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“GPUs Aren’t Gasoline: Why

NVidia and Advanced Micro Devices Prove AI Chips Aren’t Commodities” 🚨🚨🚨

If you use enough AI chatbots, they can start to feel interchangeable.

Whether it’s Google’s Gemini, tools from OpenAI, or other big-name platforms, the differences for everyday users can seem incremental. Paid tiers may perform better. Specialized coding tools may shine in niche tasks. But at a surface level, AI assistants are starting to feel like utilities — broadly similar, widely available, and increasingly commoditized.

The chips powering them? That’s a completely different story.

AMD’s Deals Signal Leverage — Just Not Its Own

Lisa Su and her team at AMD have struck notable AI chip deals recently, including arrangements with OpenAI and Meta Platforms. But these agreements reportedly involved AMD granting rights tied to potentially significant equity stakes.

That’s not standard supplier behavior. It suggests AMD is working harder — and giving up more — to secure major customers in the AI arms race.

Contrast that with Nvidia.

Nvidia’s Premium Position

Jensen Huang doesn’t appear to need to hand over equity sweeteners to close blockbuster partnerships. Nvidia’s multi-year, multi-generational GPU supply agreements stand on the strength of its dominance.

Yes, Nvidia sometimes supports customers financially to expand AI infrastructure. But that strategy looks more like ecosystem investing — ensuring its clients succeed so future GPU demand stays strong — rather than a concession to win business.

Why the difference?

Because Nvidia doesn’t just sell chips. It sells an ecosystem.

Its GPUs are tightly integrated with CUDA, the developer platform that has become the industry standard for AI training and deployment. Switching away from Nvidia hardware often means retraining teams, rewriting code, and accepting performance tradeoffs. That friction gives Nvidia pricing power — and leverage.

AI Chips Are More Like Energy Infrastructure

Think of AI models like electricity. Consumers don’t care whether power comes from solar, hydro, or natural gas — as long as the lights turn on.

Similarly, many chatbot users don’t obsess over which model is generating their text. They just want answers.

But upstream, the infrastructure is not interchangeable.

In energy markets, different grades of crude oil may refine into similar gasoline — but sourcing, transport, and refining advantages determine who captures the profits.

In AI, GPUs are the critical infrastructure. Data centers packed with advanced chips are the new power plants. And not all chips are created equal.

Commoditized Outputs, Scarce Inputs

The irony of the AI boom is this:

• The end products — chatbots — may increasingly feel like commodities.

• The foundational hardware powering them absolutely does not.

AMD’s willingness to structure creative equity-linked deals underscores its challenger status. Nvidia’s ability to command premium pricing without such concessions highlights its dominance.

In a world where AI applications blur together, the real differentiation — and pricing power — sits deeper in the stack.

And right now, the company holding the keys to that stack isn’t negotiating from weakness.