DeepSeek AI: China and USA Face-off in Artificial Intelligence Race

The race to the moon in the 1960s was mostly motivated by politics. The rivalry between the U.S. and the Soviet Union resulted in one of the most important events affecting humanity and its progress in exploring the Universe. It’s difficult not to draw parallels between the moon landing and artificial intelligence dominance as a key event in human technological advancement, as AI technology is fundamentally shaking up the way we live, work, and engage with entertainment.

The race for AI dominance between the United States and China has intensified over the past few years, which has significantly affected the global technology landscape. With AI breakthroughs increasingly dictating economic and geopolitical power, both nations have pushed for rapid innovation. However, U.S. restrictions on NVIDIA’s high-powered AI chips (the leaders in the market for enterprise-level AI-capable hardware) have limited China’s access to cutting-edge AI hardware. This has inadvertently accelerated China’s push for self-reliance in AI development, leading to the emergence of new players in the AI field, one of the most disruptive being Deepseek AI.

While Google CEO Sundar Pichai recently suggested that DeepSeek AI is not as efficient as Google’s Gemini models, the platform is still proving to be a formidable force in AI development, especially when you look at the fluctuations in NVIDIA stock in mid-January. DeepSeek’s potential to operate effectively without requiring the most advanced chips could change the AI market’s cost dynamics. If DeepSeek can match or even approach the performance of U.S.-based AI tools while running on less expensive and lower-powered hardware, it could offer businesses a more cost-effective alternative—posing a direct threat to dominant U.S. AI players.

However, with this rise comes concerns beyond just competition. Questions about the security of the DeepSeek AI app have surfaced, particularly regarding data privacy and the potential vulnerabilities in user interactions. 

This article explores two critical aspects of DeepSeek AI’s impact:

1. Whether its ability to perform AI tasks efficiently on lower-powered chips could make it an industry game-changer
2. The security risks and concerns surrounding the platform’s openness and data protection

As DeepSeek AI continues to grow, the global AI ecosystem will need to weigh cost-efficiency against security implications in deciding its future role.

What is DeepSeek AI?

DeepSeek specializes in the development of large language models (LLMs), focusing on efficiency, affordability, and open-source accessibility. Its latest models have been reported to match or even surpass the quality and capabilities of OpenAI’s ChatGPT, marking a significant milestone in the AI industry. Unlike many Western AI companies that require high-end computing infrastructure and costly training models, DeepSeek achieves comparable AI performance using significantly fewer resources.

Who Owns DeepSeek AI?

DeepSeek AI is an artificial intelligence platform developed by Hangzhou DeepSeek Artificial Intelligence Basic Technology Research Co., Ltd., a Chinese AI company operating under High-Flyer, a hedge fund based in Hangzhou. Due to the complexity of its official name, the company rebranded as DeepSeek in 2023 to improve its market presence and branding.

Overview of Deepseek AI’s Capabilities

DeepSeek has developed several AI models, with its flagship being DeepSeek-V3. This model employs a Mixture of Experts (MoE) architecture, activating 37 billion parameters per token out of a total of 671 billion, which allows it to achieve top-tier performance among open-source models. Notably, DeepSeek-V3 excels in various benchmarks, including English MMLU, code generation, and mathematical problem-solving, often rivaling or surpassing more resource-intensive models like OpenAI’s GPT-4 and Meta’s Llama 3.1. These claims are openly expressed on DeepSeek’s website.

Open-Source Nature and Efficiency Claims

DeepSeek distinguishes itself by adopting an open-source approach, releasing its models under licenses that allow for public access and adaptation. This means that companies can take the code for the LLM and adapt it to their needs internally without having to pay for licensing costs or vendor fees that would be necessary when they use models like GPT-4.  

 

• Deepseek also claims that its models are significantly more efficient than U.S. counterparts. DeepSeek-V3’s training reportedly cost approximately $5.6 million, utilizing about 2,000 NVIDIA H800 GPUs over 55 days. 
• In contrast, comparable models from Western companies have incurred training costs upwards of $100 million, requiring substantially more computational resources. This affordability extends beyond training, as DeepSeek’s architecture requires fewer high-end GPUs to achieve similar performance, making AI deployment more efficient in general.

