By funding and backstopping CoreWeave, which exclusively uses its GPUs, NVIDIA establishes its hardware as the default for the AI cloud. This gives NVIDIA leverage over major customers like Microsoft and Amazon, who are developing their own chips. It makes switching to proprietary silicon more difficult, creating a competitive moat based on market structure, not just technology.

Nvidia paid $20 billion for a non-exclusive license from chip startup Groq. This massive price for a non-acquisition signals Nvidia perceived Groq's inference-specialized chip as a significant future competitor in the post-training AI market. The deal neutralizes a threat while absorbing key technology and talent for the next industry battleground.

NVIDIA's deal with chip startup Grok, which includes hiring 90% of its staff and a massive valuation payout, is structured as a licensing agreement. This is a transparent maneuver to function as an acquihire and neutralize a competitor while avoiding the intense antitrust scrutiny a direct acquisition would trigger.

Nvidia's non-traditional $20 billion deal with chip startup Groq is structured to acquire key talent and IP for AI inference (running models) without regulatory hurdles. This move aims to solidify Nvidia's market dominance beyond chip training.

A massive, high-premium acquisition like NVIDIA buying Groq serves as a psychological "unlock" for other corporate boards. It normalizes what was previously seen as an outrageous price, silencing dissent and making it easier for executives to justify similarly large, strategic M&A deals to stay competitive.

Nvidia bought Grok not just for its chips, but for its specialized SRAM architecture. This technology excels at low-latency inference, a segment where users are now willing to pay a premium for speed. This strategic purchase diversifies Nvidia's portfolio to capture the emerging, high-value market of agentic reasoning workloads.

Despite NVIDIA's new Rubin chip boasting 10x inference improvements, the acquisition of Grok's team was not redundant. It was a strategic move to acquire a world-class team with rare expertise in SRAM innovation—a skill set outside NVIDIA's core wheelhouse—effectively a $20 billion acqui-hire for unique talent.

In a power-constrained world, total cost of ownership is dominated by the revenue a data center can generate per watt. A superior NVIDIA system producing multiples more revenue makes the hardware cost irrelevant. A competitor's chip would be rejected even if free due to the high opportunity cost.

NVIDIA's deal with inference chip maker Grok is not just about acquiring technology. By enabling cheaper, faster inference, NVIDIA stimulates massive demand for AI applications. This, in turn, drives the need for more model training, thereby increasing sales of its own high-margin training GPUs.