Just a few months after being launched, DeepSeek has claimed its place as a key player in the AI Large Language Model (LLM) landscape. And while it is still new in the field, it can refine your marketing tasks.
In this blog, we’ll explore everything a digital marketer needs to know about DeepSeek:
- What is DeepSeek
- The History of DeepSeek
- Technology Behind DeepSeek
- DeepSeek Usage Statistics
- DeepSeek Ranking vs. Other AI models
- Should You Use DeepSeek?
- DeepSeek Real-World Applications
- DeepSeek Use Cases for Marketing
- DeepSeek limitations
- DeepSeek FAQs
What is DeepSeek?
DeepSeek is an artificial intelligence company that develops various large language models trained for specific tasks such as software development, general reasoning, and real-time problem-solving.
The history of DeepSeek
Liang Wenfeng built DeepSeek out of his hedge fund-owned AI lab. Liang Wenfeng comes from a background in quantitative finance merged with AI.
Here is the timeline for how DeepSeek came to be:
Since its inception, DeepSeek has released eight models, trained on different data subsets, and has released two main variants, Base and Chat. These are all under the MIT open-source license. For image generation, they have launched Janus-Pro-7B.
If you’re using DeepSeek V3.0 for web development or game development, the new version will deliver better web page design and front-end design for games. Function calls are also more accurate.
DeepSeek V3-0324 has also shown a marked improvement in benchmark performance. Its best performance jump is on AIME for math with a 19.8 increase, followed by a 10-point increase in LiveCode Bench all against Qwen, GPT-4.5, and Claude-Sonnet-3.7.
DeepSeek recommends users consider V3-0324 for non-complex reasoning tasks.
Technology behind DeepSeek
When DeepSeek was first released in the U.S. market, it shocked the AI industry with its unprecedented breakthrough in AI technology. DeepSeek R1-0 was trained solely on reinforcement learning with no supervised fine-tuning (SFT).
On top of reinforcement learning, DeepSeek was trained on older generation GPUs after the US sale ban of the latest GPUs to China. Based on their release paper, DeepSeek outlines the key learning techniques it used to train its models.
The key training techniques were:
Reinforcement learning
Before DeepSeek came into the picture, most of the leading LLMs were trained using supervised fine-tuning. This training meant the models were fed labeled datasets to learn from.
DeepSeek was incentivized to learn on its own and improve its reasoning skills through rewards. As training went on, the instinct to learn was more intrinsic than trainer- or dataset-defined.
Reward modeling
This feature incentivizes the model to learn which is the better output. Whichever output is given more rewards, that’s the one that wins — unreadable, incomprehensible, or confusing outputs receive penalties. The reasoning process used in the winning solution grows stronger through the testing.
Training template
For prompting, the model is instructed to solve prompt problems in a two-step process: think and answer. The model encloses their reasoning process in the think element before releasing their output in an answer element.
Distillation
To show DeepSeek’s capabilities, the researchers trained by using other open-source models such as Llama by Meta and Qewn by Alibaba, smaller families of open-sourced models. This process is where the DeepSeek researchers use SFT to show distillation of an LLM model to smaller models does work!
DeepSeek usage statistics
Since its release last January, users and companies have been curious about DeepSeek capabilities. Here are a few statistics that show its power and relevance:
- There were 1.53 million app downloads in the first 10 days of release in January 2025.
- There were 17.6 million app downloads in January 2025, second to the ChatGPT app.
- 25-34 year olds make up the majority of total downloads.
- There are 61.81 million App Monthly Average Users (MAU) as of February 2025.
- There are 15.22 million app downloads on the Google Play Store.
DeepSeek vs. other AI models
There are many benchmarks by which to judge DeepSeek against other LLMs in the market. For this section, we’re going to look at:
- DeepSeek’s training costs
- DeepSeek’s R1 reported research results
- Chatbot Arena results
- Humanity’s Last Exam
DeepSeek R1 vs. OpenAI GPT-4o: Training Cost
Comparing DeepSeek against other AI models, you can start with its training factors.
While DeepSeek engineers were able to train their model for much less than its main competitor, OpenAI, the training cost remained low due to its parent company’s prior hardware investments. The training cost also doesn’t include data acquisition, data cleaning, and processing fees, as well as staff salaries.
Meanwhile, their novel use of reinforcement learning instead of supervised fine-tuning makes it an LLM capable of improving on its own. It also demonstrated astounding numbers in terms of hardware spending.
Its input and output usage costs also make it attractive for enterprise customers.
Due to this, the premium model’s pricing is more competitive than GPT-4o.
