NVIDIA's official response: Congratulations to Google on its AI progress, while emphasizing its own leading position. Google's rapid advancements in AI (especially the Gemini 3 model and TPU chip optimization) have sparked discussions about NVIDIA's dominance. NVIDIA responded with a positive yet confident tone, ostensibly praising its competitor while actually reiterating the unparalleled advantages of its GPU platform. A tribute to Google: NVIDIA begins by expressing "delight," acknowledging Google's "great advances" in AI, and emphasizing the continued collaboration between the two companies—NVIDIA continues to supply hardware to Google. This demonstrates NVIDIA's strategic maturity: avoiding zero-sum competition and positioning itself as an ecosystem partner to avoid being seen as a "monopolist." NVIDIA's core advantage lies in its claim of being "a generation ahead." Its GPU platform is the only solution capable of "running every AI model and deploying it everywhere computing is done." In contrast, ASICs (Application-Specific Integrated Circuits, such as Google's TPU), while optimized for specific AI frameworks or tasks, lack versatility. Performance Comparison: NVIDIA highlights its products' comprehensive leadership in "performance," "versatility," and "fungibility." While ASICs are efficient, they are "designed for specific purposes" and are susceptible to model iterations or framework changes, resulting in insufficient flexibility. This is crucial in AI training/inference scenarios, especially with the current diversification of models (such as from Transformers to multimodal models). My impressions after reading this: GPUs are a more general-purpose architecture, with wider applications in terms of scale and purpose. They can be used by individuals and by large enterprise clusters. TPUs are specifically optimized by Google in terms of system, architecture, and toolchain, and are better optimized for the performance of large-scale clusters. However, they are not suitable for small-scale users. Only large-scale applications like DeepMind and Anthropic can demonstrate their advantages. Therefore, it seems that GPUs and TPUs are not in direct hardware sales competition. TPUs will be offered to the public through Google Cloud, which is a competition of cloud computing power.
