Is ChatGPT or DeepSeek Better For Content Creation?

Which tool is more likely to listen when you angrily tell them to WRITE LIKE A HUMAN? It depends on the hour. But that is the whole fun of creating with AI tools like ChatGPT and DeepSeek. As we are speaking, these models undergo refinement. So, the ones that perform better may be replaced by others. 

In this article, we are comparing the two specifically for content creation. We will throw a few writing tasks at both tools and decode the responses together to see how each tool copes. 

ChatGPT and DeepSeek in numbers 

The fact that both platforms are central to the generative AI and content creation process is undeniable. Let’s take a look at how ChatGPT and DeepSeek are generally used in terms of creating content and not only. 

• ChatGPT is available almost all around the world, currently in 180 countries. 
• GPT-4, the engine behind ChatGPT, is trained on over 1 trillion parameters and can understand around 25 languages․
• The most common use case for ChatGPT is general research (about 36%), followed by academic research (18%), helping with coding (14%), and creating emails (14%). 
• Gen Z is using ChatGPT more frequently than other generations, with over 60% reporting regular use.

• ChatGPT significantly enhances productivity. Software engineers using it complete 126% more projects per week, customer support agents handle 13.8% more inquiries per hour, and business professionals produce 59% more documents per hour.
• 70% of users rated their ChatGPT experience as positive, with helpfulness being a main reason.
• As of April 2025, DeepSeek has approximately 96.88 million monthly active users worldwide․ 
• DeepSeek’s iOS downloads in China made up 39% of the total, followed by the U.S. with 16%, India with 10%, and South Korea with 7%.
• DeepSeek is widely used by media companies, with reports showing a 40% increase in content creation efficiency.

When we take a look at what statistics say, the summary of all those numbers would allow us to make a solid conclusion. 

ChatGPT dominates in global reach and total content generated, with hundreds of millions of users and billions of content outputs daily. It is widely used for a range of content creation tasks across personal, academic, and enterprise settings.

DeepSeek is a fast-growing competitor, especially strong in Asia. It has tens of millions of users and a particular focus on business, academic, and media content creation. DeepSeek is recognized for boosting efficiency in media workflows. 

Shall you use ChatGPT or DeepSeek in content creation?

I have been using both chatbots in my daily content operations and not only. Yet, every time they ask “Is ChatGPT or DeepSeek better?”,  my answer is that it depends on your content goal. 

To give you a tangible answer to this question, I prepared several content tasks to complete on both chatbots. We will analyze the responses together and identify the winner for brainstorming, reasoning, idea structuring, accuracy, and some other factors. 

But before that, here is a quick comparison of performance when it comes to producing content. 

Task 1: Brainstorming and idea generation

The first task of the experiment was to generate ideas for a newsletter. So I used this very simple prompt that does not really provide details:

“Suggest me 5 topic ideas for my newsletter named “English writing for non-natives”. I intend to help non-native English writers become more confident in their writing skills and work more efficiently. Keep the ideas casual and do not solely focus on challenges, mistakes, and observations that are most commonly covered and are viewed as clichés”. 

Results from ChatGPT 

ChatGPT framed the ideas in a more “how-to” format, which is not exactly the wording I would choose to include in the titles. Beyond the phrasing, it did a great job of tying the general challenge to my experience as a writer. This personal touch makes the ideas intriguing, and they do not feel like general tips. 

Another thing I liked is that the tool provided a suggestion on how to lead the reader towards taking an action, such as “Invite readers to share theirs too”. Because it assumes the goal of the newsletter is not just for people to read, but also to show engagement. 

Results from DeepSeek 

I liked DeepSeek’s way of framing the ideas. From the copywriting point of view, the phrasing of most ideas has a specific emotional effect, and mentions the pain points “explicitly”. 

Unlike ChatGPT, DeepSeek is more direct about the practical takeaway of the idea, and explanations on application seem more actionable to me. 

• Winner: ChatGPT

Though I requested not to share any clichéd ideas, I did not specify what a cliché sounds like to me. So, both ChatGPT and DeepSeek shared ideas concerning the main challenges everyone speaks about. That is why none exactly excelled in this regard. 

However, I prefer ChatGPT as it was able to read between the lines of what I was looking for. 

Task 2: Reasoning and logic 

Both ChatGPT and DeepSeek currently offer a separate reasoning functionality. These are called Reason for ChatGPT and DeepThink in the case of DeepSeek. Yet, it does NOT mean that the model stops reasoning” when this functionality is off. 

The difference is that we can see the chain-of-thought prompting process. The Large Language Model (LLM) breaks down the steps and reveals what it considers before providing the final response. So, I inserted the next question while this functionality was on. 

The task for this time was answering the question “Why does the temperature on Earth continue to rise?”. 

Results from ChatGPT  

ChatGPT provided the answer to a “why” question in a matter of 3-4 seconds. When the Reason functionality was off, the chatbot just listed a few common reasons. Yet, the key difference for my specific case is that ChatGPT started with what each term means (Greenhouse effect, Deforestation, etc.) before going deeper into those reasons. 

Unlike DeepSeek, it had a more comprehensive summary of the key points covered. 

Results from DeepSeek 

DeepSeek thought for a whole 39 seconds. Yet, there was not much difference between having DeepThink on or off. The key advantage is that the bot analyzes the task and “thinks” about how it should enrich the content, such as using specific examples, which angle to emphasize more, etc. 

• Winner: DeepSeek 

It takes DeepSeek much longer to generate the response. However, the process is very transparent. ChatGPT focused more on listing all the possible reasons and explaining the causal relationship of those. 

