Vincent Ping - NVIDIA Through a Crypto Miner's Eyes<br>NVIDIA Through a Crypto Miner's Eyes<br>June 21, 2026·Vincent Ping·encn<br>For the past two years, watching people scramble for NVIDIA cards and the AI frenzy run hotter every quarter, I keep getting a strange flicker of recognition. I’ve seen this before. Roughly ten years ago, through my own stint as a miner, I lived the whole arc once.
I’m not here to analyze NVIDIA. I want to talk about a few things those mining years left me — and the lens they hand me for looking at the world’s most valuable company.
Up front: this is personal observation, not investment advice .
Let me start with my rigs. I’ll keep it short — it’s only the setup.
The Setup: My Mining Rigs
At the peak of the 2017 ETH mining craze, GPUs weren’t just expensive — they were gone. China was still the world’s crypto mining capital back then, and every mining-capable card got swept up domestically first. I bought over twenty cards, mostly NVIDIA, a few AMD. Some I fought for locally; others I ordered from the UK through Amazon, shipped in batches over weeks. The last batch spent a month on a cargo ship before reaching Shanghai. Once I had them all, I assembled six-card rigs, set them up in my attic, and let them hum. A big standing fan pointed at them. In summer, I ran the air conditioning too. Electricity ran several thousand RMB a month. Sometimes the house circuit couldn’t handle it — tripped the breaker more than once.
I put up with all of it because the money was genuinely good.
I stopped because of the late-2018 ETH crash. As Ethereum’s price kept falling, there came a point where what I mined couldn’t even cover the power bill. Mining rigs aren’t like stocks — if a stock drops, you can hold and wait, it costs you nothing. A mining rig burns real money every single day it’s running. The moment revenue dips below cost, your money-making asset becomes a hole that bleeds cash. So I shut them down.
I never sold a single one of those twenty-plus cards. Anyone in the GPU world knows mining cards are untouchable — running 24/7 destroys the VRAM, and nobody wants them. They sat in my attic for years until I moved house and finally scrapped them. From hunting them down across the globe to disposing of them as junk — about seven years.
That’s the setup. I dwell on it because the GPUs that ate my power bill back then were mostly NVIDIA’s — and the GPUs eating the world’s data-center power today are still NVIDIA’s. Nearly a decade apart, same protagonist; only the label changed, from “gaming” to “AI.” Those years handed me a pair of glasses: with any capital-heavy asset, ask a few questions before anything else. Below, I aim those questions at NVIDIA.
How Much of the Demand Is Real?
NVIDIA’s quarterly earnings are staggering right now — each one better than the last. But impressive earnings and real demand have never been the same thing. The mining boom taught me that.
During that scramble, how many buyers were real gamers, and how many were miners like me? This isn’t hindsight. A big slice of NVIDIA’s revenue in those years was actually mining money — booked under gaming, and counted as genuine growth in gaming demand. In 2022 the SEC found that NVIDIA had failed to tell investors mining was a “significant” reason its gaming revenue surged across several quarters of fiscal 2018, and the company settled with a fine. A class action is still grinding on, alleging more than a billion dollars in mining-related sales were buried inside “gaming.” Then the mining crash hit, that demand evaporated overnight, and the earnings were exposed for what they were: inventory piled up, the stock halved. Demand that looked bottomless had a huge chunk that could vanish in an instant — and at the time almost no one, NVIDIA included, was willing to mark it off on its own.
Today’s AI compute demand is the same setup. How much of it comes from applications that actually make money, and how much is pure arms race — “everyone else is buying, so I can’t afford not to”? On the books, both kinds look identical. You can only tell them apart after the tide goes out. And right now, a hard-to-ignore fact: end-user revenue across the entire AI industry is still in the tens of billions per year, while the big tech companies’ combined capital expenditure is heading toward $700 billion in 2026 and projected to break $1 trillion in 2027. Sequoia Capital did the math back in 2024: to justify spending at that scale, the industry needs $600 billion in annual revenue. Actual revenue is nowhere close. The enormous gap in between is held up by one thing — the not-yet-proven expectation that “AI will change the world.”
Versatility: Moat and Achilles’ Heel
When I was getting into mining, a friend advised me: buy GPUs — they’re insurance. If ETH goes south, you can mine other coins. Worst case, you can game on them. Sounded reasonable. Versatility. If one road closes, there’s always another. That’s the biggest seduction of a...