Why Does DeepSeek Dare to Go Open Source? A Deep Dive into the Business Logic and Strategic Thinking

Open Source Isn't Charity — It's the Optimal Survival Strategy

DeepSeek's decision to go open source has sparked widespread discussion across the industry: why would an AI company make its core technology publicly available? It seems to defy business intuition, but a deeper analysis reveals that this may be DeepSeek's optimal move given the current competitive landscape.

Some analysts have pointed out that if DeepSeek had chosen the closed-source route, it would have had virtually no chance of beating giants like ByteDance in a head-to-head competition. The reason is simple — closed source means you need commercial barriers to protect your technology, but when your team size and funding are far smaller than your competitors', those barriers are paper-thin. Rivals can easily poach your key talent with offers of 30-million-yuan annual salaries.

In the AI industry, the typical representatives of the closed-source model are OpenAI (despite the "Open" in its name) and Anthropic, which build commercial moats through proprietary technology and paid API models. But this approach requires sufficient capital and talent density to maintain a technological lead. For a company like DeepSeek, whose parent company High-Flyer Capital Management is formidable in quantitative investing, it still can't match ByteDance's hundreds of billions in revenue when it comes to a sustained AI spending war. The "moat" in a closed-source model fundamentally relies on information asymmetry — and when a competitor can hire away the people who hold that information with a 30-million-yuan salary, that asymmetry collapses instantly.

As one vivid analogy puts it: "It's like a child walking barefoot down the street clutching a gold bar" — for DeepSeek, going closed source isn't protection; it's a liability.

The Three Strategic Values of Open Source

First: Explosive User Growth

Open source propelled DeepSeek's usage to the top ranks globally in record time. Consider that ByteDance and OpenAI spent enormous sums on advertising and marketing to achieve their current user bases. DeepSeek, through open source, achieved comparable or even greater user penetration at virtually zero marketing cost.

The logic behind this is straightforward: when the technology is good enough, open source itself is the best marketing. Word-of-mouth in developer communities, organic adoption by enterprise users, and citations and research from academia all create powerful network effects. Network effects refer to the phenomenon where a product or service becomes more valuable as more people use it. In the open-source AI model space, this manifests as: more developers use the model → more bugs are found and fixed → more use cases are developed → more users are attracted → more developers join. Meta's LLaMA series pioneered this approach, rapidly building a massive community ecosystem through open source. On the Hugging Face platform, there are thousands of derivative models based on LLaMA, and once this kind of ecosystem forms, it becomes powerfully self-reinforcing. DeepSeek's V3 and R1 models quickly captured global developer attention after being open-sourced — a clear manifestation of this network effect.

Second: Making the Technology "Unstealable"

Once open-sourced, the technology belongs to the world. No one needs to "steal" it anymore because everyone can use it. This paradoxically frees the DeepSeek team from the anxiety of talent poaching — even if key members are lured away with high salaries, the open-source community ecosystem is already established, and the technology's iteration won't be interrupted.

More importantly, open source establishes DeepSeek's brand identity as the "origin of the technology." Subsequent commercialization — whether enterprise services, customized deployments, or API access — can all leverage this brand premium for monetization.

Third: National Strategic Support

It has been reported that before DeepSeek's release, national leaders met with Liang Wenfeng. This suggests that DeepSeek's open-source strategy is not merely a corporate decision but carries national-level strategic intent — using the open-source model to position Chinese AI companies at the forefront of the Fourth Industrial Revolution.

The concept of the Fourth Industrial Revolution (Industry 4.0) was proposed by Klaus Schwab, founder of the World Economic Forum, referring to the new wave of technological transformation driven by artificial intelligence, quantum computing, biotechnology, IoT, and more. In the previous three industrial revolutions, nations and companies that controlled core technology standards gained enormous economic and geopolitical advantages — Britain dominated the First Industrial Revolution with the steam engine, while the United States led the second and third with electricity and information technology. In the AI era, whoever's technology becomes the default choice for global developers holds the power to set standards. China already has similar experience in 5G standards (Huawei) and mobile payments, and DeepSeek's open-source approach can be seen as a parallel effort in the large model space.

When an open-source project becomes a global standard, the surrounding ecosystem, toolchain, and talent development all tilt toward its place of origin. This is an "advance by retreating" strategy in international competition.

