PART 27 / 63 spaceX招股书

算力成本 = 单 token 成本的主要决定因素

ENGLISH · ORIGINAL

This dynamic directly impacts model quality, responsiveness, and accessibility, while also determining the ability to serve the rising global demand across consumer, enterprise, and mission-critical AI applications. This creates a self-reinforcing advantage in which lower token costs drive greater model quality and user adoption, reinforcing AI leadership. Cost of Compute is the Main Driver of Cost Per Token. The total cost per token is determined by the efficiency, availability, and unit economics of the underlying compute and the cost of building and operating compute infrastructure. Improvement in the cost of building and operating this compute infrastructure—whether through lower data center construction cost, lower power infrastructure cost, shorter time to grid interconnection, or higher cluster-level throughput—translates directly into lower cost per token. Accordingly, for a given level of intelligence, we expect the long-term economics of AI companies to be driven by the ability to consistently deliver bleeding-edge compute at the lowest possible cost per token. Put simply, we view cost per token as a function of three primary inputs—the underlying AI model, the compute hardware, and energy, and we expect to have a competitive advantage in the latter two cost components.

中文翻译

算力成本 = 单 token 成本的主要决定因素

上面说的这个循环直接决定了模型质量、响应速度、可及性，也决定了能不能满足消费、企业、关键任务这些领域里全球范围内正在爆发的 AI 需求。它形成了一个自我强化的优势：token 成本越低，模型质量就越好，模型越好用户就越多，用户越多又反过来强化 AI 领导地位。

算力成本 = 单 token 成本的主要决定因素。 单 token 总成本由两个东西决定：

• 底层算力本身的效率、可获得性、单 token 经济学；

• 建设和运营算力基础设施的成本。

只要能把"建和运营算力基础设施"的成本降下来——不管是数据中心建设成本更低、电源设施成本更低、接到电网的时间更短、还是集群级吞吐更高——就直接等于单 token 成本下降。所以，在"智能水平"相同的情况下，AI 公司的长期经济模型将由一件事决定：能不能持续以"全行业最低的单 token 成本"交付最顶尖的算力。 简单讲，我们把"单 token 成本"拆成三个输入：底层 AI 模型、算力硬件、能源——而我们在后两项上有竞争优势。

⚡ 地面 AI 算力的双优势