What is DeepSeek? Breaking Down the AI That Caught Everyone’s Attention

DeepSeek R1 — if you’ve kept up with AI news, or just any news in general, there’s a good chance you’ve been hearing about it the past few days.

The AI app claims to rival the likes of OpenAI and Nvidia — claims that have caught the attention of AI enthusiasts. As a result, DeepSeek R1 has quickly climbed up the charts to become the most downloaded free app on Apple’s App Store and Google Play Store in the United States. Plus, it’s also one topic EVERYONE seems to talk about nowadays. 

But what is DeepSeek and why exactly is it making headlines? If you’re looking for answers, continue reading. We’ve discussed all about DeepSeek, what makes it special, and whether it’s worth a try.

Let’s dive right in.

What is DeepSeek?

DeepSeek AI is a Chinese artificial intelligence company that was founded in 2023 by Liang Wenfeng. Even though the company is fairly young, it has researched and developed many versions of its AI model over the past couple of years. 

Two of them, DeepSeek R1 and earlier, DeepSeek V3, have brought the company to the limelight for achieving high accuracy parameters at relatively lower costs. 

What is DeepSeek R1?

DeepSeek R1 is a new large language model (LLM) that’s designed for logical and reasoning tasks. It’s open-source and has a conversational chat interface like any other AI tool. 

This AI model in itself, has two versions, DeepSeek R1 and DeepSeek R1 Zero. The former was launched on 20th January 2025 and is accessible on the web. It is also available in the model catalogs in Azure AI Foundry and GitHub.

DeepSeek R1 Zero, on the other hand, has shown impressive results in terms of accuracy and performance for mathematical and reasoning use cases. However, it is not yet released for users.

Despite being one of the many companies that trained AI models in the past couple of years, DeepSeek is one of the very few that managed to get international attention. But exactly what separates DeepSeek R1 from other AI models? Why is it special? Let’s find out.

DeepSeek R1: What Made It the Talk of the Town?

At first glance, DeepSeek R1 doesn’t look too different from other AI models we know. After all, it can understand conversational commands and give outputs in natural language — and it’s pretty good at that.

However, that’s not what makes DeepSeek R1 different. What’s caused the buzz in AI communities is the cost in which it was trained, the results it has achieved, and the transparency of the training data.

DeepSeek R1 is extremely cost-effective

DeepSeek claims to have trained the AI model, DeepSeek R1, for just $5.6 million — which is extremely low in comparison to the billions other AI giants have been spending over the past few years.

OpenAI, in contrast, spent $5 billion in the past year alone. The training cost of Google Gemini, too, was estimated at $191 million in 2023 and OpenAI’s GPT-4 training costs were estimated at around $78 million.

Why does it matter?

The cost of training DeepSeek R1 may not affect the end user since the model is free to use. However, it means a lot for sustainability and ethics.

The AI industry is extremely expensive in terms of energy and resource consumption. A lower cost of training means lower consumption of resources, which makes DeepSeek’s feat a new hope for sustainable AI. 

And even though experts estimate that DeepSeek might have spent more than the $5.6 million that they claim, the cost will still be nowhere close to what global AI giants are currently spending.

DeepSeek R1 matches other AI models in accuracy and performance

Despite being developed with a significantly lower budget, DeepSeek R1 has proven itself capable of competing with the most advanced AI models available today in terms of accuracy and performance.

Check this detailed comparison released by DeepSeek:

Image Source

According to these benchmark tests, DeepSeek R1 performs at par with OpenAI’s GPT-4 and Google’s Gemini when evaluated on tasks such as logical inference, multilingual comprehension, and real-world reasoning.

Why does it matter?

Accuracy is a critical factor in determining the reliability of AI models. 

Consider this. You ask an AI model “What is 2+2?” and it says 5. No matter how quick the model is or how much it costs to train it, if the end result is inaccurate, your purpose of using the AI model fails. 

Many industry experts believed that DeepSeek’s lower training costs would compromise its effectiveness, but the model’s results tell a different story.

This balance between accuracy and resource efficiency positions DeepSeek as a game-changing alternative to costly models, proving that impactful AI doesn’t always require billions in investment.

DeepSeek is transparent with its training data

Along with the release of R1, the parent company also released research papers related to the training of the AI model. Apart from the usual training methods and evaluation criteria, this paper also highlighted the failures of their training methods.

This is quite rare in the AI industry, where competitors try keeping their training data and development strategies closely guarded. DeepSeek, unlike others, has been quite open about the challenges and limitations they faced, including biases and failure cases observed during testing.

Why does it matter?

DeepSeek’s transparency allows researchers, developers, and even competitors to understand both the strengths and limitations of the R1 model and also the usual training approaches. 

This training data can be key to speedy AI developments in various fields. Plus, it has also earned DeepSeek a reputation for building an environment of trust and collaboration.

