DeepSeek
DeepSeek is an AI model family from China that became known above all for capable, cost-efficient language models. The line's reasoning models in particular, DeepSeek R1 for instance, have drawn attention, because they think complex tasks through step by step while being comparatively cheap to train and run. Several DeepSeek models have been published as open source, so they can in principle be self-hosted too. For companies, DeepSeek is therefore an example of how strong AI capability and cost awareness can be combined.
Also known as: DeepSeek AI, DeepSeek R1, DeepSeek models
What is DeepSeek?
DeepSeek denotes a family of large language models developed by an AI company from China. The name stands both for the company and for the various model variants published over time. DeepSeek became known above all through models concentrating on solving demanding tasks step by step, that is, on reasoning.
Unlike purely proprietary providers, DeepSeek has made part of its models openly available. That means the model weights can be downloaded and, under certain conditions, reused. DeepSeek thus joins the movement around Open-source LLM , without all components or training data being fully disclosed.
For context it is important that model versions, licences and availability change regularly. We therefore describe DeepSeek deliberately in general terms and recommend always checking the provider's current information before production use.
Reasoning models and cost efficiency
A central feature of DeepSeek is its reasoning models, designed for multi-step thinking tasks. Rather than giving an answer straight away, such models work through intermediate steps of thought, which makes them interesting for mathematics, logic, writing code and complex analysis. DeepSeek R1 is the best-known example within the family.
DeepSeek also received much attention for the claim that such capability can be reached with comparatively modest resources. Specific figures vary greatly by source and model version, which is why we name no benchmark values here. What can be said is that cost efficiency is a declared focus of the DeepSeek models.
This can matter for companies because cheaper Inference the profitability of AI solutions can improve. Whether a model actually fits depends on the specific use case, the quality wanted and the requirements around data protection and operation. A cheap model is only an advantage if it meets the expectations of the field; otherwise apparent savings can quickly be eaten up again by rework or poorer results. Careful trialling with your own realistic examples is therefore more important than general statements about capability.
DeepSeek compared with Western models
DeepSeek enters a market long shaped by US providers. The overview below places DeepSeek against well-known Western model families without claiming performance figures. It shows above all differences in origin, openness and how they are typically perceived.
Notably, several models from the DeepSeek stable are openly available, whereas GPT, Claude or Gemini mainly as closed services via an API are offered. That creates different starting points for operation and data protection, which have to be considered case by case.
The column on openness is deliberately phrased in a differentiated way, since openly available does not automatically mean usable without restriction. Licences can limit certain commercial uses or redistribution, and a model's origin can matter to some organisations for regulatory or strategic reasons. The table therefore replaces no assessment of your own but offers a first orientation to be checked against the current terms.
| Model | Provider / origin | Open source? | Typical strength | Note on use |
|---|---|---|---|---|
| DeepSeek | DeepSeek (China) | Several models open | Reasoning, cost efficiency | Self-hosting of the open models possible |
| GPT | OpenAI (USA) | No | Versatile general-purpose models | Access mainly via API |
| Claude | Anthropic (USA) | No | Safety, long contexts | Access via API and platforms |
| Gemini | Google (USA) | No | Multimodality, integration | Built into Google services |
| Llama | Meta (USA) | Openly usable (licence) | Wide availability, community | Often self-hosted |
| Mistral | Mistral AI (France) | Partly open | Efficient, compact models | European provider |
Self-hosting DeepSeek: data protection for German companies
Because some of the DeepSeek models are openly available, they can in principle be run on your own infrastructure. For German companies that is a weighty argument: if models are self-hosted, input and results need not be sent to an external service. That eases GDPR compliance considerably, since personal or confidential data can stay within your own area of responsibility.
With a cloud service whose servers sit outside the EU in particular, data protection questions arise, around processing in third countries for instance. Self-hosting an open model reduces such risks, because the processing happens locally or in a controlled environment. Tools such as Ollama or Hugging Face make getting started easier.
- Open DeepSeek models can be run on your own infrastructure.
- This way, data does not have to go to an external service outside the EU.
- That makes GDPR compliance easier with sensitive or personal data.
- Tools such as Ollama or Hugging Face support deployment and testing.
- Each model’s licence and terms of use should be checked before deployment.
When is DeepSeek interesting?
DeepSeek is worth a look above all when reasoning ability is needed and costs matter at the same time. Use cases range from code support in Software development through analysing structured tasks to scenarios where a self-hosted model is preferred for data protection reasons.
At the same time companies should consciously consider the origin and the respective terms of use. Questions of licence, support, long-term maintenance and integration into existing AI governance are part of a well-founded decision. No blanket recommendation for or against DeepSeek is possible, because it depends heavily on the purpose.
At Elisabit we help companies select suitable models, test them and integrate them responsibly into existing processes. We consider open and proprietary models alike and align the choice to the actual requirements and data protection rules.
Frequently asked questions
What is DeepSeek?
DeepSeek is a Chinese AI model family known for capable, cost-efficient language models. The reasoning models such as DeepSeek R1 have attracted particular attention because they work through complex tasks step by step. Several models are available as open source.
Is DeepSeek open source?
Some of the DeepSeek models are openly available, meaning the model weights can be downloaded and reused under certain conditions. Not every component or the training data is necessarily fully disclosed. Which models sit under which licence changes, so the provider's current statements are what counts.
What is DeepSeek R1?
DeepSeek R1 is the best-known reasoning model of the family. It is designed to solve tasks in several thought steps rather than answering immediately. That makes it especially suited to mathematics, logic, code and complex analysis.
Can DeepSeek be used in Germany in a privacy-compliant way?
Because open DeepSeek models can be self-hosted, data can be kept within your own responsibility rather than sent to an external service. That eases GDPR compliance, with sensitive data in particular. When using an external cloud service, its terms and server locations have to be checked carefully.
How does DeepSeek differ from GPT or Claude?
OpenAI's GPT and Anthropic's Claude are offered mainly as closed services through an API. DeepSeek, by contrast, has released several models openly, so they can be self-hosted. DeepSeek also comes from China and places a declared emphasis on cost efficiency.
Which use cases is DeepSeek suited to?
DeepSeek is particularly interesting where reasoning ability and cost awareness come together, in code support in software development or structured analysis tasks for instance. Scenarios in which a self-hosted model is preferred on data protection grounds come into question too. Suitability always depends on the specific purpose.
Related terms
Freely available, self-hostable language models as an alternative to proprietary AI APIs.
Meta's open-weights model family, which can be self-hosted and adapted.
A European AI company with both open and commercial models — relevant where data sovereignty matters.
A language model optimised for multi-step reasoning that thinks in steps before answering.
A tool for running large language models locally on your own machine, with a simple command line and API.
A framework of policies, roles and controls for responsible and compliant AI.
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