Why Its Efficiency Threatens Traditional AI Infrastructure Costs

DeepSeek’s efficiency substantially challenges traditional AI infrastructure development standards. By delivering high-performance models that require less advanced hardware and lower operational costs, DeepSeek enables broader access to advanced AI capabilities. This democratization could lead to a shift in the AI market, where companies might prefer cost-effective solutions over investing in expensive infrastructure. Consequently, established AI firms may need to reassess their pricing models and infrastructure investments to remain competitive.

General Comparison: DeepSeek AI vs. ChatGPT

 

Feature	DeepSeek	ChatGPT
Architecture	MoE	Transformer-based
Training Cost	Around $5.5 Million	$100+ Million
Performance	Excels in tasks with logical breakdowns	Has more versatility and consistency with performing a variety of tasks
Customization	Provides high customization abilities for applications	Limited customization
Ethical Considerations	Focuses on addressing bias, fairness, and transparency (open source)	Has fairness and transparency policies that need to be interpreted by the user
Real-World Applications	Best for solving technical problems and domain-specific tasks	Excels in general knowledge, writing, and other creative tasks
Speed	Provides optimized resource usage which generally means tasks are done faster	Moderate speed
Natural Language Output	Contextual, structured, and task-focused	Conversational
Scalability	Highly scalable	Requires intensive resources for scalability
Integration	Flexible	Better for broader use cases

The Business Case for Deepseek AI

Should businesses move to DeepSeek AI? This question is important as cost efficiency and infrastructure flexibility are becoming key differentiators in a highly competitive market. DeepSeek AI has certainly positioned itself as a cost-effective alternative to U.S.-based models by leveraging hardware-independent efficiency and open-source innovation. This has profound implications for businesses looking to optimize AI deployment while reducing costs.

1. Cost Efficiency: Why Companies Might Prefer Deepseek AI Over US-based Models

It isn’t difficult to understand why the DeepSeek AI app is an attractive option for organizations of all sizes that engage with AI. If they can get their work done for less without sacrificing quality, then that’s the ideal scenario. Rising costs and inflation make this software even more attractive.

 

For example, a startup offering AI-powered customer support could adopt DeepSeek AI to generate responses with near-GPT-4-level fluency while running on mid-range GPUs instead of requiring top-tier NVIDIA hardware such as their H200 clusters (a popular choice for AI tasks) or Blackwell architecture. Similarly, an e-commerce company using AI for real-time product recommendations can leverage DeepSeek’s efficiency to reduce inference costs without sacrificing model accuracy.

 

DeepSeek AI’s open-source nature also means businesses can fine-tune and deploy the model on their own infrastructure, avoiding the recurring fees and vendor lock-in that come with closed-source AI models like Gemini and GPT-4. This level of flexibility allows companies to optimize AI models for specific applications, such as medical diagnostics, legal research, or autonomous systems, without being tied to proprietary APIs.

2. Hardware Independence: Running Powerful AI on Cheaper Hardware Reduces Infrastructure costs

Unlike many Western AI models that depend on NVIDIA’s most powerful GPUs, DeepSeek AI’s models are designed to operate efficiently on lower-cost hardware. This reduces the need for expensive cloud infrastructure, making AI adoption more feasible for startups and enterprises with budget constraints. By eliminating reliance on high-end AI chips, DeepSeek AI could disrupt the AI-as-a-service industry, providing scalable solutions at a lower operational cost.

• For instance, AI-driven content creation platforms, which require massive text generation capabilities, could integrate DeepSeek AI to power their services while slashing GPU rental costs or by reducing fees paid to cloud providers like AWS, Google, and NZO Cloud.
• Similarly, a research institution that processes large-scale language datasets may prefer DeepSeek AI because it can run on consumer-grade AI accelerators rather than expensive enterprise-grade clusters. This actually makes the cost control offered by NZO through fixed fee plans more attractive because companies will require fewer resources to perform the same tasks, thus reducing their costs. 

3. Competitive Threat to U.S. AI Companies

Of course, DeepSeek poses a major competitive threat to U.S. tech giants like OpenAI, Meta, Microsoft, and Google, which have invested billions into generative AI. These companies rely on a combination of proprietary AI models and cloud-based infrastructure to dominate the market. However, if DeepSeek AI continues to gain traction, it could reshape the competitive landscape by offering comparable AI capabilities at a significantly lower price.

