In 2026, the cloud computing industry makes history by overturning a nearly two-decade-long tradition. The long-held pricing rule of "only price cuts, no increases" is shattered as global cloud providers launch a sweeping wave of price hikes.

From overseas tech giants taking the lead to domestic top-tier providers following suit, prices for core products such as AI computing power and high-end storage surge. An AI-driven computing power pricing revolution is reshaping the underlying logic and business landscape of the cloud computing industry.

This round of price hikes is not a mere market fluctuation but an inevitable result of triple transformations in AI-era computing power supply-demand, industrial costs, and business models.

As computing power shifts from a universally accessible basic resource to a scarce strategic asset, as hardware costs soar across the board squeezing industry profits, and as cloud providers pivot from "selling resources" to "selling intelligence," the two-decade-long cycle of price declines officially ends, and the cloud computing industry enters a new phase of development.

Global Cloud Providers Raise Prices in Unison

Ending Two Decades of Price Declines

For nearly two decades, the cloud computing industry has focused on scaling costs down and competing on price to gain market share, with price reductions being the constant theme.

However, in 2026, this ironclad rule is shattered as global cloud providers reach a rare consensus on price hikes, with overseas and domestic markets sounding the call for price adjustments one after another.

The overseas market takes the lead in driving change. In January this year, AWS breaks nearly two decades of industry tradition by raising prices for EC2 instances dedicated to large-scale model training by 15%, becoming the first global cloud service giant to publicly increase prices.

Google Cloud follows suit by raising prices for AI infrastructure, with increases reaching up to 100%, directly targeting the core sectors of AI computing power and storage.

Price hikes by domestic cloud providers are more concentrated, forming a coordinated move among the top three. Tencent Cloud takes the first step by announcing on March 13 a price adjustment for its Hunyuan series models, with increases of up to 400% for some core products, firing the first shot in the domestic cloud price hikes.

On March 18, Alibaba Cloud issues a price adjustment notice, raising prices for computing power card products such as the Pingtouge Zhenwu 810E by 5%-34% and for file storage CPFS (Intelligent Computing Edition) by 30%, with the new prices taking effect on April 18.

Just hours later, Baidu Intelligent Cloud follows suit, announcing price adjustments for AI computing power and storage products starting April 18, with AI computing power increasing by 5%-30% and parallel file storage also rising by 30%.

Cloud providers at home and abroad cite highly consistent reasons for the price hikes: the explosive growth of global AI applications has driven up demand for computing power, core hardware and infrastructure costs have surged, and the industry's low-price, cutthroat competition model is no longer sustainable.

From AWS and Google Cloud to Alibaba, Tencent, and Baidu, the collective actions of the world's top cloud providers signal a fundamental shift in the pricing logic of the cloud computing market.

Notably, this round of price hikes is not a blanket increase but is precisely focused on core product lines such as AI computing power and high-end storage, while prices for traditional cloud servers and other basic products remain unchanged.

This detail clearly reflects that the core driving force behind the industry's price hikes comes from the restructuring of demand in the AI era, rather than a simple cost pass-through.

AI Agents Explode in Popularity

Computing Power Transforms from Universal Resource to Strategic Asset

The pricing dynamics of the cloud computing industry have always been determined by supply-demand relationships. Over the past decade, the core demand for cloud computing has come from enterprise digital transformation, focusing on standardized scenarios such as server replacement and data storage. Cloud providers have relied on economies of scale to reduce costs, be caught in (trapped in) a cutthroat "low-price, market-share grab" dynamic.

However, the advent of the AI era has sparked a qualitative leap in demand for computing power, directly triggering a supply-demand gap.

The immediate catalyst for this round of price hikes is the widespread adoption of AI agent applications.

The rapid proliferation of OpenClaw-like agents reflects market demand for autonomous, execution-capable agents. However, in real industrial environments, their implementation faces significant challenges: due to a lack of deep understanding of industry rules and business processes, agents often repeatedly call tools when performing complex tasks, resulting in Token consumption far exceeding effective output.

Especially in high-frequency call scenarios, the Token consumption costs of OpenClaw can be tens or even hundreds of times higher than those of integrated agents. This high-input, low-output model poses sustainability challenges for large-scale industrial applications.

Behind this lies exponentially growing computing power consumption, with Tokens becoming the core variable for measuring computing power demand.

In AI large-scale model systems, Tokens are the smallest computational units for natural language processing. Every user query and every AI-generated response involves the flow and consumption of Tokens.

Data shows that the Token consumption per task for agents like OpenClaw is dozens or even hundreds of times higher than that of traditional conversational AI, directly opening the door to long-term growth in computing power demand.

IDC's forecast data vividly illustrates this explosive trend: by 2030, there will be 2.216 billion active AI agents globally, with annual Token consumption soaring from 0.0005 Peta Tokens in 2025 to 152,000 Peta Tokens in 2030, a growth of over 300 million times.

Demand growth in the domestic market is equally rapid, with Alibaba Cloud's MaaS business Bailian achieving record-high growth from January to March 2026, and Tencent's Hunyuan model seeing a fourfold increase in monthly calls, plunging computing power resources into extreme shortage.

The explosive growth in demand sharply contradicts the rigid constraints on computing power supply. Large-scale model training and inference heavily rely on high-end GPU chips. Despite ongoing efforts to promote domestic alternatives, overall production capacity still struggles to meet explosive demand.

Global chip suppliers' production capacity has long been booked in advance, prioritizing large, stable orders. Cloud providers' external computing power procurement is limited.

At the same time, global tech giants are ramping up their computing power reserves, further exacerbating supply tightness.