These three factors have made DeepSeek stand out among the rest. But let’s be practical. As an end user, you’d rarely focus on the research data and training costs. What matters more is DeepSeek R1’s features and drawbacks, which we’ll discuss now.

DeepSeek R1 Features

Here are some features of DeepSeek R1:

Conversational intelligence

DeepSeek R1 is an AI model powered by machine learning and natural language processing (NLP). That means, it understands, accepts commands, and gives outputs in human language, like many other AI apps (think ChatGPT and ChatSonic). 

That also means it has many of the basic features, like answering queries, scanning documents, providing multilingual support, and so on.

Math, Logic, and Problem Solving Skills

One of R1’s most impressive features is that it’s specially trained to perform complex logical reasoning tasks. The benchmarks we discussed earlier alongside leading AI models also demonstrate its strengths in problem-solving and analytical reasoning.

Check how DeepSeek answered one of our queries:

This makes it ideal for industries like legal tech, data analysis, and financial advisory services. It is quite effective in interpreting complex queries where step-by-step reasoning is critical for accurate answers.

Open-Source Availability

DeepSeek R1 is one of the LLM’s that are open-source. That means developers are free to use this LLM to power their own AI apps and tools. 

How does that help? Here’s how:

1. Customization: Developers can fine-tune R1 for specific applications, potentially enhancing its performance in niche areas, like education or scientific research.
2. Transparency: The ability to examine the model’s inner workings fosters trust and allows for a better understanding of its decision-making processes.
3. Community-driven improvement: With many minds working on the model, bugs can be identified and fixed more quickly, giving you access to new and safe features.

The open-source approach also aligns with growing calls for ethical AI development, as it allows for greater scrutiny and accountability in how AI models are built and deployed.

High Accuracy for Complex Tasks

One of the main reasons to use DeepSeek R1 is its accuracy. As explained by DeepSeek, several studies have placed R1 on par with OpenAI’s o-1 and o-1 mini. This high accuracy combined with its use case of solving complex problems means you get a high-performance AI model for specialized applications.

It even answers the famous “STRAWBERRY” query correctly:

While DeepSeek R1 is all the buzz currently, it’s not without drawbacks and errors. Let’s discuss some of them here.

DeepSeek R1 Drawbacks

While R1 has many impressive features, it’s important to consider some potential drawbacks:

Privacy Concerns

As DeepSeek is a newer company, people are skeptical about trusting the AI model with their data. Many users and experts are citing data privacy concerns, with larger companies and enterprises still wary of using the LLM.

Despite DeepSeek’s claims of robust data security measures, users may still be concerned about how their data is stored, used, and potentially shared. The absence of clear and comprehensive data handling policies could lead to trust issues, particularly in regions with strict data privacy regulations, such as the European Union’s GDPR.

In fact, it’s already under scrutiny in the EU and is restricted by several companies and government agencies.

Lack of Integrated Web Search

DeepSeek R1 doesn’t have web search integrated but has a separate option for it. While most AI models search the web on their own, DeepSeek R1 relies on the user to choose the web search option.

Without the web search option switched on, the AI model can only access its dated knowledge base. Here’s an example:

For updates on real-time data, you need to click on the “Search” option in the chatbox:

How Does DeepSeek R1 Compare to ChatGPT?

When comparing DeepSeek R1 to ChatGPT, it’s important to note that we’re looking at a snapshot in time. AI models are constantly evolving, and both systems have their strengths.

R1 shares some similarities with early versions of ChatGPT, particularly in terms of general language understanding and generation capabilities. However, R1 boasts a larger context window and higher maximum output, potentially giving it an edge in handling longer, more complex tasks.

ChatGPT’s current version, on the other hand, has better features than the brand new DeepSeek R1. It has integrated web search and content generation capabilities — areas where DeepSeek R1 falls behind.

However, both tools have their own strengths. While ChatGPT is great as a general-purpose AI chatbot, DeepSeek R1 is better for solving logic and math problems.

Final Thoughts: Is DeepSeek R1 Worth a Try?

The question of whether DeepSeek R1 is worth trying depends largely on your specific needs and concerns. 

DeepSeek R1 is excellent at solving complex queries which require multiple steps of “thinking.” It can solve math problems, answer logic puzzles, and also answer general queries from its database — always returning highly accurate answers.

Apart from the data privacy concerns, DeepSeek R1 is worth a try if you’re looking for an AI tool for problem-solving or academic use cases at present.

However, if you’re looking for an AI platform for other use cases like content creation, real-time web search, or marketing research, consider other tools built for those use cases, like Chatsonic.

Want to know more about DeepSeek R1? Stay tuned to Writesonic’s blog for more updates. 

Meanwhile, discover how AI can transform your marketing process. Try Chatsonic today!

Niyati Mahale

Niyati Mahale is a Content Writer @Writesonic. She specializes in artificial intelligence and B2B, with a flair for combining effective storytelling and SEO best practices to create impactful content.