If you find that the cost of renewing or purchasing a new cloud server in 2026 is higher than it was last year, your impression is correct. At the start of 2026, Amazon AWS and Google Cloud led the way by raising prices on core cloud products—a move subsequently followed by domestic cloud providers in China. This breaks a nearly 20-year industry convention of prices only ever decreasing. This is not merely a pricing strategy adjustment by a single provider; rather, it is the result of structural cost increases on the supply side being passed on to end users.

Understanding exactly where these costs are rising is more important than simply comparing price tags. Below, we break down the true sources of this wave of cloud cost increases across four dimensions: hardware, electricity, networking, and business models.

Hardware: The "AI Crowding-Out Effect" on Storage Chips Is the Biggest Variable

The most direct and intense driver of rising cloud costs in 2026 stems from memory and flash storage chips.

Procurement data disclosed by Octave Klaba, founder of OVHcloud, shows that—using June 2025 as a baseline—memory prices had risen approximately sixfold by June 2026, while SSD prices had increased about 3.2 times. By September 2026, memory prices are projected to reach nine times their baseline level, with forecasts for early 2027 suggesting an increase of up to 12 times. NVMe drives have seen price hikes of roughly seven times, and mechanical hard drives (HDDs) about 3.5 times; meanwhile, prices for CPUs, motherboards, and network interface cards (NICs) are expected to rise by 15% to 20%.

The root cause lies in the "crowding-out" of storage production capacity by the demand for AI computing infrastructure. Major suppliers like Samsung and SK Hynix have prioritized shifting their manufacturing capacity toward High-Bandwidth Memory (HBM) for GPUs, which has directly squeezed the supply available for standard DDR4 and DDR5 memory. Data from TrendForce further quantifies this trend: contract prices for server DRAM rose by a cumulative 64% in the second half of 2025 and are projected to climb by another ~270% in 2026. Enterprise-grade SSDs are also expected to see a cumulative price increase of 235% throughout 2026. As a result, the share of DRAM and NAND within the capital expenditures (CAPEX) of major cloud service providers is projected to climb from 47% in 2026 to 68% by 2027. The systematic inflation of hardware procurement costs—driven by memory and storage chips—inevitably exerts upward pressure on server rental prices.

Electricity: The "Ongoing Operational Cost" of AI Inference Erodes Subsidization Capacity

The cost structure of cloud computing is shifting from "one-time hardware investment" toward "ongoing operational expenditure," with electricity emerging as the fastest-growing variable.

In the past, the low prices seen during "compute power wars" were largely predicated on the fact that model training tasks were episodic expenditures—allowing cloud providers to trade subsidies for market share. AI inference, however, represents an ongoing operational expense. With the proliferation of AI agents and a surge in token-based requests, the electricity and bandwidth costs generated by massive concurrent usage have surpassed the limits of what cloud providers can afford to subsidize.

Data confirms this trend: TrendForce forecasts that global data center power demand will reach 161 GW by 2026—a year-on-year increase of approximately 31%—with AI servers accounting for roughly 33.4% of this total. The convergence of constrained power quotas and a critical shortage of high-end compute capacity has created a severe supply-demand imbalance, leaving no physical room for prices to decline. For operations hosted in overseas data centers, local electricity rates are directly reflected in monthly server rental costs—a variable that is set only to rise through 2026.

Networking: The "Scarcity Premium" on High-Quality Connectivity to China Is Further Amplified

For businesses serving users in mainland China, networking costs represent a distinct variable—one separate from hardware and far more difficult to mitigate through simple capacity scaling.

High-quality network routes back to China—exemplified by CN2 GIA—possess a cost structure fundamentally different from standard international bandwidth. Enterprises are not merely purchasing a specific amount of bandwidth (Mbps); they are securing dedicated network paths, guaranteed delivery quality for specific carriers, and capacity assurances during peak hours. CN2 GIA, which leverages China Telecom’s premium international network (CN2), involves distinct upstream procurement terms and capacity guarantees. Because these routes are highly specific, there is far less flexibility in resource selection, leaving little room for cost optimization. Against a backdrop of rising hardware costs, the scarcity premium for high-quality network routes has been further amplified. To maintain connectivity, some businesses may be forced to route traffic through third-party intermediaries—a practice that significantly inflates costs while compromising stability. For those hosting websites or providing API services, any bandwidth savings gained by opting for "standard" (lower-quality) network routes are often effectively "paid back" through business losses caused by packet loss and retransmissions during peak evening hours.