DeepSeek-R1 test and results
When DeepSeek released its Base and Chat models along with their research results, the AI industry was shocked when they saw R1 performing better by a margin, if not beating, leading models such as Claude-3.5, GPT-4o, OpenAI o1-mini, and o1-1217 on various knowledge benchmarks.
They specifically beat the other models in terms of education-oriented and other intelligence benchmarks with the model’s ability to answer STEM questions.
Based on its FRAMES result which tests for document analysis ability, DeepSeek R1 has beaten Claude-3.5, GPT-4o, DeepSeek V3, and OpenAI o1-models.
While it still performs decently for fact-based queries for the SimpleQA benchmark, the information it provides can be limited.
Chatbot Arena results
UC Berkeley Skylab and LMArena developed Chatbot Arena, an open platform for AI benchmarking. They rank the best LLM and AI chatbots using the Bradley-Terry model.
Below are DeepSeek’s results with the Chatbot Arena ranking criteria.
Overall ranking
Chatbot Arena’s ranking methodology for overall ranking comes from crowdsourced ratings. Chatbot Arena’s process has users submit questions or prompts, compare and rate responses from two anonymized LLMs to limit biases. The ratings are then tallied and make up the leaderboard rankings.
The leaderboard rankings are updated weekly or bi-weekly, depending on data collection and analysis. Currently, DeepSeek-V3-0324 and DeepSeek-R1 are ranked fourth and fifth-best LLMs, respectively. Now, we’ll look at how DeepSeek compares against other LLMs in terms of language by tasks, language fluency, and web development.
Below, you will find how DeepSeek ranks against other LLMs based on how it performs in terms of:
These tasks are some of the most frequent use cases digital marketers have for LLMs like DeepSeek V3 and DeepSeek R1.
Language (by tasks)
Chatbot Arena has grouped task prompts into categories. The pie chart above shows the main categories users tested LLMs in–most tested them in terms of tech programming, puzzles & math, creative writing, and AI innovations.
DeepSeek-V3 ranks first for coding and multi-turn. DeepSeek-V3 also ranks second, along with R1, for hard prompts with style control and math.
DeepSeek V3 has beaten R1 in producing creative writing outputs, longer query, hard prompts, and overall ranking.
Language (by language fluency)
In terms of language fluency, DeepSeek-V3 ranks first in two languages–German and French.
Meanwhile, R1 only shares the top spot for French, but ranks second for Spanish and Korean.
However, both models need work in English. Overall, V3 is more fluent in languages than R1.
Web development
Chatbot Arena’s topic clustering shows in which web development areas users tested LLMs. Most of the prompts tested LLMs in website design, game development, and clone development.
DeepSeek R1 beats most LLMs, even OpenAI’s o3, when it comes to web development. This means the model can produce good-quality code against fellow LLMs.
Humanity’s Last Exam
If the Turing test had a computer make humans believe they were talking to another human instead of a computer, Humanity’s Last Exam (HLE) is a test of whether the best LLMs out there are capable of solving humanity’s hardest academic problems.
HLE is a set of advanced problems that the best and brightest minds can expect on a doctorate level. The questions have been fed first to leading LLM models.
If the question was unanswerable, it was then vetted, refined, and answered by human reviewers — meaning it’s answerable by human beings.
However, that’s not the present case with major LLMs. Based on the latest HLE results, while R1 has managed a high accuracy (on a text-only subset), its calibration error, or confidence level, about the correctness of its answer is the lowest among the other models.
Should you use DeepSeek?
Yes, DeepSeek can be a helpful tool for marketing and research that anyone can use. However, remember that any prompt and output may be used as part of its training data.
To learn more, let’s look at these usage factors:
Accuracy
Based on the benchmarks DeepSeek has passed, it is capable of aiding your marketing projects. If it will be used for hard prompts with style control, then DeepSeek can help with content ideation, brainstorming, chatting, and answering questions.
Ease of access
Through DeepSeek’s API, marketing developers can easily integrate it into the applications and platforms they handle. After integration, a marketer can use DeepSeek capabilities to create chatbots and recommendation engines.
Its Janus Pro 7 can also be used to generate images for marketing campaign assets.
Cloud services providers NxtGen and Microsoft Azure already offer DeepSeek R1.
Cost vs. value
Being an open-source tool released under MIT license, DeepSeek is simply unbeatable when it comes to cost.
Input Cost
In terms of cost, DeepSeek is currently positioned in the middle of the market, with input costs as low as $0.55 and $0.27 for DeepSeek R1 and V3, respectively.
