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The per-token inference cost, the integration overhead, and the total compute bill for running AI workloads at scale are the variables enterprise procurement teams price before committing to any AI deployment.
When that cost stack falls, the addressable market for AI products expands.
Singapore's GIC, the sovereign wealth fund managing the city-state's foreign reserves, has publicly argued that Chinese AI models will materially cut those adoption costs, and the fund expects that compression to produce strong growth among Chinese AI companies.
The cost compression thesis GIC's argument ties the falling cost of Chinese AI models directly to broader enterprise deployment.
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