In the dynamic landscape of technology following the Chinese Spring Festival of 2025, a seismic shift began to unfold within the AI sector, primarily influenced by the emergence of an innovative model known as DeepSeekThis model, characterized by its efficient performance and economical cost structure, has instigated a fierce competition for computational powerOn one side lies the open-source DeepSeek, which challenges traditional industry norms with its promise of “low-cost, high-performance” solutions, while on the other, we observe the frantic depletion of NVIDIA's GPU inventory, even for models previously banned from saleThis apparent contradiction hints at a structural transformation within the AI computation market.

DeepSeek made waves on January 20th when it unveiled its open-source inference model, R1. This development, which only required an investment of $5.576 million for its pre-training—utilizing 2,048 NVIDIA H800 GPUs over roughly 55 days—boasted performance levels nearing that of OpenAI's renowned GPT-4oEven more astonishing was its inference cost, which was just 5% of that associated with similar modelsThis groundbreaking achievement posed a direct challenge to the entrenched belief that "computational power equates to dominance," resulting in a significant reaction in the financial markets; NVIDIA's shares plummeted 16.86% in a single day, erasing approximately $590 billion in market value.

However, this initial shock was just the beginning of a more dramatic narrativeIn the week following the Spring Festival, Chinese tech companies scrambled to acquire NVIDIA GPUs, including models like the H800, which were under a sales banReports indicated that these GPUs were quickly sold out, highlighting a shift in purchasing behaviorOne distributor echoed the sentiment of many, stating, "Last year, clients were comparing prices meticulously; now even the banned models are flying off the shelves." This stark change illustrates a burgeoning demand precipitated by DeepSeek's capabilities, signaling a new era in computing.

The underlying logic of this supply-demand conundrum can be traced to the explosive growth in inference demand coupled with a corresponding drop in training costs

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DeepSeek's transformative approach lies in its Test Time Scaling technology, which enhances model output quality by deploying additional computational power during the inference phase rather than relying solely on large-scale training clustersConsequently, two significant outcomes materialized: a dramatic surge in demand for inference computation and a stabilization of training requirementsEnterprises adopting DeepSeek’s models spanned diverse sectors such as finance, healthcare, and automotive, leading to a surge in user engagementOne IT company's platform witnessed thousands of new users on its first day, resulting in server overload and urgent GPU procurement.

As training needs plateaued given DeepSeek’s cost-efficient training methods, organizations now focused on optimizing inference services rather than investing heavily in expanding training infrastructureThis systemic change led to stark disparities within the GPU marketWhile banned models like the H800 series became highly sought after, certain gaming GPUs, such as the RTX 4090, faced an alarming sell-off due to diminishing training demands.

Despite a temporary rebound of NVIDIA’s shares, increasing by 13% after the initial crash, the company faces numerous challenges aheadThe progress of domestic alternatives poses a significant threatHuawei's Ascend 910C chip, for example, has already achieved 60% of the inference performance of NVIDIA’s H100, forming a robust framework of “domestic models plus domestic power” that is gaining traction in the European market.

Moreover, the optimization of algorithms also looms as an impending riskThe DeepSeek team aims to leverage model distillation techniques, potentially compressing their 600 billion parameters to a more manageable size and further reducing inference power needsShould this initiative succeed, the current GPU frenzy may prove to be fleeting.

Yet, NVIDIA's ecological advantages continue to present substantial barriers to competitors

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