Nvidia is making the biggest acquisition in its history, and it is not about selling more GPUs.

The company agreed to buy Groq, a startup that designs specialized chips for AI inference, in an all-cash deal valued at about $20 billion, according to CNBC’s reporting on Nvidia’s largest acquisition ever. The price tag alone makes it Nvidia’s most expensive purchase to date and a major escalation in how aggressively it plans to shape the future of artificial intelligence.

For Nvidia, this is about control, not scale.

What Nvidia Is Buying With Groq

Groq focuses on AI inference, the stage where trained AI models generate responses, images, recommendations, and real-time decisions. Unlike training chips, which build models, inference hardware runs them continuously in production.

As Wikipedia’s overview of artificial intelligence explains, inference workloads grow exponentially as AI moves from experimentation into everyday use across search, cloud software, automation, and consumer applications.

Groq built its chips specifically for that phase. Its technology emphasizes predictable latency and high throughput, making it attractive for companies deploying AI at scale rather than training new models.

By acquiring Groq, Nvidia is buying specialized silicon, engineering talent, and intellectual property designed to keep AI workloads inside its ecosystem.

Why This Is Nvidia’s Biggest Acquisition Ever

This Nvidia Groq Deal surpasses Nvidia’s $6.9 billion purchase of Mellanox in 2019, which helped transform the company from a GPU supplier into a full-stack data center provider.

Nvidia has attempted even larger deals before. Its failed effort to buy British chip designer Arm collapsed under regulatory pressure, offering a preview of how closely authorities watch Nvidia’s expansion.

The Groq acquisition is smaller than the Arm bid but more focused. It directly targets a critical bottleneck in AI deployment, making it strategically cleaner and harder to dismiss as speculative.

The Inference Race Is Heating Up

The AI chip market is splitting into two fronts: training and inference.

Nvidia dominates training, but inference is increasingly competitive. Rivals are racing to offer cheaper or more efficient alternatives for running AI models at scale. That pressure comes from traditional chipmakers like AMD and Intel, as well as from cloud providers backed by GOOGL and GOOG developing custom silicon.

The Groq deal also lands as markets speculate whether a controversial Nvidia rival may finally IPO, adding another potential competitor to the inference landscape.

Regulators Are Already Paying Attention

Any major Nvidia acquisition draws scrutiny.

Reuters reported that regulators are examining the Groq transaction for antitrust concerns, particularly given Nvidia’s dominance in AI accelerators and its expanding vertical integration.

The key issue is whether Nvidia could use control over inference hardware to disadvantage competitors or limit choice for cloud providers and enterprises. The failed Arm deal still looms large in regulators’ minds.

What Investors Should Focus On

For investors, the question is not whether Nvidia can afford the deal. It ended its latest quarter with tens of billions in cash, making an all-cash acquisition feasible.

The real question is whether owning inference hardware strengthens Nvidia’s moat without triggering regulatory constraints that limit future growth.

If successful, the Nvidia Grok Deal positions Nvidia not just as a chipmaker, but as the central architect of AI infrastructure. If regulators intervene aggressively, it could cap how much strategic value Nvidia ultimately extracts.

Either way, Nvidia is making its intentions clear: AI inference is not a side business. It is the next battlefield.

Article Sources

1. Wikipedia. “Nvidia”
2. Wikipedia. “Artificial intelligence”
3. Nvidia Newsroom. “Nvidia’s largest acquisition and M&A history”
4. Nvidia Newsroom. “Buy British chip designer Arm”
5. Reuters. “Nvidia antitrust scrutiny tied to Groq deal”