The price of artificial intelligence (AI) chips is rising globally due to a mismatch between high demand and limited supply. AI technology is being used extensively in fields such as data analysis, automation, and advanced computing, but the production of specialized hardware, especially semiconductors, cannot keep up with this demand. This has led to a significant increase in the cost of semiconductor components, particularly high-bandwidth memory (HBM), which is crucial for AI systems because it allows for faster data processing through stacked memory chips. This surge in prices is not limited to Western companies. In China, major AI chip manufacturers like Huawei and Cambricon have raised the prices of their latest AI accelerators. Huawei, for example, increased the price of its newest AI chip, the Ascend 950DT, to 250,000 yuan (around 32,000 euros), a 20 to 50% increase from just two months ago. Similarly, Cambricon, often compared to U.S. tech giant NVIDIA, raised the price of its 690 AI chip by 20 to 30% in the same period. These increases reflect the broader trend of rising costs in the AI chip market. The situation is exacerbated by U.S. sanctions that have restricted access to advanced components for Chinese manufacturers. As a result, Chinese companies have had to rely on alternative supply chains, which are not only less reliable but also more expensive. This has led to higher prices for memory components, which in turn affect both new and older AI chips. For example, Huawei’s Ascend 950PR has seen its price climb from 60,000 yuan (about 7,700 euros) at the start of the year to 80,000 yuan (approximately 10,200 euros). The Ascend 910C, another Huawei product, has also increased in price from nearly 90,000 yuan (11,500 euros) to 110,000 yuan (14,100 euros). The inflation in AI chip prices is a global phenomenon, but it is particularly pronounced in China, where domestic companies are trying to overcome supply chain restrictions. Despite these challenges, the demand for AI technology continues to grow, putting pressure on manufacturers to produce more while dealing with rising costs. This dynamic is likely to continue as the race to develop advanced AI infrastructure intensifies worldwide.