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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.
+30% increase in execution speed compared to GPT-4 on an internal benchmark.
Increased precision on logical and mathematical tasks (according to MMLU).
Fine-tunable version available for deployment on private servers.
AI-generated summary
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 usage rules, API limitations and moderation of generated content), DeepSeek is betting on openness and customization.
For web design and 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 offers an open source alternative to proprietary AI models, designed for custom integrations in the web, no-code and business tools.
DeepSeek vs ChatGPT: Quick Comparison
Criterion
DeepSeek (R1 / V3)
ChatGPT (GPT-4)
Model
Open source, modifiable
Proprietary, not modifiable
Response time
⚡ Fast
⏳ Varies with server load
Training and fine-tuning
Possible locally or via API
Limited to the OpenAI Enterprise plan
Integration into an app / website
🌐 Easy with an API or open source SDK
Requires the paid OpenAI API
UX / product answer quality
Contextual, can be optimized
Consistent but sometimes generic
Required infrastructure
Optimized server or compatible cloud
OpenAI servers
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 no-code tools, CMS or web platforms can deliver experiences that are more personalized, faster, and better.
Faster responses: faster AI response time = improved user experience.
Less dependence on US tools = more flexibility for European companies.
Native AI personalization: you can train the model on the content of a site, a CRM or an internal database.
Lower costs over the long term thanks to open source.
How DeepSeek fits into a powerful web approach
Factor
Risk without well-integrated AI
What DeepSeek brings
Visuals & media
Poorly compressed content, heavy videos
AI to adapt formats, sizes and dynamic content.
Scripts & animations
Too many effects, unoptimized JS
AI to generate lighter, UX-oriented code.
Resource loading
Poorly structured DOM, render-blocking CSS
AI to predict the optimal loading order and generate optimized components.
UX tracking & iterations
Lighthouse score that is hard to act on
AI to analyze user feedback and improve through continuous iteration.
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 an open model, editable, and fully customizable depending on the use case. 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 to 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 semi-automated, supervised production workflows. DeepSeek can generate page drafts, optimized snippets, or rich responses to long-tail queries, 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.