Google's TPU & Gemini3 Breakthroughs: Assessing Competitive Impact on NVIDIA's AI Dominance

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• According to Internal Research Database [0]：Google’s 7th-gen TPU (Ironwood) achieves 4614 TFLOPS (10x 5th-gen), and Gemini3 Pro outperforms GPT-5 Pro in 19/20 benchmarks (Humanity’s Last Exam:41% vs31.64%) [1][2].
• Research shows：NVIDIA holds ~80-90% AI accelerator market share, with CUDA ecosystem as core moat; 2025 Q3 revenue $57B (+62% YoY), data center revenue $51.2B [5].
• Research findings：TPU excels in inference tasks (15-30x GPU performance,30-80x energy efficiency), but switching from CUDA faces high costs (software compatibility, code refactoring) [4].

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• Reddit user [3]：Google’s TPU+OCS architecture has advantages but relies on NVIDIA GPUs for flexibility; bullish on compute supply chain (LITE, Xuchuang, Shenghong) and NAND flash.
• Xueqiu user (Antique Fish) [3]：Gemini3 shows Google’s strength, but TPU lacks CUDA ecosystem and global supply chain; NVIDIA builds compute backbone for others, while energy infrastructure is a key bottleneck.

：Google’s tech advances pose a long-term threat to NVIDIA, but short-term dominance remains intact due to CUDA’s moat. Both companies drive demand for AI compute, creating opportunities in supply chains (optical modules, NAND) and energy solutions. Investors should monitor supply chain players and energy infrastructure developments.