On the other hand, DeepSeek focused on providing data in numbers and included comparisons between how things once were versus how they progress these days. It also classified the reasons between human-caused and natural causes, linking the influence. So to speak, the waiting was worth it. 

Task 3: Structuring the content

To test how ChatGPT and DeepSeek present and structure the responses, I asked to generate an article outline for an audience I described.  To keep it fair, I did not provide specifications on how I want the models to phrase titles or any outlining principles. 

Results from ChatGPT 

When asked to structure the content, ChatGPT is more likely to keep the headings within the scope of your topic. Because it is typical of DeepSeek to go really deep into the topic and structure it from angles that do not entirely reflect the intent of the searcher. 

Results from DeepSeek 

Unlike ChatGPT, DeepSeek also suggested a title for the article. However, the criteria the tool chose to organize subheadlines did not match the main title. 

What I like is that DeepSeek is usually more specific when it suggests bullet points to support the main idea. 

• Winner: DeepSeek

When it comes to structure, DeepSeek is more comprehensive and practical. Especially when you clarify principles to outline the content. So, there are more ideas to pick from and include in your structure if necessary. Yet, ChatGPT takes a more creative approach when it comes to content that is a “non-listicle” format. 

So, my recommendation would be to structure with DeepSeek if you want to list something. And generate with ChatGPT when you want to structure a topic from one angle, yet stay comprehensive. 

Task 4: Information accuracy 

One thing that keeps annoying me when using LLMs is that they sometimes tend to fabricate anything for which there is no specific answer. And right after clarification, you see the apology reply with another misleading piece of information. 

So, which model should we use for accurate research? 

Results from ChatGPT 

If we speak of the accuracy in terms of content research, ChatGPT has a slight advantage. When you ask a challenging question with no definite answer, ChatGPT tries to come up with a response that would feel safe to the majority and feels more or less logical.  

The real problem is that it can dodge the answer by providing false information. You can ask for sources as confirmation, and it can trick you into sources where there is no mention of whatever it generated. 

Such cases do not happen as frequently when you turn on the Search functionality. 

Results from DeepSeek 

In terms of mathematical accuracy, DeepSeek tends to perform better. There is a belief that DeepSeek-V3 is optimized for mathematical and programming tasks. But in general and more philosophical contexts, DeepSeek often fabricates the information. 

• Winner: ChatGPT

I usually turn to other LLMs to find sources for any content, as ChatGPT and DeepSeek fabricate more often. 

Yet, if I compare the cases when I received accurate sources just the way I requested, ChatGPT provided more useful results than DeepSeek. 

In the examples above, I asked to provide names of coaches who currently sell bundle offers, not standalone ones. With the same prompt, ChatGPT led me to the pages where the coaches present the bundle. 

On the other hand, DeepSeek only shared the names of popular coaches and creators. Yes, there is a chance these people had bundle offers at some point. But the whole idea behind my prompt was to find coaches who currently sell in bundles. 

Task 5: Creativity 

If you consider ChatGPT and DeepSeek for creative writing, you would notice that the former is more likely to consider the context. 

In the charts Artificial Analysis provides, ChatGPT’s context window is broader with the models o1 and o-3 mini. Yet, if we compare the GPT-4o-mini with Deepseek R1, the results are the same. 

Let’s discuss the differences with another task example. 

I shared an abstract line for both models to develop a story around it, which went like “The moon disappeared last night, and nobody noticed, except me.” The prompt only specified the technical aspect for writing, and I included no specifications on the direction I wanted the plot to go. 

Results from ChatGPT 

For stories and other types of creative writing, ChatGPT usually takes a specific direction and tries to create something substantial from an abstract idea. For example,

“A faint shimmer, like a bubble hanging in the sky. Invisible to the world, but there. I reached out on instinct. My fingers grazed cold nothingness—and yet, something pushed back. A pulse.”

Results from DeepSeek 

When you give an abstract idea for DeepSeek, in most cases, it keeps the ending vague. Sentences feel more repetitive and chaotic, which do not add value to the plot you want to develop. Unless you provide instructions, it just develops dramatic beats and does not expand the idea you suggest. For example, 

“The moon didn’t just vanish. It was stolen. And I’m the only one who remembers it ever existed.

Now, the whispers are louder. They’re coming.

And when they take me, will anyone notice?”

• Winner: ChatGPT 

If you want to develop ideas, ChatGPT takes a more explorative approach. DeepSeek, on the other hand, is more reactive. So, ChatGPT is conceptually deeper, more layered, and more nuanced in how everything evolves. 

Task 6: Personalizing the tone 

Both ChatGPT and DeepSeek stick to the tone you set for them to write. The question is for how long? 

If you do not use the paid version of ChatGPT, it sometimes loses its tone and style after changing the model. And the same is true for DeepSeek. 

Yet, the way ChatGPT writes feels more natural, conversational, and contextual. I had no clear winner when it came to matching the tone. Yet, what I noticed was that

ChatGPT

• Excels at mimicking literary tone and pacing.
• Maintains emotional atmosphere and subtle voice cues well.

DeepSeek

• Is more literal or direct even if you specify the tone
• Struggle with literary subtlety

Who said we cannot use both? 

In this article, we tested ChatGPT and DeepSeek across various content tasks. And as you can see, the better one depends on the nature of the task. 

If your goal is to create emotionally engaging and well-structured content, ChatGPT consistently comes out ahead. It reads between the lines, understands nuance, and adds contextual depth in tasks when you are brainstorming, storytelling, or trying to get the tone right.

DeepSeek, on the other hand, excels in analytical tasks, structured lists, and fact-heavy content, especially when you give it specific instructions.

But instead of picking one tool for content creation, it is always better to know which one to turn to at the right time. After all, you are the writer, and these tools are only as good as the prompts you give them.