I ran a simulation to try and find out, in the current situation regarding RAM prices, which was more economically efficient, one high performance machine, or many used/old machines. The answer ended up being a little more nuanced than I expected. Posting here because I ran this research with AI and because there is a prompt for you to do it yourself :) the long and the short of it: Conclusion There’s no single winner — the honest answer is that the right choice depends on time horizon and how much RAM is actually needed, and the crossover point is close enough to matter, not a rounding error: Short-lived project, or CapEx is the binding constraint: the fleet wins decisively on every axis (cost, compute-per-dollar) at the moment of purchase, current RAM prices make this especially lopsided right now. Always-on service expected to run 2+ years, especially at higher RAM targets: the fleet’s power draw compounds against it faster than it looks like it should, and a single modern machine is very plausibly cheaper by the time you’d actually be relying on the setup long-term. The RAM crisis specifically changes the shape of this tradeoff , not just the numbers — normally a modern machine’s higher compute-per-dollar would be a point in its favor; right now, DDR5 pricing is expensive enough to erase that advantage entirely, at least until fab capacity meaningfully recovers (most estimates: not before late 2027). Standing lesson for next time this framing comes up: “cheap old hardware looks like a clear win” is a CapEx-only intuition. Once power is counted honestly, the real crossover point is a genuinely useful number to compute before committing to either side, not an afterthought. submitted by /u/boyo1991
Originally posted by u/boyo1991 on r/ArtificialInteligence