According to a report by global brokerage Jefferies, the emergence of low-cost artificial intelligence (AI) models is unlikely to slow AI investments. Instead, it could increase demand for computing infrastructure. The report highlights that the launch of Chinese AI company Z.ai's GLM-5.2 model marks another key development in the AI industry, intensifying competition with leading Western AI firms while reducing inference costs.
GLM-5.2: A New DeepSeek Moment
The report refers to the growing competition from Chinese AI developers as another "DeepSeek moment." Jefferies said GLM-5.2 delivers performance close to leading enterprise AI models at a much lower operating cost. Lower costs could encourage wider AI adoption across businesses.
Jefferies also noted that falling token costs are prompting more companies to deploy AI models on their own servers instead of relying on public cloud platforms. This helps improve data security and reduce cloud dependence. "GLM-5.2 proves enterprises no longer have to sacrifice intelligence for privacy. We are seeing a massive acceleration in companies pulling their AI workloads out of the public cloud and back onto local corporate servers," the report said.
Growing Acceptance of Lower-Cost AI Alternatives
According to Jefferies, Chinese AI models have rapidly increased their share of global usage on OpenRouter, reflecting growing acceptance of lower-cost AI alternatives. The report said lower AI costs could eventually increase overall demand for computing power through the economic principle known as Jevons Paradox, where greater efficiency leads to higher overall consumption.
Jefferies believes this trend will benefit AI hardware suppliers, especially memory chip makers, as higher computing demand is expected to support stronger Dynamic Random Access Memory (DRAM) demand and pricing. The brokerage also stated that there is currently "zero sign of AI capex slowing," indicating that hyperscalers and AI developers continue to invest heavily in data centres and computing infrastructure.
Long-Term Risks and Portfolio Adjustments
Jefferies said the biggest long-term risk remains whether companies will generate sufficient returns on their large AI investments. However, it added that these concerns remain theoretical for now as investment momentum continues. Reflecting its positive outlook, Jefferies added South Korean memory maker SK Hynix and Japanese flash memory company Kioxia to its model portfolios. It has also increased its weighting in Samsung Electronics while reducing exposure to internet companies such as Alphabet and Alibaba.
AI-Driven Investment Trends in Taiwan
The report also highlighted strong AI-driven investment trends in Taiwan. It said the country's economy, exports and semiconductor capital expenditure continue to benefit from the global AI infrastructure expansion led by companies such as TSMC. This content is sourced from a syndicated feed and is published as received.
