Spent part of this week reading that r/macbook thread telling people to buy before prices go up again. Top comment calls it inflationary thinking. I think that comment has the mechanism right and the market wrong, and the difference matters if you're putting real money into hardware right now.

System (so to speak) * 2x DGX Spark (GB10, 128 GB unified each) * RTX 3090 * 2x Tesla P40 * 192 GB DDR4 * API bills that keep dropping

Why this is happening, in order of how much I trust the driver

Memory is in a structural shortage. DRAM and NAND are up 200–400% off the 2023 lows. A RAM kit cost about half in mid-2024 what it does now. The three memory makers barely disagree on the timeline: Micron says the shortage runs through 2027, Samsung through 2028, SK Hynix through 2030. The cause is allocation, not a pandemic: fabs make HBM for datacenters because that's where the margin is, and consumer DRAM gets the leftovers. One stat I keep coming back to: OpenAI is said to be pulling about 40% of global DRAM supply. NVIDIA raised the DGX Spark from $3,999 to $4,699 in March 2026 and publicly blamed memory. The box I want to run got 17% more expensive in a single move.

Export controls are ratcheting, not easing. The US-China chip fight has been going long enough that it's now infrastructure, not policy debate. India and the EU are stockpiling sovereign compute, and people write about a "compute curtain" instead of a chip shortage. If cloud AI access gets geopolitically gated, the box in your house stops being a hobby and becomes a hedge.

The labs have every incentive to raise prices once they've hooked you. Token prices have fallen three years straight, which is exactly how you capture a market. It's also a classic entry strategy. Compute inputs are getting more expensive (see driver one), capex is brutal, and none of the big labs is convincingly profitable at frontier scale. So either the price of tokens rises, or the price of the hardware to avoid them does.

The counter-argument, and why it doesn't kill the bet. Open weights are getting more efficient faster than the hardware needed to run them. DeepSeek V4.1 Flash is MIT-licensed, 284B total parameters with 13B active per token, and the release materials say it runs locally on dual RTX 4090s. That's the direction of travel. Distillation, MoE activation sparsity, quantization, they all keep pushing the same capability down the memory requirements, which is a big part of why API prices keep cratering. So the labs' pricing power is weaker than it looks, I'll grant that.

But it cuts both ways. A release like that makes my existing box worth more, not less. Every few months the same 128 GB runs something better than it could three months earlier. People call hardware a depreciating asset, and they're right about the silicon, wrong about the full picture: the silicon depreciates, the capability it runs appreciates. And the cheaper the open weights get, the more it matters who actually owns the thing that runs them, because the alternative is trusting someone else's access.

Which is the part that keeps me in this bet. Three years in, AI is integral to how most of us work. Going back would be detrimental, not mildly inconvenient. When something is that embedded and the access to it is somebody else's to grant or revoke, the position that gets rarer is the one with local access.

The part that makes me think this isn't a normal cycle

The thing that separates this shortage from the ones I've lived through: the people who make the stuff don't want it to end. DRAM is basically three companies, Samsung, SK Hynix, Micron. Three fabs decide the global price. And they have a documented history of agreeing on that price with each other: the early-2000s DRAM price-fixing scandal ended in billions in fines, and Micron only escaped by becoming the government's witness. In June 2026 a federal cartel lawsuit alleged the same three started coordinating again around 2022, which is exactly when this scarcity began. I'm not claiming the lawsuit is true. I am saying "it's not in their interest to make memory cheap" is not paranoia, it's an incentive structure with a paper trail.

The state layer used to push the other way. Democratic governments leaned on the industry against monopoly pricing, that's what the fines were. That era is ending in real time: the US is reportedly mulling an equity stake in Micron, and this week there are reports of Intel and SK Hynix talking joint memory production in Ohio. Korea backs Samsung and SK Hynix. China runs the whole thing as a state program. When the government is the regulator and the shareholder at the same time, the old "keep prices honest" pressure disappears. It looks less like a bust cycle and more like governments industrializing on purpose, the way Japan did in the Meiji era: pick the industries, back the companies, let them set the terms.

So the forecasts keep sliding. Micron says through 2027, Samsung through 2028, SK Hynix through 2030, and none of them has an incentive to call an early end. My position: prices don't go back to 2023 levels for the rest of the decade. That's a plateau, not a promise. Memory has crashed unexpectedly before, 2007 was one, and a broke cartel or an overbuilt fab would do it again. Keep the "for a long time," drop the "never."

Planned obsolescence is real but it's not physical. Nobody comes to smash old GPUs. What dies is support: drivers stop, architectures get shelved, NVIDIA's software contract on the GB10 is NVIDIA's to renew or drop. That's the destroy-old-hardware mechanism they actually have, and it's why holding silicon forever fails even when scarcity holds: value follows the software roadmap, not the silicon.

That's where the class divide lands. The people on the right side of this aren't the ones who watched. It's the ones who can afford the hardware AND run it properly, KV caches, quants, memory budgets, model serving. A new upper-middle class built out of people who own their compute and know how to operate it, and a growing gap to everyone renting it sight unseen. The window to buy commodity-priced hardware closes somewhere around 2030, after which they keep finding reasons to extend the narrative. If that's the world, the mistake is waiting.

Where I have to be careful

My own framework says scarce compute holds value (the 3090, 24 GB of VRAM that's still useful) and commoditized compute collapses (the 1080 Ti, whose capability got eaten by everything after it). The GB10 is in the dangerous middle. The 128 GB is scarce today, but the software contract is NVIDIA's: DGX OS, Arm, a closed-enough platform. Carmack's public complaint that the Spark runs at half its promised performance and runs hot didn't dent the price, but it told me the platform's reputation can be moved. Datacenter GPUs tell the same story with better numbers: refurbished H100s hold maybe 75–85% of value through month 24, NVIDIA's warranty doesn't transfer, and Blackwell is expected to push H100 secondary prices down 10–20% once it's broadly available. Every hardware bull case has a schedule-driven obsolescence clause.

The bet, stated plainly

I'm gauging that local AI hardware appreciates more than gold over the next five years. Gold is at about $4,400 after touching $5,600 in January, up from roughly $2,000 three years ago. That's a high bar and it's already run.

The part I'm most confident in is the skills half. Running small models well on home boxes, knowing what a KV cache is worth, serving a 100B-class model on a 273 GB/s memory budget, that's a scarce skill getting scarcer. When compute is gated, the people who can operate it locally are the infrastructure. I'm running a two-Spark setup and keeping a ledger of what it costs versus what the API equivalent would cost, because I want the number that settles this instead of the narrative.