DeepSeek vs ChatGPT: A Comprehensive Comparison

DeepSeek has recently taken social media by storm, sparking curiosity and debate. Many are eager to find out whether this AI from a Chinese startup truly lives up to its reputation—even challenging ChatGPT, the long-standing leader in the field. Today, we’ll dive into the key differences between DeepSeek and ChatGPT, shedding light on what sets DeepSeek apart.

Development of DeepSeek and ChatGPT

DeepSeek is a Chinese AI startup founded in 2023, focused on developing efficient and low-cost large language models. Utilizing an innovative Mixture-of-Experts (MoE) architecture, DeepSeek provides outstanding AI services across various domains. Its first model, DeepSeek-R1, was released in January 2025, followed by DeepSeek-V3, which excels in natural language processing, mathematical reasoning, and code generation. The training cost of DeepSeek-V3 is approximately $6 million, significantly lower than other large models.

ChatGPT, developed by the U.S. company OpenAI, is a conversational system based on the GPT (Generative Pre-trained Transformer) architecture. Since its release in 2022, ChatGPT has rapidly gained popularity and become a global tool. The GPT-4 model of ChatGPT excels in language understanding and creative generation. Its training costs are relatively high, with GPT-3 costing around $1.4 million and GPT-4 ranging from $2 million to $12 million. Additionally, ChatGPT’s annual operational cost in 2023 was about $475 million.

DeepSeek vs ChatGPT: Core Technical Comparison

DeepSeek and ChatGPT differ significantly in terms of their technical capabilities, resulting in distinct user experiences.

Model Architecture & Efficiency

DeepSeek uses a Mixture-of-Experts (MoE) architecture, where only a subset of specialized experts is activated for each task, making it more efficient in terms of computational resources and cost. It activates fewer parameters (about 37 billion out of 671 billion) for each query, resulting in lower energy usage. However, this type of model means that DeepSeek may not be as flexible or stable as ChatGPT when handling very complex or cross-domain tasks.

In contrast, ChatGPT uses a transformer architecture where the entire model is activated for every task, ensuring consistent performance but with higher resource consumption and operational costs. This makes ChatGPT less efficient compared to DeepSeek, especially for tasks that don’t require the full power of the model.

Coding, Math, and Reasoning Capabilities

Compared to ChatGPT, DeepSeek gives you a more accurate and direct answer in technical tasks.

With the MoE architecture and large data train, DeepSeek is highly specialized in coding, math, and reasoning. In coding, DeepSeek is pre-trained on 2 Trillion tokens in more than 80 programming languages, including Python, Java, C++, etc. This enormous training pool helps DeepSeek gain higher accuracy than ChatGPT.

On the other hand, ChatGPT is a versatile AI with strong general-purpose capabilities. It can be considered as a teacher who tries to make you learn about the principal. While it can finally give you an accurate answer, you might think it talks too much.

Language Generation & Multimodal Abilities

Both DeepSeek and ChatGPT are good at writing. However, DeepSeek is slower than ChatGPT in answering. I give the same prompt to DeepSeek R1 and ChatGPT 4o, and 4o responds in 1 second while R1 thinks for about a half minute. Meanwhile, ChatGPT doesn’t finish the story at once; it will ask you what the end you want. But both the R1 and 4o models’ stories are good.

As for multimodal abilities, DeepSeek can only analyze an image and text file. However, it doesn’t support creating images. While ChatGPT can analyze and create audio, images, and texts.

DeepSeek vs ChatGPT: Pricing & Free Access

According to DeepSeek’s official news, its 6 small models are open-source and free. Users can experience them on Chat.DeepSeek.com and its app version.

ChatGPT, accessible via web UI and API, offers a free version suitable for everyday use. The ChatGPT Plus version costs $20 per month, unlocking GPT-4 for faster performance and more capabilities. The Pro version is $200 per month, providing even more advanced features. While the free version is sufficient for basic tasks, the paid versions offer more efficient and professional tools, especially for complex tasks and creative needs.

Related: Gemini vs ChatGPT: Which One Is Better?

DeepSeek vs ChatGPT: Final Verdict

Is DeepSeek better than ChatGPT? For now, DeepSeek still has some ground to cover before fully catching up with ChatGPT. However, it has proven to be highly capable in technical fields, as reflected in its global user base and reviews.

Both DeepSeek and ChatGPT are widely recognized AI tools that have garnered significant attention. DeepSeek, being open-source and free, is especially popular among developers and researchers in China. It excels in specialized fields such as finance and biomedical research, often surpassing ChatGPT in accuracy. However, concerns about data security and privacy, particularly when handling sensitive information, remain a topic of discussion.

On the other hand, ChatGPT has built a strong global presence thanks to its ability to generate smooth, natural conversations. It performs exceptionally well in general tasks and everyday interactions but may not be as precise as DeepSeek in highly technical areas.

Community discussions, particularly on Reddit, highlight this divide—while the majority of users still favor ChatGPT for its versatility and ease of use, some technical users find DeepSeek better suited to their specific needs.

DeepSeek vs OpenAI

DeepSeek announces its latest R1 model is rivaling OpenAI o1, the latest model of OpenAI. And it puts a chart to explain. The chart compares the performance of different AI models, like DeepSeek-R1, DeepSeek-V3, and OpenAI-o1-mini, on various tasks. It shows how well each model performs on different types of challenges, such as solving math problems, programming, answering difficult questions, and multitasking.

The results show that DeepSeek models, especially DeepSeek-R1, usually do better than OpenAI models, particularly when the tasks are complex or require specialized knowledge, like solving advanced math problems or handling technical issues. However, OpenAI models still perform well on simpler tasks and are great for everyday use, such as having general conversations.

This means if you need an AI for tough tasks like coding or math, DeepSeek is a better choice. But for basic tasks or casual conversations, OpenAI models are a good option.

However, everyone has a different user experience. You can use both and then get your own conclusion.