Business Model: Shifting from "Low-Price Market Grab" to "Value-Based Pricing"

Beyond physical hardware costs, the very logic behind cloud service pricing is undergoing a transformation as we approach 2026.

For nearly two decades, cloud computing costs followed a downward, cyclical trend—driven by technological advancements and economies of scale—with "price wars" serving as the primary tactic for acquiring customers. However, the advent of the AI ​​era has triggered an explosive surge in demand, which, coupled with rising supply-side costs, has pushed the cloud industry into a phase of value reassessment and repricing. In explaining recent price adjustments, a representative from Tencent Cloud explicitly cited factors such as "market supply-demand dynamics and cost pressures," as well as an "alignment with broader global industry trends."

This signals that the strategy of relying solely on aggressive price-cutting to capture market share is losing its efficacy. Competitive success now hinges on a provider’s ability to consistently deliver stable, abundant, and scalable high-end computing power, alongside robust supporting infrastructure—including storage, networking, and engineering services. For users, the criteria for evaluating cloud providers must shift: rather than asking "who offers the best first-year discount," the focus should be on "who offers the most predictable long-term costs, and whose infrastructure can reliably deliver on its promises during peak demand."

Navigating Long-Term Costs During a Period of Rising Prices

Once the drivers of rising costs are understood, the appropriate response becomes clear: distinguish between "one-time hardware costs" and "long-term operational costs," and prioritize locking in the latter through contractual agreements.

First, focus on renewal pricing rather than first-year discounts. In an environment where hardware costs are steadily climbing, a pricing model characterized by "low first-year rates followed by a price surge in the second year" poses a greater risk to the user. Opting for a provider that explicitly guarantees the same price for renewals ensures that you are not merely securing a one-time promotional rate, but rather establishing a predictable cost baseline for the entire duration of your usage. Jtti’s lifetime recurring discount policy is designed precisely around this logic: the price paid at the initial purchase remains the same for all subsequent renewals, unaffected by market fluctuations in hardware costs.

Second, the use of high-quality network routes serves as a hedge against the uncertainty of network-related costs. While premium routes back to China command a higher price, they guarantee stability—ensuring no packet loss and consistent service performance, even during evening peak hours. Jtti’s Hong Kong and U.S. nodes utilize premium CN2 GIA routes with optimized direct connectivity across all three major Chinese carriers; in real-world testing, packet loss during evening peak hours remains consistently below 0.5%. In an environment where rising hardware costs are already driving up total expenditure, avoiding service disruptions and the operational overhead of retries—issues often caused by poor network quality—is, in itself, a form of cost control.

Third, Jtti aligns configurations with specific use cases, ensuring users don’t pay for "excess computing power." For workloads characterized by short bursts of high throughput (such as image pulling or batch synchronization), Jtti’s "lightweight" cloud offerings provide the necessary bandwidth—featuring 200 Mbps of dedicated capacity—at a lower monthly cost. For operations requiring 24/7 uptime with unpredictable traffic growth, the CN2 cloud server series—offering unmetered bandwidth—prevents the additional expenses that would otherwise arise from exceeding monthly data quotas. Jtti provides a comprehensive range of configurations, from lightweight cloud options to unmetered CN2-based solutions, with transparent, easily accessible pricing.

The projected rise in cloud costs by 2026 stems from a convergence of four factors: the strain placed on storage capacity by AI, surging demand for electricity, the growing scarcity of high-quality network resources, and a fundamental shift in pricing logic. For users, the best response is not to wait for hardware prices to fall, but rather to make more prudent choices in areas where costs can be locked in via contract—specifically through lifetime renewal policies, high-quality network routing, and precise configuration matching.