labcomputer
Joined 14 years ago
Joined 14 years ago
MoE models want a different ratio of memory/compute/$ than dense models like a Gemma4 31B or Qwen3.8 27B.
Since only some of the experts are active each round, you don’t need as much compute to get good tok/sec, but you do need a lot of memory to avoid streaming weights from SSD or system RAM.
You could run a full Muse Spark on one of these for $24k at probably around 50 tok/sec.
You’d need 5x RTX 6000 Pros at $80k for Muse Spark (albeit at much higher tok/sec).
On a $24k budget, you’re looking at a maximum of 96GB from Nvidia or 384GB from Intel or AMD. So you’re bottlenecked by PCIe bandwidth, and all those TFLOPS go to waste.
Other configurations of the Studio have similar logic for other MoE models. For instance, Qwen3.8 flash-next runs at a very acceptable 75 tok/sec on a 128GB M5 Max for about 1/3rd the price of an RTX 6000 or 40% less than 4x B70’s.
Even using the sale prices, an iMac is still cheaper than a Mini with the Kuycon.
My absolute favorite feature of Apple displays is that I don't need to have the brightness cranked to max all the time, even when sitting next to a window. Some of them are, dare I say it, too bright for a normal office at maximum brightness (yet still dim for comfort in a pitch black room).
There are some good alternatives if your budget stretches to $1000, though: Samsung's 27" ViewFinity S9 comes to mind, with 2880p and 600 nits.
Every enrichment process drops in efficiency as the enrichment increases, asymptotically approaching that process's enrichment ceiling.
That's why nobody uses thermal diffusion to enrich uranium: It's by far the easiest method (you can do it with 1800's technology), but the practical maximum enrichment fraction is too low for anything useful (other than providing feedstock to better enrichment processes).
That's also the reason a centrifuge enrichment plant uses warehouses full of cascaded centrifuges: The centripetal force inside the centrifuge is working against a diffusion gradient, so each stage only gives a small percentage decrease of the "derichment" fraction.
Once you pass 50%, you stop looking for U-235 needles in a haystack to keep and start looking for U-238 needles in a haystack to throw away.
If a company pays you $1M of shares, the IRS treats it exactly the same as if you were paid $1M of cash and you used it to buy the shares. The capital gains work the same too: you pay capital gains tax on the difference in value between when you receive the shares and when you sell them. That’s how it already works.
When a billionaire moves to Wyoming, the marginal tax revenue is far greater than the marginal cost of police services, for example.
There’s some manifold of Pareto-optimal solutions to the problem of taxes and services.
California, for example, spends a lot of money to get not-great public schools, and has housing costs that are out of control. So if you’re importing new hires from other states, and pay them a lot to live here, and personally pay high taxes on top of that… that doesn’t seem like a Pareto-optimal point.
At some point, the wealthy will decide to move someplace that looks more Pareto-optimal. Better externalities, lower taxes, or both.
It is a fiscal detriment to CA and NY though.
- Larger MoE models only need compute proportional to the number of active parameter, so Qwen3.8-Flash-Next (180b with 6b active) runs more tok/sec than Qwen3.8-27b on the same hardware.
- Larger models typically have higher quality output and require fewer thinking tokens to get to an answer.
Consequently, measuring time to complete a task with a wall clock, the speed difference is less than you would expect.