Google's Ironwood TPU vs Nvidia: The AI Chip Battle and Investment Implications

Google’s Ironwood TPU vs Nvidia: AI Chip Competition and Investment Insights

Research Findings

Google’s TPU Progress
: 7th-gen Ironwood offers 4x performance boost, supports 9,216-chip pods, and secured Anthropic’s 1M-chip order (1GW compute). Its closed architecture provides efficiency but lacks CUDA compatibility.
Nvidia’s Dominance
: 92% AI chip market share, Q3 2025 data center revenue $51.2B, Blackwell GPU delivers 2.5x training/15x inference gains. CUDA ecosystem with 4M+ developers is a key moat.
Competition Dynamics
: Both race on compute efficiency; Google’s TPU is optimized for specific workloads, Nvidia’s GPU is universal with global supply chain.

Social Media Perspectives

Reddit
: Focus on AI industry competition—Google’s TPU+OCS architecture优势 but依赖Nvidia GPU for flexibility.看好算力供应链 (LITE, 旭创, 胜宏) and NAND闪存.利空话语权低的软件公司.
Xueqiu
: “强大的谷歌，不等于颠覆NV”—Gemini 3’s strength underscores compute demand, but TPU’s closed stack limits adoption. Nvidia’s CUDA and supply chain keep it dominant.建议关注算力硬件核心资产 and energy infrastructure (供电瓶颈).

Investment Implications

Supply Chain
: Lumentum (LITE) benefits from OCS demand; Chinese suppliers 旭创 and 胜宏 for光模块/PCB.
Energy
: Bloom Energy addresses AI’s power needs (供电瓶颈).
Long-term
: Nvidia’s ecosystem remains strong; Google’s TPU adds competition but doesn’t displace NVDA yet.

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