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From 8-GPU servers to supernodes: AI data centers for the inference era

AI summary

Speaking at the 2026 ITValue Summit on September 17, xFusion computing vice president Wang Liangdong said AI has entered an inference-dominated phase in which global token consumption keeps surging and buyers judge infrastructure by cost per token, throughput and cluster stability rather than peak per-card performance. The article cites a range of figures: the 2026 China Development Forum said China's daily token calls topped 140 trillion in March, OpenRouter data showed China accounted for 36% of global token calls in the March 16-22 week, JPMorgan expects Chinese inference token consumption to grow roughly 370x in five years, and IDC projects annual global consumption of 150,000 Peta Tokens by 2030. It argues the 8-GPU server paradigm hits communication bottlenecks under trillion-parameter, high-concurrency inference, pointing to Huawei's Ascend 960 supernode (4,096 cards per node, 8E FP8), Lenovo's Wanquan heterogenous computing platform V5.0 and xFusion's FusionPoD for AI rack-scale designs — while warning that supernodes only suit very large workloads, interconnect standards remain unsettled, and utilization depends on sustained paying demand.

In-depth insight

The yardstick for AI infrastructure spending is shifting from training peak performance to cost per token and long-run utilization, which shapes how enterprises buy and size compute.

(本文作者为 硅碳变量,钛媒体经授权发布)

文|硅碳变量,作者|沈浪

9月17日,在2026 ITValue Summit数字价值年会上,超聚变算力领域副总裁王梁栋指出,伴随大模型能力加速演进,AI进入推理为主的“干活”时代,全球Token消耗将持续爆发,促使AI基础设施同步进化。

当下算力行业的竞争逻辑正在迭代,单纯依靠堆叠服务器和扩张硬件规模的粗放式发展路径,效用持续减弱。

随着AI重心从模型训练转向海量推理,算力基础设施正在经历底层变革,传统“堆硬件、扩规模”的建设思路,越来越难以匹配新阶段的产业需求。

Token的真实账单

Token不是噱头,是AI产业正在面对的真实账单。

#xFusion#Huawei#Ascend 960#Lenovo#CAICT#OpenRouter#IDC#JPMorgan

Original · 10 min readRead the original
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