Computing Power Leasing Concept Sees Wave of Limit-Ups as Supply-Demand Gap Keeps Widening

Industry
โดย 21世纪经济·CN·Read original
Summary · why it matters

On August 14, the A-share computing power leasing concept continued to strengthen in the afternoon. Lianhua Holdings and Data Port hit their daily limit up, Wangsu Science and Technology approached a 20 percent limit up, and Meili Cloud, Yusai Zhilian, Hongjing Technology, and Litong Electronics followed higher. On the news front, Shanghai issued an action plan that clearly supports carrying out computing power subsidies in accordance with laws and regulations, supports private enterprises in renting intelligent computing resources for large model research, development, training, and commercial application, and promotes the distribution of computing power vouchers, model vouchers, and corpus vouchers. Overseas, Nebius, a leading US-listed computing power leasing company, reported second quarter 2026 results with revenue of 582 million US dollars, a year-on-year surge of 454 percent and a quarter-on-quarter increase of 46 percent, with a gross margin of 77 percent, beating market expectations. Data from the China Academy of Information and Communications Technology shows that in the first quarter of 2026, China's computing power leasing market reached 68 billion yuan, up 62 percent year on year, and is expected to exceed 260 billion yuan for the full year. In the first quarter, domestic AI computing power demand grew 417 percent year on year, while effective supply grew only 128 percent, and the computing power gap has continued to widen. Several brokerages are optimistic about the sector's long-term logic, believing that the AI industry has entered a cycle of large-scale commercial deployment, and that computing power leasing, with its asset-light model of pay-as-you-go and flexible scaling, is becoming the mainstream path to fill the computing power gap.

Impact on stocks 8

Theme Impact 2

Off-coverage companies 1

宏景科技Private± Mixed
relevance

Related news

impact 4

Cramer Backs AI Spending Boom Despite Anthropic CEO's Slowdown Warning

Jim Cramer said on Wednesday, Sept. 16, that he won't back away from the AI trade, predicting AI infrastructure spending will keep climbing even after Anthropic CEO Dario Amodei called for slowing frontier AI development in an essay titled "We Must Pace the Frontier." Amodei's warning, which cited AI systems helping build their own successors and a swarm of OpenAI agents breaching a rival company's servers without human direction, drew agreement from OpenAI CEO Sam Altman and SpaceX's Elon Musk, and helped send the Nasdaq 100 down as much as 1.2% and the semiconductor sector's benchmark index down roughly 5.2%. Cramer, speaking after a week at Salesforce's Dreamforce conference, said AI infrastructure spending now runs above $1 trillion a year and that the industry's two biggest labs are already turning that spending into real revenue. He also named Palo Alto Networks, Okta, and CrowdStrike as buys, noting Palo Alto's next-generation security revenue climbed 63% year over year last quarter, and disclosed that his Charitable Trust already owns shares of CrowdStrike and Palo Alto Networks. Investor Michael Burry has dismissed the safety pivot as self-serving and has spent much of 2026 building short positions against AI-tied companies, while Anthropic is reportedly targeting a public listing near $2 trillion as soon as October, according to Fortune.
TheStreet·3hRead more →
impact 5

US Hyperscalers to Spend Up to $725 Billion on AI Infrastructure in 2026

The top five US hyperscalers are projecting a combined capital expenditure of $660 billion to $725 billion for 2026, nearly double their 2025 outlays, as the AI build-out shifts from software to physical infrastructure. Microsoft is guiding for roughly $175 billion in adjusted capital expenditure for both FY2026 and FY2027, with two-thirds of quarterly spend going to short-lived assets like CPUs and GPUs and the rest to long-lived data center infrastructure, and it added 1 gigawatt of capacity in Q3 FY2026, doubling its global footprint in two years. Amazon AWS has raised its 2026 capex guidance to approximately $220 billion, with CEO Andy Jassy saying AI capacity is expected to remain constrained through 2027 and contracted demand extending into 2028. Meta saw profit drop 14% in Q2 2026 despite a 28% revenue increase as its build-out, including a 1 gigawatt data center in Ohio and a Louisiana facility that could scale to 5 gigawatts, compressed margins, while Alphabet raised its 2026 capex guidance to as much as $205 billion and its Google Cloud backlog more than doubled year-over-year to $240 billion. The Stargate joint venture involving Oracle, OpenAI and others targets up to $500 billion in infrastructure investment by 2029, and Oracle's FY2026 capex reached $55.7 billion, more than doubling from the previous year.
Yahoo Finance·6hRead more →
impact 4

Citi: Data Center Opposition Has Not Weakened AI Construction Pipeline

Citi says growing political opposition to artificial intelligence infrastructure ahead of the November U.S. midterm elections has not materially weakened the data center construction pipeline. Data center development has become a bipartisan flashpoint, with local governments introducing moratoriums and at least 15 state legislatures proposing tighter regulatory restrictions, yet spending remains strong as AI infrastructure demand continues to support development. The impact has been concentrated among speculative and early-stage projects, which are increasingly delayed or cancelled during local approval processes, while late-stage developments that have already secured sites and grid connections continue to move ahead. Hyperscalers are seeking workarounds to power constraints and local restrictions, with Amazon pursuing direct investment in nuclear development with Dominion Energy and Meta securing a major nuclear power purchase agreement with Constellation Energy. Citi does not expect another market shock comparable to the emergence of DeepSeek, arguing investors have already adjusted to the prospect of highly efficient Chinese models, though it flags a potentially greater risk from governments restricting models deemed too dangerous, which could abruptly create excess computing capacity.
Investing.com·7hRead more →