Price War in the AI Hardware Market

In the past two years, the AI hardware market has rapidly transitioned from an era of shortages where 'money couldn’t buy GPUs,' to a new phase marked by climbing production capacity, increasing players, and intensifying price competition. From upstream chip designers and manufacturers, to midstream server and system integrators, down to downstream cloud service providers and AI computing platforms, every segment is feeling the pressure of shrinking gross margins. On the surface, it appears to be a 'price war,' but at its core, it's a game of who will bear the costs and who holds pricing power: cloud providers hope to push costs back to upstream chipmakers, while chipmakers strive to maintain their bargaining advantage, balancing between high R&D investments and capacity expansion.

When the wave of large AI models first emerged, high-performance GPUs and AI accelerators were scarce assets. Leading chipmakers, leveraging their technological and ecosystem advantages, could almost dictate 'seller’s market' terms. Cloud providers and large model companies, eager to secure computing power, were willing to accept higher procurement prices and pass these costs on to end customers renting cloud computing power—those were days when 'you had to buy even if you couldn’t negotiate the price.' However, as manufacturing processes matured, capacity gradually increased, and more competitors introduced self-developed or alternative solutions, the supply-demand relationship began to shift subtly: no longer was it controlled entirely by a single supplier, and cloud providers now have more options.

At this turning point, a price war was almost an inevitable outcome. On one hand, chipmakers, aiming to consolidate market share, offer more attractive discounts and bundled packages to major clients, such as tying multi-generational product purchases or bundling software tools and ecosystem services. On the other hand, competition among cloud providers is exceptionally fierce, with each striving to lock in AI ventures and enterprise clients through cheaper per-unit computing costs, more free trials, and subsidies. Consequently, prices begin to ripple outward from upstream to downstream, while margin pressures simultaneously cascade inward.

For cloud providers, AI computing power is both a flagship offering and a costly battleground. On one hand, they must constantly engage in 'price wars': rolling out lower hourly rates, cheaper annual or monthly subscription plans, and even introducing promotional strategies like 'compute credits' or 'model training subsidies' to prevent high-quality clients from defecting to competitors. On the other hand, cloud businesses are often viewed as critical engines for overall company growth and profitability, and management must account for gross margins and ROIC in financial reports to shareholders—creating a natural tension.

Within the chain of price transmission, cloud providers occupy a midstream position, absorbing procurement costs from upstream chipmakers while facing the harsh reality of downstream clients who 'only recognize the lowest price.' As such, they adopt several typical strategies: First, they leverage bulk purchasing and long-term agreements to negotiate lower prices upstream, trading 'locking in multi-year demand' for better unit pricing. Second, they bundle products and implement tiered pricing, maintaining higher gross margins on top-tier GPU compute offerings while engaging in price wars with mid-range or hybrid computing solutions. Third, they emphasize Total Cost of Ownership (TCO), bundling their advantages in networking, storage, development tools, and pre-training services to downplay client focus on pure hardware unit prices.

Specifically, they maintain several defensive lines. First, for cutting-edge flagship products with still-tight supply, they adhere to relatively stable pricing, supported by technological performance and energy efficiency advantages, avoiding low-price competition. Second, for mature or mid-tier products, they proactively lower prices and offer discounts for key client programs, using a 'tiered' pricing system to expand market depth. Third, through integrated hardware-software solutions, developer ecosystems, and proprietary software tools, they increase customers’ switching costs, shifting negotiations away from 'price per chip' to the overall value of the solution.