ByteDance alone has stockpiled 480,000 H20 GPUs, while Tencent, Alibaba, and other providers prioritize their own computing power for internal large-scale model development, leaving extremely limited computing power resources for external lease. Overseas, OpenAI, Google, and Microsoft are also continuously increasing their computing power investments, intensifying the global competition for computing power.

Under dual pressures, AI computing power has completely transformed from a "universal resource" to a scarce strategic asset, shifting the cloud computing market from a buyer's to a seller's market.

Providers like Alibaba Cloud have explicitly stated their strategy to "allocate scarce AI computing power to Token-based businesses," abandoning the low-price sale of general-purpose computing power in favor of focusing on high-value AI computing power scenarios. This resource strategy is directly reflected in price adjustments, forming the core demand logic behind this round of price hikes.

From "Selling Computing Power" to "Selling Intelligence"

Token Ecosystem Becomes Core Lever

This round of price hikes is not merely a passive adjustment to costs and supply-demand dynamics but signals a proactive strategic transformation by cloud providers. The industry is Say goodbye completely (biéchù gèbié, completely bidding farewell to) the old model of "scale at all costs, low-price cutthroat competition," shifting from "selling computing power resources" to "selling intelligent services" and reconstructing the business ecosystem around Tokens.

Alibaba Cloud's moves are the most representative. Two days before announcing the price hikes, Alibaba established the new Alibaba Token Hub (ATH) business group, integrating core AI businesses such as Tongyi Labs and Qianwen Business Unit, led directly by CEO Wu Yongming.

The organizational restructuring and price adjustments form a strategic echo (hūyìng, resonance), marking Alibaba Cloud's official abandonment of the profit model of simply selling computing power and its full upgrade to the high-end track of "selling intelligence."

Jensen Huang's assertion at the 2026 GTC Conference captures the industry's new logic: "Tokens are hard currency, and computing power is a company's revenue."

His proposed Token tiered pricing blueprint, ranging from a free tier to an ultra-high-speed tier with prices per million Tokens ranging from $0 to $150, positions Tokens as a basic commodity like electricity or water—a model widely adopted by global cloud providers.

Tokens are not just a metric for computing power consumption but have become the core lever for reconstructing cloud providers' business models.

Alibaba Cloud's strategy of allocating computing power resources to Token-based businesses is essentially about building a Token-centric business ecosystem. The more Tokens customers consume, the higher their dependence on Alibaba Cloud's AI services becomes.

Through tiered pricing, ordinary users enjoy free or low-cost Token services, while high-end customers pay a premium for high-speed, high-concurrency services, maximizing value.

Tencent Cloud's substantial price adjustments for its Hunyuan model are similarly based on a revaluation of Token value, directly enhancing the profitability of AI services by increasing Token unit prices.

Cloud providers are no longer fixated on low-price competition for general-purpose computing power but are focusing on high-value Token businesses and intelligent services. The price hikes serve as a "manifesto" for the industry's shift to high-value tracks.

Zhang Peng, General Manager of the Large Model Technology Innovation Department at Ant Group, states that technological development will ultimately return to the industry's rational demand for efficiency. In the next phase of competition, Token efficiency will become the core metric for measuring enterprise-level AI value.

"The core proposition in the second half of large-scale model industrialization is not competition over model parameter scale but the continuous improvement of unit Token efficiency," Zhang argues. He believes that enterprises should combine actual scenarios and needs, opting for AI solutions that integrate large and small models to achieve higher business value at lower computing power costs.

This transformation means that the core competitiveness of the cloud computing industry has fundamentally changed. In the past, the focus was on scale, price, and server count; in the future, it will be on model capabilities, Token ecosystems, and intelligent service efficiency, ushering the industry into a new dimension of competition.

Price Hikes Are Not the Endpoint

But the Starting Point for AI Computing Power Ecosystem Restructuring

The collective price hikes by global cloud providers are not merely price adjustments but mark the starting point for the restructuring of the entire AI industry chain. In the short term, they will accelerate industry consolidation; in the long term, they will drive the industry toward a balanced, healthy, and sustainable development trajectory.

In the short term, the price hikes will accelerate the survival of the fittest. Small and medium-sized enterprises lacking financial resources and computing power reserves will exit the market due to cost pressures, further concentrating computing power, technology, and capital resources among top cloud providers. Industry concentration will continue to rise, and the market landscape will stabilize.

In the long term, the price hikes will force the entire industry chain to break through bottlenecks. Upstream chip providers will accelerate capacity expansion and technological breakthroughs, advancing domestic substitution processes. Midstream cloud service providers will optimize computing power scheduling efficiency and reduce hardware dependence. Downstream developers will optimize model calling logic to reduce unnecessary Token consumption, forming a virtuous cycle of collaborative cost reduction and technological upgrades across the entire industry chain.

For cloud providers, the price hikes are just the first step in strategic transformation. The core of long-term competition remains three capabilities: first, computing power efficiency, improving hardware utilization through technological optimization; second, service experience, providing customers with one-stop AI intelligent services; and third, Token ecosystem, building a complete tiered service system to bind high-value customers.

The 2026 cloud computing price hike wave represents the first profound transformation brought by the AI era to the industry. It ends nearly two decades of price declines, breaks the industry's low-price, cutthroat competition dilemma, and ushers in a new era where "computing power is power, and intelligence is value."

As Tokens become the industry's hard currency and computing power becomes a strategic resource, the cloud computing industry will escape the low-level trap of resource-based competition and embark on a new journey of technology-driven, value-driven high-quality development.