With its open-source approach and cost-efficient deployment, DeepSeek AI is poised to alter the economics of AI adoption. If businesses opt for lower-cost yet high-performing models, U.S. AI leaders may be forced to rethink their pricing structures and cloud dependency strategies. The question remains: will DeepSeek AI merely complement the AI market, or will it fundamentally shift the balance of power away from U.S.-based AI dominance?

Geopolitical and Market Impact of DeepSeek AI

The emergence of DeepSeek AI has sent ripples through the global technology sector, influencing stock valuations, which has prompted strategic shifts among U.S. tech giants, potentially redefining the competitive landscape of the AI industry.

NVIDIA’s Stock Volatility

In late January 2025, NVIDIA experienced a historic market capitalization loss of approximately $590 billion in a single day, triggered by investor concerns over DeepSeek AI’s cost-effective and efficient AI model. This unprecedented decline highlighted the market’s sensitivity to competitive threats from emerging technologies. However, NVIDIA’s stock demonstrated resilience, recovering nearly half of its lost value within three weeks, bolstered by sustained demand for its AI chips and strategic investments in AI infrastructure. Deepseek AI stock price is nonexistent, as the company is not publicly traded.

U.S. Tech Giants Ramp Up Investments

In response to DeepSeek AI’s advancements, major U.S. technology companies have accelerated their investments in AI infrastructure:

Company	Investment Plans
Meta Platforms	Announced plans to invest between $60 billion and $65 billion in AI initiatives, focusing on enhancing personalized user experiences and maintaining a competitive edge in AI-driven services.
Microsoft	Committed to an $80 billion investment in AI data centers, aiming to improve the efficiency and accessibility of AI technologies. CEO Satya Nadella emphasized the anticipated exponential growth in AI demand as the technology becomes more cost-effective.
Amazon and Alphabet	Collectively, these tech giants are projected to spend over $300 billion on AI infrastructure in 2025, highlighting their commitment to advancing AI capabilities and infrastructure.

 

Implications for the Global AI Market

The potential widespread adoption of DeepSeek AI could significantly impact the global AI market:

• Market Dynamics: DeepSeek’s cost-effective models may lower entry barriers for businesses, fostering increased competition and innovation within the AI sector.
• Strategic Realignments: U.S. tech companies might need to reassess their AI strategies, focusing on cost efficiency and open-source collaborations to remain competitive.
• Geopolitical Considerations: DeepSeek’s rise could prompt policymakers to reevaluate international AI collaborations and regulatory frameworks to address emerging challenges and opportunities.

Security Concerns Surrounding DeepSeek AI

While DeepSeek AI has garnered attention for its cost-effective and efficient AI models, significant security concerns have emerged, particularly regarding transparency and user data protection.

1. Transparency Issues

A comprehensive security analysis conducted by Qualys TotalAI revealed that DeepSeek’s flagship reasoning model, DeepSeek-R1, failed over half of the jailbreak tests designed to assess the model’s resilience against unauthorized manipulations. This vulnerability raises questions about the model’s robustness and the company’s transparency in addressing security flaws.

2. User Data Vulnerabilities

In January 2025, security researchers discovered that DeepSeek had left an internal database exposed, compromising over a million log entries, including sensitive user interactions, authentication keys, and backend configurations. This exposure not only jeopardized user privacy but also highlighted significant lapses in DeepSeek’s data protection measures.

Further exacerbating these concerns, an audit of DeepSeek’s iOS application revealed that it transmitted sensitive user and device data without encryption. Other security risks aside from weak encryption include SQL injection risks and hardcoded keys. 

 

The app was found to send unencrypted data over the internet, making it susceptible to interception and manipulation. Additionally, the data was routed through servers managed by ByteDance, a controversial Chinese company, (at least in the west) that owns platforms such as TikTok, and stores user data on Chinese servers. This act alone causes some to be unsure about data privacy and safety, since the company doesn’t adhere to western data privacy laws, raising alarms about potential unauthorized access and data misuse.

3. Government and Corporate Bans

These security vulnerabilities have prompted several governments to take precautionary measures: 

 

• Taiwan, for instance, has banned the use of DeepSeek AI within government agencies, citing national security concerns and the risk of information leakage. 
• Various members of the EU are either outright banning the app or have opened investigations into it to determine their next move. 
• U.S. government agencies like NASA and the US Navy have also responded by banning the app.

