
The narrative in artificial intelligence has been clear: the companies with the biggest budgets, the most powerful GPUs, and access to vast data resources would dominate. The DeepSeek’s R1 AI model has turned the tech industry on its head, proving an age-old truth: innovation thrives not on money, but on ingenuity.
DeepSeek, a Chinese AI startup, has delivered R1 model that was built at a fraction of the cost, that matches the performance of its competitors and without relying on advanced hardware.
This isn’t just a win for DeepSeek—it’s a moment that challenges the entire way we think about innovation in AI. Let’s unpack why R1’s success proves that ingenuity, creativity, and resourcefulness can outshine deep pockets.
Nvidia remains a dominant force in the AI world, and its GPUs are still crucial for many advanced tasks.
The Cost Myth in AI
With creative problem-solving and data efficiency, smaller players can achieve what once seemed impossible.
Until now, it was widely believed that building a world-class AI model requires billions of dollars, vast amounts of high-end hardware, and exclusive access to cutting-edge chips like Nvidia’s A100s or H100s. This mindset has enabled Big Tech to dominate AI development, leaving smaller companies unable to compete due to high entry barriers.
But DeepSeek’s R1 model has shattered that myth. Using older, less expensive Nvidia chips—hardware that’s still available to Chinese companies despite U.S. export restrictions—DeepSeek achieved results on par with OpenAI’s models. The company reportedly spent just $6M to train R1, a figure that pales in comparison to the billions poured into similar projects by industry giants.
How DeepSeek Did It
Innovation doesn’t always come from brute force—it often comes from optimizing what you already have. When budgets are tight, teams are often forced to think outside the box, leading to breakthroughs that might never have been explored otherwise.
Instead of throwing endless resources at their project, DeepSeek focused on smarter strategies for training and refining their AI model. They developed algorithms that maximized efficiency, allowing them to get exceptional results with fewer resources.
DeepSeek made parts of its model open source, allowing others to run it on accessible hardware.
If a company like DeepSeek can build a state-of-the-art model without needing cutting-edge resources, what’s stopping smaller companies or startups from doing the same?
Not everyone is sold on DeepSeek’s claims. There are questions whether the company truly achieved its results with just 2,000 chips or if it has access to more resources than it lets on. Also, DeepSeek’s model appears to censor certain topics, likely in line with China’s political environment.