Liang Wenfeng's Vision: From Follower to Leader

From Liang Wenfeng's public interviews, his core philosophy is clear: Chinese technology shouldn't forever be a follower — it should lead and share.

Liang Wenfeng is the founder of High-Flyer Capital Management, one of China's top quantitative hedge funds, which at its peak managed over 100 billion yuan in assets. The core competitive advantage in quantitative investing lies in algorithms and computing power, and High-Flyer began investing heavily in GPU clusters for financial model training as early as 2019, laying the computational foundation and deep learning expertise that would later underpin DeepSeek. Liang himself graduated from Zhejiang University with a degree in Electronic Information Engineering and has a deep technical background. His motivation for founding DeepSeek wasn't simple business expansion but rather a long-term belief in AGI (Artificial General Intelligence). This combination of "technological idealism + commercial pragmatism" means DeepSeek's strategic decisions often transcend short-term profit considerations.

If DeepSeek hadn't gone open source, only DeepSeek would benefit; by going open source, the whole world benefits. This vision sounds idealistic, but it's actually a carefully calculated strategic choice. Linux is open source, but Red Hat (now under IBM) generates over $3 billion in annual revenue; Android is open source, but Google controls the lifeblood of the mobile internet through its ecosystem.

Open-source software commercialization has over 20 years of proven success stories. Red Hat went public in 1999 and was acquired by IBM for $34 billion in 2019, proving the viability of the "open-source core + commercial services" model. MySQL was acquired by Sun Microsystems for $1 billion, which was then acquired by Oracle for $7.4 billion. More recent examples include Elastic (based on Elasticsearch), which had a market cap exceeding $10 billion, MongoDB with annual revenue surpassing $1.7 billion, and HashiCorp, acquired by IBM for $6.4 billion. These companies share a common pattern: open-source core technology to acquire users and build an ecosystem, then monetize through enterprise features, managed services, and technical support. Open-source commercialization in AI is still in its early stages, but the logic is exactly the same.

The DeepSeek team clearly has this figured out: open source is just the appetizer — there are "several more moves" to come. When developers worldwide are building applications on top of DeepSeek, the company becomes an irreplaceable infrastructure provider.

Monetization Paths for the Open-Source Model

Although the original content doesn't elaborate on the business model in detail, based on industry practices, DeepSeek's commercialization path likely includes:

• Enterprise API Services: Open-source the base model for free, but offer high-performance, high-availability paid APIs
• Customized Deployment: Provide private deployment and model fine-tuning services for large enterprises
• Technical Consulting and Support: Free community support, paid commercial support
• Ecosystem Positioning: Once the ecosystem is large enough, capture value through cloud services, chip compatibility, and other touchpoints

Notably, DeepSeek's API pricing strategy already reflects this approach. Its API prices are far lower than those of OpenAI and Anthropic, adopting a "low-price customer acquisition, win through scale" strategy. As developers become accustomed to DeepSeek's interface specifications and model characteristics, migration costs gradually increase, creating a form of "soft lock-in" — the code may be open source, but the service ecosystem is not easily replicated.

Conclusion

DeepSeek's open-source decision is fundamentally a "punch above your weight" strategic choice. With limited resources, rather than spending heavily to build a moat that could be breached at any moment, it's better to tear down the walls proactively and turn the entire world into your allies. This isn't abandoning commercial value — it's choosing a longer-term, more imaginative path to value creation.

From a broader perspective, DeepSeek's choice also reflects a paradigm shift underway in the AI industry: from "the model is the moat" to "the ecosystem is the moat." As the capability gap between foundation models gradually narrows, the real competitive advantage will shift to data flywheels, application ecosystems, and user stickiness. Open source is precisely the most efficient way to set that flywheel in motion.

Key Takeaways

• DeepSeek chose open source because the closed-source model couldn't compete head-to-head with giants like ByteDance, and core talent was vulnerable to poaching with high salaries
• Open source gave DeepSeek a world-class user base at minimal cost — far more efficient than spending on advertising
• The open-source decision received national strategic support, aimed at positioning Chinese AI at the forefront of the Fourth Industrial Revolution
• Liang Wenfeng's philosophy is that Chinese tech should transform from follower to leader, with open source benefiting the entire world
• DeepSeek has stated that open source is just the appetizer, with more strategic moves to follow