The Roller Coaster of Large Model Markets: Capital Logic and Technological Evolution Behind Trillion-Dollar Valuations

I. Market Volatility: From Euphoria to Correction

On June 22, 2024, a leading large model company’s stock price peaked at HK$2,980 on the Hong Kong Stock Exchange, achieving a market capitalization exceeding HK$1.33 trillion—a 24x surge from its HK$52.8 billion debut on January 8. This meteoric rise transformed the company from a “unicorn” to a “trillion-dollar club” member in just five months. However, by September 25, the stock plummeted to HK$610.5, erasing nearly 80% of its peak value and settling at a HK$300 billion market cap.

This volatility reflects broader market trends. The company’s projected 2025 revenue stood at RMB 724 million against RMB 4.7 billion in losses, yielding a price-to-sales ratio exceeding 1,000x. In contrast, another foundational model competitor traded at one-fifth its valuation, highlighting irrational exuberance and subsequent market recalibration.

II. The Logic of Scarcity Premium

1. Technological Rarity

The company’s valuation surge stemmed from its unique combination of:

• Foundational Model Excellence: Its seventh-generation model achieved industry-leading performance in multimodal understanding and long-text processing, improving test scores by 37% over its predecessor.
• Developer Ecosystem: Through its Model-as-a-Service (MaaS) platform, it attracted over 1.2 million developers, forming China’s largest AI application community.
• Technological Closure: A full-stack toolchain covering data annotation, model training, and deployment optimization reduced enterprise AI adoption barriers.

2. Structural Market Opportunities

As the first pure large model IPO in Hong Kong, the company benefited from标的稀缺性 (asset scarcity premium). With only 3% of shares publicly traded, supply constraints amplified price surges during capital inflows. ETF tracking AI sectors allocated 42% of their 2024 H1 net inflows to this stock.

3. Early Investor Exit Pressures

Angel investor Zhongkechuangxing’s RMB 40 million 2019 investment yielded 100x returns by August 2024. This triggered a chain reaction, with 380% stock turnover in Q2 2024—far exceeding tech sector averages.

III. Value Realignment: Technology and Commercial Realities

1. Delayed Monetization

Despite frequent model releases, commercialization lagged capital expectations. API calls remained the primary revenue source, with enterprise solutions contributing less than 15% of income. This “advanced technology, narrow business model” contradiction intensified during market downturns.

2. Financing-Confidence Mismatch

The company raised over HK$75 billion through three funding rounds (including IPO) within nine months, raising efficiency concerns. R&D spending plummeted from 65% of revenue in Q1 2024 to 42% in Q3, shifting investor focus to capital allocation.

3. Competitive Disruption

In H2 2024, cloud providers launched “model-as-a-service” bundles, slashing 100B-parameter model prices to RMB 0.001 per 1,000 tokens. This price war eroded the company’s API margins by 12 percentage points in Q3.

IV. Valuation Revolution: From Scarcity to Sustainability

1. Paradigm Shift in Evaluation Metrics

Markets now prioritize:

• Customer Retention: Enterprise renewal rates dropped from 89% in Q1 2024 to 73% in Q4
• Revenue Mix: Subscriptions must exceed 40% of income to justify premium valuations
• R&D Efficiency: Patent output per RMB 100 million in R&D must rank top 20% industry-wide

2. Balancing Innovation and Capital

Successful AI firms align technical milestones, financing cycles, and commercialization. For example, one platform adopted a “3-month post-model release funding, 6-month scenario deployment” rhythm, maintaining stable valuation growth.

3. Ecosystem Moats

Companies investing in developer toolchains raise customer switching costs by 3-5x. Those with comprehensive IDE plugins and model tuning tools report 41% lower major client attrition than industry averages.

V. Developer Strategies for Market Cycles

1. Technology Selection: Prioritize platforms with complete toolchain support to minimize migration risks
2. Skill Development: Focus on model fine-tuning and prompt engineering rather than generic model competition
3. Monetization Models: Balance freemium access with customized services
4. Risk Mitigation: Track emerging open-source frameworks alongside mainstream platforms

The large model market is transitioning from capital-driven speculation to value-driven competition. For technology firms, building three-dimensional competitiveness through technical depth, commercial breadth, and ecological density becomes essential for long-term survival. Developers must adopt rational technology assessments, balancing innovation with pragmatic commercialization strategies.