DeepSeek has quickly become one of the most controversial players in the AI space. With discussions swirling around its training costs, methodologies, and hardware choices, many are wondering: Is DeepSeek truly a game-changer, or is it just another overhyped project? Let’s break it all down—quickly and clearly.
Understanding the Training Cost Controversy
One of the biggest misconceptions floating around is that DeepSeek spent $5.6 million to train its model. This number, however, only represents the cost of the final training run for the base model, known as V3. In reality, AI model training is an iterative process, and earlier stages often cost significantly less. Comparing DeepSeek’s training expenses directly to competitors like OpenAI or Anthropic without understanding this nuance leads to misleading conclusions.
Is DeepSeek Really That Expensive?
The $5.6 million cost that people keep talking about is just the price of finishing the training, not the whole process. The full cost of training AI models is complicated, and DeepSeek’s actual expenses were lower than this number suggests.
DeepSeek’s Unique Training Method: Reinforcement Learning
Most AI models rely heavily on supervised fine-tuning, where human-labeled data is fed into the system to refine its performance. DeepSeek, however, took a different route—reinforcement learning. This technique allows the model to improve itself autonomously by interacting with its environment and adjusting based on reward-based feedback. This method reduces reliance on manually curated datasets and accelerates self-improvement cycles, making training both more efficient and cost-effective.
How Did DeepSeek Train Its Model Differently?
Instead of giving the model tons of pre-labeled data to learn from, DeepSeek let it teach itself by experimenting and learning from feedback. This made training faster and cheaper.
R1 vs. O1: Cost & Accessibility
The cost structure of DeepSeek’s models is another major differentiator. R1, DeepSeek’s open-source model, is available for free, making it highly attractive for developers and researchers. In contrast, O1—their premium version—requires a subscription fee of $200 per month. Moreover, DeepSeek’s API pricing for R1 is significantly lower, costing 97% less than O1’s equivalent offering. This makes R1 a much more viable option for businesses looking to integrate AI without incurring heavy expenses.
How Much Does It Cost to Use?
You can use R1 for free because it’s open source, while O1 costs $200 per month. For businesses, R1 is way cheaper, with its API pricing being 97% lower than O1’s.
The Hardware Behind the Models
Another major distinction between DeepSeek and other AI companies is the hardware they used for training. While O1 was trained using NVIDIA’s H100 GPUs, DeepSeek leveraged the H800s—a weakened version of the H100s, modified due to U.S. export restrictions on high-performance AI chips to China. Despite this hardware limitation, DeepSeek managed to achieve competitive results, raising questions about whether American AI firms truly have an insurmountable advantage in computing resources.
What Hardware Did DeepSeek Use?
DeepSeek used H800 GPUs, which are a weaker version of NVIDIA’s H100 chips. Even with this limitation, they still managed to build a strong AI model, making people wonder if all the expensive hardware in the U.S. is really necessary.
The Bigger Picture: Is AI Innovation Dependent on Massive Budgets?
DeepSeek’s approach has sparked a broader discussion in the AI community: Do companies need billions of dollars and access to the most powerful hardware to build cutting-edge AI? By demonstrating that advanced models can be trained efficiently with reinforcement learning and slightly inferior hardware, DeepSeek has disrupted the prevailing narrative of AI development. This has implications not only for AI research but also for the global AI race, particularly in the competition between the U.S. and China.
Does AI Need So Much Money and Hardware?
DeepSeek has shown that you don’t need the best, most expensive chips or billions of dollars to create powerful AI. This challenges the idea that only big American companies can lead the AI industry.
Final Thoughts: DeepSeek’s Impact on the AI World
DeepSeek has proven that alternative training methods, cost-effective models, and less powerful hardware can still lead to highly capable AI systems. Whether you see it as a revolution or just another player in the AI space, one thing is clear—DeepSeek is forcing the industry to rethink how AI is built, priced, and accessed. The AI race is evolving, and DeepSeek is at the center of the drama.
