Nvidia Spends $20 Billion On Acquiring Groq

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Nvidia announced that it is acquiring Groq (not Grok), an AI accelerator company founded in 2016 by former Google TPU engineers, for approximately $20 billion. It is Nvidia's largest acquisition ever.

Groq built specialized hardware designed specifically for AI inference, which is the process of running trained models on new data. While everyone focuses on training the biggest models, Groq focused on running them efficiently at scale. The company built chips optimized for inference speed and cost. Speed is important because inference happens billions of times per day. Every chatbot response, image generation, and AI decision in production requires inference.

Training is expensive and concentrates in data centers owned by OpenAI, Google, Anthropic, Microsoft. But inference happens everywhere. Phone servers, devices, customer applications. All of these add up to millions of inferences per second globally.

Groq's technology reduces latency for inference and cuts the cost of running models in production. If Nvidia integrates Groq's architecture into its GPU lineup, the company does not just sell chips for training anymore, but also becomes essential for deploying those trained models at scale.

Other companies are doing something similar. Google is building custom chips for inference. Amazon is designing specialized hardware. Meta is building chips optimized for specific AI tasks. The trend is toward vertical integration. Build the models, own the inference hardware, and capture both ends of the value chain.