Output Cost
The same goes for their output cost, with $2.19 for DeepSeek R1 and $1.10 for V3.
DeepSeek real-world applications: Who uses DeepSeek?
Since its launch, DeepSeek has shown its effectiveness in a wide range of real-world applications. Who uses DeepSeek today? And for what purpose? Here are some high-profile users and where the technology has been applied to:
Government
Though largely local Chinese governments in Shenzhen and Kunshan, DeepSeek, being fluent in Mandarin, has helped government workers draft and proofread their documents, sometimes as many as 1,000 characters, in just a few seconds. It has also helped authorities locate missing people.
Industry partnership
Microsoft, despite being a major investor in OpenAI, quickly embraced the arrival of DeepSeek and offered it on Azure. This allows software developers, especially marketing developers, to easily integrate and develop AI apps for their marketing tasks.
DeepSeek is also available for installation on NxtGen, AWS, and Nvidia AI platforms.
Car manufacturers
Chinese car manufacturers such as BYD, Geely, and Great Wall have announced they have installed DeepSeek. BYD has reported it will use DeepSeek’s “God’s eye” capabilities to boost its cars’ self-driving technology.
Meanwhile, SAIC-GM will also integrate it into its Buick and Cadillac cars.
Telecommunications
Telco companies such as China Mobile and China Telecom are also eager to onboard DeepSeek.
Search engine
Like its Western counterparts Google & Bing, Baidu has integrated and harnessed DeepSeek’s AI technology to help with search and cloud services. DeepSeek now helps refine search result relevance and improve understanding of users’ natural language. This makes search results address the search intent better and aids chatbots in providing more accurate replies.
Gaming industry
NetEase has integrated DeepSeek to provide better-crafted non-player characters (NPCs). AI also helps in updating storylines in real time to give a player a personalized playing experience. This makes gaming a truly unique experience for every single player.
Chatbots
DeepSeek AI will be available for integration into Meta’s WhatsApp worldwide. One can add DeepSeek as a contact with the following phone number: +34 613 333 330. Despite using a Spanish country code, this number can be used globally.
After adding, you can start asking or prompting DeepSeek on WhatsApp, given you’ve allowed contact sharing. You can also forward WhatsApp messages to DeepSeek via a third-party automation platform for analysis and response automation. It can also be integrated with Telegram through its GPTBots agent.
DeepSeek use cases for marketing
Want to know how to use DeepSeek for marketing tasks? Here are some of the top DeepSeek use cases for marketing:
1. Content creation
Using its Mixture of Expertise training dataset and passing multiple academic benchmarks, it is not far-fetched to say DeepSeek can be an expert in your industry and sector. R1 can generate marketing content like blog posts, social media content, or email copy in seconds.
Case in point, Chinese government workers let DeepSeek draft and proofread their work with over a thousand characters in under a minute.
2. Customer support via chatbots
R1 and V3-0324 rank 2nd in hard prompts with style control which shows their capability to accurate answers. The DeepSeek Chat model is purposefully built to provide any business with a chatbot whose reasoning capabilities just get better with every customer it serves. Its natural language processing also helps it adapt its tone and voice to sound more like a human.
3. Personalized marketing
As 42% of marketing professionals trust AI to personalize content and offers in real time, DeepSeek has the capability for it. Given R1’s reinforcement learning technique, it is intrinsically incentivized to learn and build better reasoning and outputs. R1 can analyze customer data and create highly personalized marketing messages.
If it can change NPC actions and game narrative in real time based on player input, then it follows it can also track a customer, their decisions, and pathways, and devise a way to move them further down the funnel to achieve a conversion.
4. SEO and keyword research
There is a reason Baidu was quick to trust DeepSeek in helping address user intent. DeepSeek’s ability to understand the nuances of every search helps it faster categorize which results resonate with the searcher’s goal. It can also detect patterns in how search engines are ranking their results and help marketers refine their pages to gain better search rankings through AI SEO.
5. Market research and sentiment analysis
Similar to leading LLMs Grok and o1 models, DeepSeek can generate synthetic respondents, helping marketers do deeper market research testing faster.
If it is trained on your historical data, it can also perform predictive analysis to provide future scenarios.
Real-time monitoring of customer sentiments can also help your business be more agile in responding to market trends and customer issues.
6. Web development
DeepSeek has proven itself strong in web development. This can be cost-effective in terms of time and effort when developing landing pages, microsites, or other temporary web assets.
