DeepSeek's road to overtaking

Artificial intelligence is developing rapidly at an unprecedented speed. Among the many high-profile AI models, DeepSeek stands out.

The surge in DeepSeek installations on Android phones is enough to prove that in some key segments, DeepSeek has a user experience that is unmatched by other products. Compared with Google Gemini, DeepSeek demonstrates unique capabilities and significant advantages in many aspects.

01. DeepSeek content summary is more organized

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

When tested using the instruction “Give me a summary of recent AI innovations in 150 words,” DeepSeek gave the key conclusions in the form of clear bullet points, although the word count slightly exceeded the limit. Moreover, DeepSeek analyzes more information and also provides references for users to explore further.

The summary given by Gemini is concise and accurate, but it is in paragraph form and is not as user-friendly as DeepSeek.

02. DeepSeek free model outperforms Gemini paid plan

DeepSeek is a free open source AI model with no subscription fees. In contrast, Gemini adopts a freemium model. The basic functionality is free, but advanced tools like the experimental 2.0 Pro model, in-depth research, and large file uploads require a Gemini Premium subscription.

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

Cloud-based Gemini sends each request to an external server for remote processing before returning a response, which leads to latency. The duration of the latency varies depending on network speed, server load, and geographical distance. When server traffic is high, it may result in longer waiting times, slower responses, or even temporary unavailability.

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

04. DeepSeek has lower training costs

The training method of DeepSeek R1 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 2048 Nvidia H800 GPUs to complete the training in just 55 days, reducing the cost to $5.5 million, much lower than Gemini's estimate of $191 million. However, experts also warned that DeepSeek's cost statements lack sufficient transparency and may not be accurate.

05. DeepSeek can work even without an Internet connection

When users need AI help the most but cannot connect to the Internet, they cannot get support from artificial intelligence. Cloud-based AI requires a stable internet connection to answer questions, summarize documents, or generate ideas.

Although Gemini Nano supports offline functions, it cannot fully tap the full potential of the cloud version. This gives DeepSeek an advantage in scenarios where offline use of artificial intelligence is required, because self-hosting DeepSeek allows users to obtain offline AI services anytime and anywhere.

06. DeepSeek can be self-hosted to maintain full privacy of interactions with AI

Most people want their search history, notes, and interaction records to remain private. Cloud-based AI models transmit data to remote servers for processing.

While providers like Google and OpenAI employ encryption and data retention policies, using cloud-based AI means users have to trust a third party to handle their information.

This is risky for users working with confidential or proprietary content, as they have little control over how the data is stored and used. For example, Google may store, analyze, and use users’ personal financial data, private thoughts, or creative projects to improve its models.

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

07. DeepSeek supports deeper AI customization than Gemini

Gemini allows users to create customized artificial intelligence experts using the "Gems" function, but users cannot access their source code or model parameters. This limits users to making pre-defined adjustments without being able to make fundamental changes to the model processing. Therefore, users cannot integrate professional data sets or optimize performance for specific application scenarios.

DeepSeek's open source framework fully opens access to its core architecture, providing a powerful choice for researchers, companies and AI enthusiasts. Users can tailor the model to specific industries, specialized applications, and unique language requirements.

For example, medical researchers can train DeepSeek using industry-specific terminology and case studies to improve its ability to interpret symptoms, test results, and medical literature. Likewise, companies can integrate proprietary data to customize AI workflows, optimize automation, and improve customer interactions.

08. DeepSeek supports open source collaboration

Unlike proprietary models that follow corporate development roadmaps, DeepSeek benefits from collective contributions that accelerate the rollout of vulnerability fixes and security patches. As a result, DeepSeek can discover and resolve vulnerabilities, biases, and performance bottlenecks more quickly than closed-source models.

The open source ecosystem also accelerates the expansion of functionality. Developers can add missing functionality without having to wait for official updates, which has led to a growing ecosystem of third-party plugins, application programming interface (API) integrations, and performance improvements. This also enables developers to embed DeepSeek into a variety of applications without proprietary constraints.

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

The closed-source model implements pre-set content review policies that limit discussion of sensitive topics for ethical, legal, or risk reduction reasons.

While content filtering can prevent abuse, it can lead to unintended censorship when AI rejects legitimate research topics or critical societal issues. This is similar to limitations in Western AI models, where filters block conversations about controversial or legally sensitive issues.

DeepSeekR1 removal version provides a unique way. An unrestricted version is available when users install the model locally or self-host it. This is achieved through a process called "de-removal," which removes the built-in rejection mechanisms by modifying the model's internal mechanisms to eliminate the rejection behavior.

10. DeepSeek AI is not a "black box" like Gemini

Open source access allows users, researchers and regulators to conduct independent review of DeepSeek. This allows for a thorough examination of biases, safety vulnerabilities, and ethical issues.

The closed source model operates like a "black box" and users can only rely entirely on the guarantees made by the provider. Without access to code and training data, users cannot fully understand how these models make decisions or determine whether they are biased, incorrect, or manipulated maliciously.

In healthcare, AI models are used to diagnose diseases, recommend treatments, and manage patient data. A biased or unreliable AI system could lead to misdiagnoses and unfair outcomes.

By accessing DeepSeek’s training data, medical professionals and AI ethicists can verify that the model uses a diverse, representative dataset, thereby reducing systemic bias.

In finance, AI models influence loan approvals, fraud detection, and drive algorithmic trading. The lack of transparency makes it impossible for users to assess whether an AI system is unreasonably rejecting loan applications from certain groups of people or whether its investment decisions are based on flawed data.

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

As a lower-cost, open-source, and efficient large-scale language model, it challenges the dominance of proprietary AI solutions. If all goes well, the algorithm behind DeepSeek's success may inspire the West and encourage them to develop more cost-effective artificial intelligence products.

Original source:

1.https://www.androidpolice.com/deepseek-gemini-comparison/

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