Google's Ironwood TPU Challenges Nvidia but Doesn't Threaten Dominance: Analysis

据谷歌最强AI芯片Ironwood即将登场：挑战英伟达: Google’s Ironwood TPU v7 delivers 4614 TFLOPS (FP8) per chip and 42.5 Exaflops per cluster, matching Nvidia B200 performance, with 20-30% total cost savings for inference.
据云巨头自研芯片竞赛升级 谷歌Ironwood挑战英伟达GPU统治: Nvidia holds ~80% AI chip market share (94% in training) via CUDA ecosystem (4M developers) and $500B backlog until 2026.

Reddit用户: Google’s TPU+OCS architecture has infrastructure advantages but relies on Nvidia GPUs for flexibility; Anthropic’s 1M TPU order validates demand.
雪球用户 (强大的谷歌，不等于颠覆NV的一些思考): Google’s Ironwood can’t颠覆 Nvidia—TPU lacks CUDA support and global supply chain; recommends LITE (光芯片), 旭创 (光模块), and NAND flash.

Both research and social media align on Ironwood’s niche potential but Nvidia’s short-term dominance. Nvidia’s CUDA moat and supply chain remain strong, while Ironwood excels in cost-efficient inference. Investment opportunities lie in AI infrastructure (optical modules, NAND, energy storage) and Nvidia’s core business.