What is DeepSeek? DeepSeek is a Chinese AI assistant developed by DeepSeek AI, a company based in Hangzhou and owned by the hedge fund High-Flyer. The system offers features similar to ChatGPT, is free to use and drew worldwide attention in early 2025 for its rapid adoption and low development costs. The current model generation is DeepSeek V4, released on 24 April 2026 as the successor to the earlier breakthrough model R1; since 10 September 2026, DeepSeek V4.1-Flash has been the newest model.
What is DeepSeek exactly?
DeepSeek is a large language model that generates text, answers questions, writes code and analyses complex problems. The system was developed as an open-source alternative to closed models such as ChatGPT and Claude, which means the underlying model weights are publicly available.
The company DeepSeek AI was founded in July 2023 by Liang Wenfeng. Its breakthrough with the general public came in January 2025 with the launch of DeepSeek-R1, a model whose benchmark performance was comparable to the o1 model from OpenAI. That DeepSeek achieved this with considerably less computing power drew attention across the international AI sector.
DeepSeek is available as a web application, as a mobile app and via an API for developers. The basic version is free to use without a subscription, which makes it attractive for professionals who want to experiment with AI without upfront costs.
What is DeepSeek R1?
DeepSeek R1 was the reasoning model with which DeepSeek broke through in January 2025, and it still forms the basis of how DeepSeek approaches reasoning. It differs from standard language models in that it reasons step by step before giving an answer. You can follow the reasoning steps: the model shows how it breaks a problem down, which alternative approaches it generates and where it corrects earlier steps.
DeepSeek V4 was released on 24 April 2026, in the variants V4 Pro (1.6 trillion parameters, 49 billion active) and the faster, cheaper V4 Flash. Both support a context window of 1 million tokens and can switch between a direct mode and an extended reasoning mode, which means V4 has in practice taken over the role of R1. On 10 September 2026 DeepSeek V4.1-Flash followed, replacing V4 Flash; V4 Pro remains available via the API. R1 is no longer the model you start with, and the old API names deepseek-chat and deepseek-reasoner were discontinued on 24 July 2026.
This makes the DeepSeek models particularly suitable for mathematical problems, logical reasoning and complex analysis tasks where the intermediate steps matter as much as the final answer. For business uses where transparency in the reasoning process is valuable, this sets them apart from more general-purpose models.
R1 uses a mixture-of-experts architecture: several specialised sub-models work together, and each task is routed to the most suitable sub-model. V4 builds on this with a more efficient attention architecture that keeps the large context window affordable. This raises efficiency, because the model’s full capacity does not have to be active for every question.
How does DeepSeek work technically?
DeepSeek uses a large language model as its basis, comparable to the architecture behind ChatGPT and Claude. The system analyses your input, recognises patterns based on training data and generates an answer token by token.
The technical difference lies in the training approach. DeepSeek claimed that the V3 model was trained for a fraction of the cost of comparable Western models, mainly through more efficient use of the available GPU capacity. Independent analyses put that claim into perspective: the amount quoted covered only the pre-training phase, not the full development costs. The efficiency gain over competitors is nonetheless real and relevant to the sector, and it continues in V4, which is considerably cheaper per token on the API than comparable Western models.
What can you do with DeepSeek?
You can use DeepSeek for a wide range of tasks: text generation, document analysis, programming support, research and mathematical problem-solving. Its features largely overlap with what you know from ChatGPT: you give an instruction in plain language and the system generates an answer. The difference between DeepSeek and ChatGPT lies mainly in where your data ends up.
One limitation is that DeepSeek cannot generate images. For visual content you need a different model. For purely text-based tasks it performs well compared with established alternatives, especially given that it is free to use.
DeepSeek works best for non-critical tasks: brainstorming, improving texts, supporting research and learning. For confidential business information there are reservations, explained in the privacy section below. For that reason, DeepSeek is also not included in the overview of the best AI for professional work.
What are the privacy risks of DeepSeek?
DeepSeek stores user data on servers in China. That means the data falls under Chinese law, which can give Chinese authorities access to business data from foreign users. For professionals who work with confidential client information, business strategies or personal data, this is a relevant risk.
DeepSeek also demonstrably censors politically sensitive topics. Questions about the student protests in Tiananmen Square are ignored or answered incorrectly. The model states that Taiwan is part of China. That ideological steering can affect the reliability of information in specific domains.
The practical guideline for professional use: do not enter confidential business information, personal data or client data into DeepSeek. The same caution applies, incidentally, to free versions of Western tools.
Is DeepSeek suitable for professional use?
For experiments, learning and non-sensitive tasks, DeepSeek is a useful option that costs nothing to access. That free access makes it easy to explore AI tools without paying for a subscription.
For professional use with confidential data, client information or business strategies, DeepSeek is less suitable because of its server location in China and the privacy legislation that comes with it. In those situations, Western alternatives with clearer privacy guarantees are the better choice. For professional use, the question of data policy matters more than for a consumer app, and decisions like this belong in an AI policy for your organisation, which sets out for each tool what is and is not allowed.
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Frequently asked questions about DeepSeek
Besides the privacy question, DeepSeek raises practical questions about running it yourself and about the service’s position in Europe.
Can you run DeepSeek locally?
Yes, you can run DeepSeek locally, because DeepSeek publishes the model weights on Hugging Face under the MIT licence. The model page for DeepSeek V4.1-Flash mentions vLLM and SGLang for running the model on your own servers, and Hugging Face shows quantised versions for Ollama and LM Studio. Your text then never goes to DeepSeek’s servers in China. With hundreds of billions of parameters, however, the model needs far more computing power and memory than an ordinary laptop has.
How much does the DeepSeek API cost?
The DeepSeek API is charged per million tokens, with separate rates for input and output, and the pricing page shows those amounts in dollars. Input that is already in the cache is cheaper than new input. Outside peak hours on weekdays, according to DeepSeek, you pay half the peak rate. The costs are deducted from a balance you top up in advance.
Is DeepSeek blocked anywhere in Europe?
Yes, DeepSeek is blocked in Italy: the Italian data protection authority, the Garante, on 30 January 2025 imposed a definitive restriction on the processing of personal data of users in Italy. The decision is addressed to the two Chinese companies behind the service, in Hangzhou and Beijing. A national decision like this only applies in the country of the authority that takes it.
