Goldman Sachs: US Outspends China on AI Compute $806bn vs $110bn
阅读原文： https://t.co/5NJcVMFmPQ
The compute gap is smaller than it looks, because efficiency gains let Chinese labs deliver competitive inference at a fraction of the infrastructure cost. Developers and procurement teams choosing between US and Chinese models should track OpenRouter usage rankings and token pricing rather than headline capex figures. Goldman expects the next competitive front to be virtual-worker use cases in finance, legal and accounting workloads.
Goldman Sachs estimates major US cloud providers will spend roughly $806bn on AI infrastructure capex in 2026, against about $110bn for China. The report argues China is competing on efficiency instead, citing DeepSeek V4.1 Flash's 437x reduction in KV-cache requirements per token versus V1. Chinese models are gaining token share on OpenRouter and moving beyond chatbots into agent and coding workloads. Falling blended LLM token prices are putting pressure on inference pricing globally.
阅读原文： https://t.co/5NJcVMFmPQ
阅读原文： x.com/Jadzo1_/status… J.D. @Jadzo1_ GS: US vs China AI (Scale vs Efficiency) → The US is still massively outspending China on AI infrastructure. Goldman estimates major US cloud-provider capex at roughly $806bn in 2026E vs ~$110bn for China, so the absolute compute gap remains huge. → China is competing through efficiency. DeepSeek V4.1 Flash has reduced KV-cache requirements per token by 437x vs V1, highlighting how aggressively Chinese labs are optimising inference economics. → That efficiency is translating into adoption. Chinese models have been gaining OpenRouter token share and repeatedly occupying leading positions in usage rankings. → The gains are showing up in more valuable workloads. China models are increasing share across agents and coding, not just general chatbot usage. → Pricing is becoming a competitive weapon. Blended LLM token prices have been falling as lower-cost Chinese models gain adoption, putting pressure on inference pricing globally. → The next battleground is agents and digital labour. Goldman sees virtual-worker use cases expanding from coding into finance, legal, accounting and broader white-collar workflows. 🔗 View Quoted Tweet 💬 1 🔄 0 ❤️ 0 👀 436 📊 1 ⚡
