The end of the silicon era is here
Jensen Huang did not talk about chips last night. He talked about tokens. The NVIDIA CEO spent his keynote reframing the entire semiconductor industry as a factory for digital intelligence. The market is still catching up. Most analysts are stuck looking at H200 yields and Blackwell shipping delays. They are missing the pivot. Compute is no longer the product. The token is the product.
Silicon is just the overhead. Last night, Huang made it clear that NVIDIA is transitioning from a hardware vendor to the central bank of the token economy. If you control the cost of generation, you control the rate of global innovation. The implications for enterprise margins are staggering.
The physics of the token economy
A token is a fragment of a word or a pixel. It is the fundamental unit of LLM output. In the old world, we measured performance in TFLOPS. In the new world, we measure it in tokens per dollar per watt. This is not a semantic shift. It is a fundamental change in how capital is deployed in data centers. Per recent reporting from Yahoo Finance, the focus on token throughput is the primary driver behind the massive valuation premiums we are seeing in the AI sector this morning.
NVIDIA’s Blackwell Ultra architecture is designed for one thing: high-bandwidth memory (HBM3e) saturation. Why? Because LLMs are memory-bound during inference. If you cannot move the weights fast enough, the GPU sits idle. Huang’s obsession with tokens is an admission that raw compute power has outstripped our ability to feed the processors. The bottleneck has moved from the logic gates to the memory bus.
The collapse of inference costs
The cost to generate one million tokens has fallen by 99 percent in the last twenty-four months. This is faster than Moore’s Law. It is a deflationary explosion. For a company like OpenAI or Anthropic, the cost of goods sold is effectively the electricity and the depreciation of the NVIDIA cluster. As Huang noted, the goal is to make the cost of intelligence effectively zero.
When intelligence is free, every software interface changes. We are moving from “search and find” to “generate and solve.” This requires a massive shift in how the street values cloud service providers. The old metrics of storage and compute hours are dead. The new metric is the Token Margin. This is the spread between what it costs to generate a token and what a customer will pay for the insight it provides.
Historical Collapse in Token Generation Costs (USD per 1M Tokens)
The Blackwell Moat
Critics argue that commodity hardware will eventually catch up. They are wrong. NVIDIA is not just selling a chip; they are selling a full-stack orchestration layer. The NVLink Switch System allows 72 GPUs to act as a single massive processor. This is critical for the KV cache requirements of long-context windows. If you are running a million-token prompt, you cannot do it on a single card. You need a fabric. According to data compiled by Bloomberg, NVIDIA’s networking revenue now rivals its compute revenue. This is the real moat.
Competitors like AMD and specialized ASIC startups are chasing the last generation’s benchmarks. They are building faster horses while Huang is building a power grid. The transition to the Rubin architecture, expected to be detailed further in the coming months, will likely push the HBM4 standard into the mainstream. This will further widen the gap in token-per-watt efficiency.
Token supply and demand dynamics
The market is currently in a state of oversupply for low-quality tokens and extreme scarcity for high-reasoning tokens. Not all tokens are created equal. A token generated by a small 7B parameter model is a commodity. A token generated by a 2-trillion parameter mixture-of-experts model is a high-value asset. Huang’s strategy is to dominate both ends of the spectrum.
| Model Class | Token Cost (Feb 2025) | Token Cost (Feb 2026) | Efficiency Gain |
|---|---|---|---|
| Frontier (Reasoning) | $10.00 / 1M | $1.20 / 1M | 88% |
| Mid-Tier (General) | $1.50 / 1M | $0.15 / 1M | 90% |
| Edge (Local) | $0.10 / 1M | $0.01 / 1M | 90% |
This pricing power is what drove the stock to its current highs. Investors are no longer betting on a hardware cycle. They are betting on the infrastructure of a new digital economy. As reported by Reuters, the capital expenditure from the “Hyperscalers” shows no signs of slowing down. They are locked in an arms race where the only exit is to own the most efficient token factory on the planet.
The next major milestone to watch is the March GTC event. We expect the first live demonstrations of the Rubin architecture’s HBM4 integration. If the token-per-watt metrics improve by another 3x as rumored, the current valuation of the AI infrastructure trade may actually be conservative. Watch the memory bandwidth numbers. That is where the real war is being won.
