chatbots, but it’s far more than that. It can generate visuals, map out ideas, edit videos, and more. It’s not just about efficiency—it’s a tool that elevates creativity while handling repetitive tasks.
Look at such AI tools:
EdrawMind: AI for Mind Maps and Slides
Try the app & get 500 free AI tokens
If brainstorming feels overwhelming, EdrawMind simplifies it.
- AI Idea Generation: Start with a topic, and AI suggests related concepts.
- Structured Mind Maps: Ideas are instantly arranged into an organized diagram.
- Slide Conversion: Turn mind maps into slides effortlessly.
- Live Collaboration: Work with teams in real time.
A great tool for students, professionals, and anyone who needs clarity fast.
DeepArt.io: AI for Image Transformation
DeepArt.io turns ordinary images into digital art. The process is simple:
- Upload a photo.
- Choose an artistic style.
- AI generates unique artwork.
A quick and free way to enhance images for creative projects.
Filmora: AI for Video Editing
Filmora speeds up video creation.
- Smart Editing: AI trims and enhances clips automatically.
- Pre-Made Templates: Get professional results with minimal effort.
- Text-to-Video: Input a script, and AI assembles a complete video.
Perfect for creators who want high-quality videos without complex editing.
Ending Notes
In short, my experience shows that DeepSeek excels in coding and math by breaking down problems into structured steps. It’s like a tutor who never skips details.
ChatGPT is faster, more conversational, and great for creative work but may gloss over details in complex reasoning.
And while these tools are transforming how we work, they’re just the tip of the AI iceberg. If you wish to push your creative boundaries, explore EdrawMind. Its mind-mapping tools offer a clear way to arrange ideas and simplify your creative steps.
EdrawMind
AppsEdrawMind Online
