By John Bromels
Publication Date: 2026-03-24 13:55:00
When Nvidia (NVDA 0.40%) paid $20 billion in cash in late 2025 for the artificial intelligence (AI) inference unit of chip start-up Groq — which is unrelated to Elon Musk’s chatbot Grok — some analysts were surprised by the hefty price tag.
But Nvidia CEO Jensen Huang clearly knows what he’s doing. “We plan to integrate Groq’s low-latency processors into the NVIDIA AI factory architecture,” he wrote at the time. And now, less than three months later, that plan has become a reality as Huang unveiled the Groq 3 LPX inference accelerator.
Here’s why this new product could change the AI inference game in 2026.
Image source: Nvidia.
Why AI inference chips matter
AI inference is nothing more than a fancy term for a trained AI model making decisions based on new data or inputs.
When ChatGPT generates a unique response to user input it has never seen before, it’s using inference. When a self-driving car analyzes real-time data from its sensors to determine whether it’s safe to accelerate, that’s inference too. Pretty much all the “work” any trained AI model does relies on inference.
Inference usually consists of two steps: prefill and decode. The prefill step is when the AI model processes a query, like a chatbot parsing a user’s question. The decode step is when the model formulates a response by accessing its accumulated training data and converting its findings into a legible answer or instruction.
“Inference chips” are processors and memory chips specifically optimized…
