Why use DeepSeek?
DeepSeek was designed from the start as an AI that is lighter, faster, and more open than its competitors. Where ChatGPT is part of a closed ecosystem (with rules of use, API limitations and regulation of generated content), DeepSeek is betting onopenness and customization.
In a logic of web creation or no-code tools, this approach is a game changer: direct integration into a product, adapting the tone, customizing responses, and deploying on proprietary servers are now possible at no additional cost.
DeepSeek vs ChatGPT: Quick Comparison
An AI at the service of web creation and no-code tools
The emergence of models like DeepSeek is part of a larger trend: the industrialization of artificial intelligence in the service of design, content and user experience. These technologies are transforming the way in which no-code tools, CMS or web platforms can deliver experiences that are more personalized, faster, and better.
To better understand the geopolitical, technical and strategic issues related to DeepSeek and semiconductors, consult our dedicated article : DeepSeek, semiconductors and the future of no-code
What DeepSeek is changing for web design and SEO
- More responsiveness : faster AI response time = improved user experience.
- Less dependency to US tools = more flexibility for European companies.
- Native AI personalization : you can train the model on the contents of a site, a CRM or an internal database.
- Reduced costs over the long term thanks to open source.
How DeepSeek fits into a powerful web approach
FAQ: Frequently asked questions about DeepSeek
Is DeepSeek an AI model available to the public?
Yes. DeepSeek is an open source model released in 2024. It can be tested freely, refined via fine-tuning, and integrated into various environments, whether locally, on a private server or via a cloud infrastructure. This makes it a strategic option for organizations that want total control over their AI, without relying on a third-party API.
What is the major difference with ChatGPT?
The main difference is in the level of openness. ChatGPT is a proprietary service, offered via subscription and API, with restrictions on content, response rates, and personalization. Conversely, DeepSeek is a open model, editable, and fully customizable depending on the case of use. This makes it more relevant in specific contexts: compliance, sovereignty, or cost-controlled performance.
Is DeepSeek suitable for web projects?
Absolutely. DeepSeek can be integrated into a web application, a back office, a no-code interface or a CMS platform like Webflow (via Make or a backend API). It is particularly suitable for projects where you want generate content, personalize the user experience, or automatically respond to contextual queries.
Can DeepSeek be trained on your own data?
Yes, it is one of its greatest assets. It is possible to train DeepSeek on a proprietary data set (internal content, product base, CRM) in order to create an AI aligned with the tone, structure and business logic of the company. This type of use is still complex to implement with OpenAI models in their public version.
Is DeepSeek relevant for SEO or content production?
Yes, especially in production logics semi-automated and framed. DeepSeek can generate page drafts, optimized snippets, or rich responses to long-tail requests, while remaining hosted on a controlled infrastructure. It can also be used to create content generation assistants embedded in a tool or a CMS.
What infrastructure is required to use DeepSeek?
Lightweight compared to historical models, DeepSeek can run on a dedicated server, a cloud machine or even locally for some use cases. It is compatible with recent GPUs and offers a modular architecture. The key is to have a Python environment and model dependencies.
Is it a risky bet against leading models?
DeepSeek is not looking to completely replace ChatGPT or Claude. It offers a freer, more customizable and sovereign alternative, useful in cases where control, security, or personalization are key. For certain projects that are very scaled or require a fine-tunable AI layer internally, this is a strategic choice.
