DeepSeek is a new generation of artificial intelligence models, designed to directly compete with ChatGPT in terms of processing performance, response accuracy and openness of uses. Open source, fast and optimized for the web, DeepSeek is a serious alternative in the world of generative AI.
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.
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
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.
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.
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.
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.
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.
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.
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.
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