The Fading Myth of DeepSeek: From AI Darling to Cold Market Eyes

Overview

In early 2025, the open-source model DeepSeek emerged with a highly competitive cost advantage, momentarily regarded as a "game-changer" in the field of artificial intelligence. However, as time passed, market enthusiasm quickly cooled, and praise once heaped upon it from a pedestal has now transformed into calm, even critical scrutiny. The technological marvel that once caused NVIDIA's stock price to fluctuate and sparked industry cheers is returning to the realm of commercial common sense.

Fading Technological Glow

At the time of its release, DeepSeek achieved performance close to that of top-tier commercial models at an extremely low inference cost, a breakthrough that once sent shockwaves through the global tech circle. Investors and commentators hailed it as a milestone for Chinese AI innovation, with some even arguing that it had broken Silicon Valley's moat of compute monopolization.

However, upon deeper analysis, the outside world discovered that its technical architecture was not a truly disruptive innovation in the full sense, but rather an efficient optimization and engineering improvement built upon existing models. This characteristic of being a "rebrand" rather than a "native revolution" gradually eroded market expectations of its scarcity. As some industry observers pointed out, once the curtain is lifted, what is seen is still the familiar "Chinese playbook"—rapid iteration and prioritized cost control, rather than breakthroughs in underlying principles.

Reversal of Market Reaction

Initially, DeepSeek's rise was interpreted as a direct challenge to the compute demand of chip giants like NVIDIA, causing significant volatility in related stocks. But as implementation progress fell short of expectations, and similar products such as Moonshot AI's Kimi and Alibaba's Tongyi successively followed suit, the market realized that a single model struggles to form a long-term barrier.

Investors began to reevaluate its commercial sustainability. While the open-source model lowered the threshold for use, it also accelerated technological homogenization. Competitors rapidly replicated and optimized similar solutions, causing DeepSeek's first-mover advantage to narrow quickly. The cold shoulder from capital markets was essentially an inevitable rational return from the premium of "concept hype."

Implications for China's AI Ecosystem

DeepSeek's journey from favorite to being shunned reflects structural problems prevalent in China's artificial intelligence industry: a focus on marketing over fundamentals, and on speed over depth. Although engineering capability is commendable, without autonomous breakthroughs in underlying algorithms or hardware, any short-term highlight is difficult to sustain.

This case also serves as a reminder to the industry that true AI competitiveness does not lie in the amazement generated at press conferences, but in long-term R&D investment, data barriers, and ecosystem construction. As the craze subsides, the market will more rationally distinguish which companies possess genuine technological moats and which merely maintain valuations through narratives.