Compiled: Heart of the Metauniverse

Artificial intelligence is developing rapidly at an unprecedented speed. Among the many highly anticipated AI models, DeepSeek stands out.

The installation volume of DeepSeek on Android phones has soared, which is enough to prove that DeepSeek has a user experience that other products cannot compare with in some key segments. Compared with Google Gemini, DeepSeek has shown unique features and significant advantages in many aspects.

01.DeepSeek content summary is more organized

DeepSeek and Gemini have the ability to summarize, but the summary content generated by DeepSeek is more readable.

When testing it with instructions like "Summarize recent AI innovations with 150 words", DeepSeek gave key conclusions in clear key points, although the word count slightly exceeded the limit. In addition, DeepSeek analyzes more information and has attached references for users to explore further.

Gemini's summary is concise and accurate, but it adopts paragraph form and is not as good as DeepSeek in terms of user-friendliness.

02.DeepSeek free model outweighs Gemini paid solution

DeepSeek is a free open source AI model without paying for subscription. By contrast, Gemini adopts a freemium model. Its basic functions are free, but advanced tools such as experimental 2.0 professional version models, in-depth research, and large file uploads require subscribing to Gemini Premium Edition.

03. DeepSeek local processing is better than Gemini's cloud latency problem.

Before the cloud-based Gemini returns the response, it will send each request to an external server for remote processing, which leads to the occurrence of delays. The delay duration will vary depending on network speed, server load and geographical distance. When the server traffic is high, it may cause the waiting time to become longer, the response will be slower, and even temporarily unavailable.

When running DeepSeek on a local computer or server, since all computing is performed locally, the delay in cloud communication is eliminated and these problems are avoided.

04.DeepSeek's training cost is lower

DeepSeek R1's training method uses reinforcement learning with a structured reward system to optimize accuracy and format, and its performance is better than traditional neural reward models.

It reportedly used 2,048 Nvidia H800 GPUs and completed training in just 55 days, reducing the cost to $5.5 million, much lower than the $191 million that Gemini predicted. However, experts also remind that DeepSeek's statement on cost lacks sufficient transparency and may not be accurate.

05. Even if notInternet connection, DeepSeek can also work

When users need AI help the most but cannot connect to the Internet, they will not be able to obtain support from artificial intelligence. Cloud-based artificial intelligence requires a stable network connection to answer questions, summarize documents, or generate creativity.

While Gemini Nano supports offline functionality, it cannot fully realize the full potential of the cloud version. This gives DeepSeek an advantage in scenarios where artificial intelligence is needed offline, because self-hosting DeepSeek allows users to access offline AI services anytime, anywhere.

06.DeepSeek can be hosted by itself to maintain full privacy of interaction with AI

Most people want their search history, notes and interaction records to be kept private. The cloud-based AI model will transfer data to a remote server for processing.

While providers like Google and OpenAI adopt encryption technology and data retention, using cloud-based artificial intelligence means users have to trust third parties to process their information.

This is risky for users who process confidential or proprietary content because they have little control over the storage and use of data. For example, Google may store, analyze and utilize users’ personal financial data, private ideas, or creative projects to improve its model.

DeepSeek provides a local AI solution that retains all queries, responses, and processing on the user's device. This eliminates people's concerns about data breaches, unauthorized access, or server intrusion.

07.DeepSeek supports deeper AI customization than Gemini

Gemini allows users to use the "Gems" feature to create customized AI experts, but users cannot access their source code or model parameters. This makes it impossible for users to make pre-set adjustments and cannot make fundamental changes to model processing. Therefore, users cannot integrate professional data sets and cannot optimize performance for specific application scenarios.

DeepSeek's open source framework completely opens up access to its core architecture, providing a powerful choice for researchers, businesses, and AI enthusiasts. Users can adjust the model according to specific industry, professional applications, and unique language needs.

For example, medical researchers can use industry-specific terms and case studies to train DeepSeek, thereby improving its interpretation of symptoms, test results, and medical literature. Similarly, businesses can integrate proprietary data to customize AI workflows, optimize the level of automation, and improve customer interaction experience.

08.DeepSeek supports open source collaboration

Unlike proprietary models that follow the enterprise development roadmap, DeepSeek benefits from collective contributions that can accelerate vulnerability repair andThe launch of security patches. Therefore, compared with closed source models, DeepSeek can detect and solve vulnerabilities, biases, and performance bottlenecks faster.

The open source ecosystem has also accelerated the expansion of functions. Developers can add missing feature options without waiting for official updates, which keeps growing the ecosystem of third-party plug-ins, application programming interfaces (API) integration, and performance improvements. This also enables developers to embed DeepSeek into various applications without proprietary constraints.

09.DeepSeek's self-hosted model reduces AI reviews

The closed-source model implements pre-set content audits, which limit discussions on sensitive topics for ethical, legal or risk reduction reasons.

While content filtering prevents abuse, unexpected censorship can occur when AI rejects reasonable research topics or critical social issues. This is similar to the limitations in Western AI models where filters block conversations about controversial or legally sensitive issues.

DeepSeekR1 Removal Edition provides a unique way. Unrestricted versions can be used when users install the model locally or host the model themselves. This is achieved through a process called "removal", which removes the built-in rejection mechanism and eliminates rejection behavior by modifying the internal mechanism of the model.

10.DeepSeek Artificial Intelligence is not a "black box" like Gemini

Open source access allows users, researchers and regulators to conduct independent reviews of DeepSeek. This will thoroughly check the deviations, security vulnerabilities and ethical issues in it.

The closed source model runs like a "black box", and users can only rely entirely on the guarantees made by the provider. Because of the lack of access to code and training data, users cannot fully understand how these models make decisions, nor can they determine whether they are biased, wrong or maliciously manipulated.

In the healthcare field, AI models are used to diagnose diseases, recommend treatment options, and manage patient data. A biased or unreliable AI system can lead to misdiagnosis and unfair results.

By accessing DeepSeek's training data, medical professionals and artificial intelligence ethicists can verify that the model uses a diverse, representative data set, thereby reducing systemic bias.

In the financial field, AI models will affect loan approval, fraud detection, and promote algorithmic trading. The lack of transparency makes it impossible for users to assess whether an AI system has unreasonably rejected loan applications from certain groups of people, or whether its investment decisions are based on flawed data.

Finally, the appearance of DeepSeek sounded a wake-up call to the West.

As a lower cost,Source and efficient large language model that challenges the dominance of proprietary AI solutions. If everything goes well, the algorithms behind DeepSeek's success may inspire the West and promote them to develop more cost-effective artificial intelligence products.