7. Product launches
Based on your historical marketing data, DeepSeek can identify product strategies and optimal timings for product launches. DeepSeek can notice gaps in the market and help marketers on how to address the gap with their product. It can also provide powerful insights on when and how to launch your product.
DeepSeek Limitations
Powerful as it may be, DeepSeek R-1 and V3-0324 have computing limitations just like any other LLM out there. These include, but are not limited to:
Language mixing
Currently, DeepSeek R-1 remains one of the few LLMs out there trained in different languages. And while it ranks first in foreign languages like French, it still needs work on its English output.
There have also been instances where R1 mixes languages—reasoning, and answering in English even when queried using a different language.
Prompt structure
Prompting is key to maximizing an LLM’s reasoning capabilities. And for R1 and V3.0324, researchers found that short prompts tend to make DeepSeek deliver low-quality outputs in the long run. They recommend users employ a clear statement of the problem and specify the output result format when prompting for better results.
AI biases
Just like other LLMs, DeepSeek is also prone to AI biases. Any LLM output will always depend on the quality of its training dataset. And even with DeepSeek’s powerful reasoning capabilities, it still has things it cannot answer because it is beyond its scope.
Censorship
Since its release, DeepSeek has been criticized for censorship or answering some questions critical of the Chinese government, and its actions are beyond its scope.
Aside from strong censorship, governments have also raised concerns about its threat to data privacy. In response, the U.S. Congress has filed a bipartisan bill to ban its use on government-issued devices. States like New York, Texas, and Virginia have also banned it.
Idiot-savant: DeepSeek and other LLMs
If there’s one thing that can relieve human anxiety about DeepSeek and most leading LLMs, it is that these models can still be considered idiot-savants.
They may show computing prowess in answering high-level questions in STEM, software engineering, language, and philosophical queries, but they still stumble upon basic arithmetic and obvious questions that a human with average intelligence can answer.
The dataset largely limits their world knowledge. Sometimes, when prompted with a difficult question, they lack guardrails of knowing when to confess they don’t know the answer and hallucinate instead. It may sound correct, but it can turn out completely wrong.
FAQs about DeepSeek for marketing
Here are frequently asked questions about DeepSeek.
What makes DeepSeek different from other AI models?
DeepSeek’s training techniques, reinforcement learning, and distillation make it a sustainable large language model that learns on its own. Its reported training costs, hardware, usage cost, and open-source license also make it a unique option from other AI models in the AI industry.
Can DeepSeek be used for content creation?
Yes, DeepSeek R1 can be used for content creation, ideation, drafts, and even proofreading.
Is DeepSeek easy to integrate with existing marketing tools?
Yes, DeepSeek is easy to integrate with existing marketing tools, especially when top cloud services like Microsoft Azure, and AWS offer it as a more affordable solution for marketing developers.
How accurate is DeepSeek for market research and sentiment analysis?
DeepSeek V3.0’s accuracy rate in detecting emotions ranges from 52%-92%. DeepSeek V3.0 was great at detecting emotions such as irony and emotion but needs work when it comes to sensing hatefulness and sentiment analysis (i.e., assigning a statement as positive, negative, or neutral).
Is DeepSeek suitable for small businesses or only for large enterprises?
Governments and businesses of all sizes — like large corporations, joint ventures, midsized businesses, and startups — benefit from DeepSeek’s groundbreaking AI technology. Its cost-effectiveness, reinforcement learning technique, and Mixture-of-Expertise foundational training make it adept at adapting to whichever industry, sector, or market size any business has.
What are some limitations of using DeepSeek for marketing?
DeepSeek is prone to language-mixing in its response, and output quality depends on good prompt structure. Government bans may also prevent companies from integrating DeepSeek into their platforms.
DeepSeek: Use With Caution
Even if they are new entrants to the LLM market, and despite using an older generation of GPUs, DeepSeek-R1 and V3-0324 have proven their AI capabilities. DeepSeek is continuously improving as it uses reinforcement learning and novel credit assigning to produce the best outputs.
As more marketing professionals elect to use more AI, DeepSeek marketing use cases have shown promise with its personalization, customer support, market research, synthetic respondent testing, and web development capabilities.
As a digital marketer, analyze your marketing needs against DeepSeek’s capabilities to decide whether DeepSeek is the AI tool for you. If you want to chat about using AI for your business, feel free to contact us online!
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Cat is an experienced digital marketer and SEO specialist who likes to hoard words like a dragon guarding its gold. Her Mount Rushmore of writers are Jane Austen, Gabriel Garcia Marquez, Terry Pratchett, and Haruki Murakami. For her, the best things in life are coffee, cats, and conversations until the cows come home. -
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