 

So while DeepSeek remains a disruptive force for the AI industry, its current security and transparency shortcomings seem to pose significant risks to user privacy and data protection, or at least enough that many countries and governments are taking notice.

The Trade-Off: Efficiency vs. Security

The obvious question now is whether the cost advantage of this highly-efficient AI model is worth the security risks that potentially come with it. 

Is DeepSeek AI’s Cost Advantage Enough to Overlook Security Flaws?

Businesses operating in cost-sensitive industries—such as startups, small enterprises, and even large corporations seeking to optimize expenses—might still find DeepSeek AI’s affordability compelling, even with the apparent security risks. After all, adopting the open-source software would mean reducing reliance on high-performance AI chips and lowering cloud computing costs, DeepSeek allows companies to deploy AI at a fraction of the usual expense. If you look at public opinion, namely on websites like Reddit, the general consensus right now (at least with consumers) seems to be “that my wallet says yes”. 

 

It’s also important to note that a major advantage with DeepSeek being open source is that the security risks, which were readily found by major players in the tech community, can be analyzed and rectified if a company or user decides to patch these vulnerabilities themselves, or if a company or individual is savvy enough to seek out user-provided security fixes. However, not every company or person is going to perform this crucial step. However, if DeepSeek’s goal really is worldwide adoption, then it’s in their best interest to improve the software’s base security measures. 

Should Businesses Risk Security Vulnerabilities for Reduced Operational Costs?

Of course, the answer isn’t as simple as “yes” or “no”. Industries with stringent security and regulatory requirements—such as finance, healthcare, and government—may find DeepSeek AI’s security lapses too great a liability. A financial institution, for example, cannot afford AI-generated errors or data leaks that could compromise customer assets.

On the other hand, companies in less regulated sectors, such as marketing or gaming, might be more willing to take on these risks if it means significant cost reductions. For them, the trade-off might be acceptable, especially if they implement additional security measures to mitigate potential vulnerabilities.

How Will Regulators Respond to the Growing Use of Potentially Insecure AI Models?

With growing concerns about AI security and data privacy, regulatory bodies worldwide may take a stricter stance on models like DeepSeek AI. Given that several government organizations around the world and even entire countries have banned the app, these restrictions could cause DeepSeek to be limited in worldwide adoption, especially in critical industries. 

Regulators may introduce new compliance requirements, such as independent security audits or stricter AI transparency standards, forcing DeepSeek and similar companies to address their security shortcomings if they want worldwide adoption. As AI governance evolves, the balance between cost efficiency and security will become a crucial factor in determining which models gain mainstream acceptance.

Ultimately, businesses must weigh the financial benefits of DeepSeek AI against the potential risks of adopting a model with unresolved security concerns. The coming years will determine whether DeepSeek AI can address these vulnerabilities or if its low-cost advantage is overshadowed by the need for trust and reliability in enterprise AI solutions.

Conclusion

The rise of DeepSeek AI underscores a shifting dynamic in the AI industry, one where cost efficiency and accessibility are challenging the dominance of well-funded Western AI models. By leveraging lower-cost hardware and an open-source framework, DeepSeek successfully presents an attractive alternative for businesses looking to optimize expenses without compromising too much on performance. However, the accompanying security concerns—ranging from transparency issues to data vulnerabilities—introduce a level of risk that organizations must carefully evaluate.

While companies in cost-sensitive sectors may be drawn to DeepSeek AI’s affordability, industries with stringent data security and regulatory requirements are likely to remain cautious. The ongoing bans and regulatory scrutiny suggest that DeepSeek’s global adoption will depend on its ability to address these security concerns. Meanwhile, U.S. tech giants are responding with increased investment in AI infrastructure, ensuring that competition in the space remains fierce.

Ultimately, the AI race between China and the United States is no longer just about innovation—it’s about strategy, regulation, and trust. DeepSeek AI represents a major step in China’s push for self-reliance in AI, and whether it becomes a dominant force or a cautionary tale will depend on its ability to balance efficiency with security in the years ahead.

In your organization’s adoption of AI technology, choosing the right cloud infrastructure provider is important. Reach out to NZO Cloud today for a free trial.