One thing i don't understand and no one is doing benchmarks on is the fact when you drop $4000 to $5000 you aren't competing with desktop processors and gpus for the type of work these people are doing. At this point you can buy a threadripper in the $2500 range and a $300-$500 motherboard and put together a machine that spec wise will kill the MAC. Sure you have to stick with at least ATX form factor and sure more power hungry but if it is for productivity I have never seen those be deciding factors.
Would you, though? Let's see (using either MSRP or real-world prices, based on what's reasonable or sensible, using PCPartpicker), comparing to a base M1 Ultra (20c/48CU/64GB/1TB) Mac Studio:
Threadripper 3970X: MSRP $1999 (PCPartpicker says $3100 real-world)
Suitable motherboard: Cheapest is ASRock TRX40 Creator at $516
RAM: 4x16GB of DDR4-3600 is ~$260 at the minimum
Storage: ~$150 for 1TB of high speed PCIe 4.0 NVMe (WD SN850 or Samsung 980 Pro)
Cooler: Noctua NH-U14S TR4-SP3 $90
GPU: RTX 3070 or RX 6700 XT - $600-800 for an RX 6700 XT or RTX 3070 - subtract ~$2-300 for prices in a saner world
PSU: >650W 80+ Platinum or Titanium with a good design, ~$130
Case: Whatever you want, but ideally a well ventilated one, likely >$100
Windows licence: $100+
That leaves us with a total price of ~$3950-$4200 depending mostly on GPU choice (or ~$3750-3900 if GPU prices were less stupid), with performance very much in the same ball park, power consumption easily being 3x under heavy loads, a case many times the size, but far more upgradeability and expandability.
So, will this spec wise "kill the Mac"? No. Is it a tad more powerful? Sure - the TR 3970 is a bit faster in many workloads, and the GPUs used in the example are a bit faster than the 48-core M1 GPU. It's still quite comparable overall. You can beat it by going for a higher end CPU or GPU, but that will also (drastically) increase your price - another $2000 for a TR 3990X, another $1000 for an RTX 3090 or RX 6900 XT. RAM and storage upgrades are of course much cheaper, and the advantage from expandability shouldn't be undersold - it's important both for utility and longevity. But neither should the M1 advantage from its NPU (RTX cards can do some similar work with tensor cores, but far less efficiently, and otherwise the PC has no neural accelerators at all unless you add an accelerator card for even more cost), nor its
massive potential for VRAM - if you have workloads that can make use of this. You might of course not - but that doesn't invalidate those examples where the advantage applies.
So, is the M1 Ultra better or worse than a HEDT PC? It's mainly
different. It's still massively powerful, but not
the most powerful; it's massively efficient, but not great at all workloads; it's
extremely fast for certain specific workloads, but those are quite specific.
That comparison is still stupid to be fair. Lets assume that a 3090 at 200 watts performs worse than a 3070. What is the freaking point then of comparing the m1 with a handicapped 3090 rather than a 3070? So even if their comparison is true, its still dishonest. Thats like saying my ford is as fast as a lamborghini (*when both cars have no wheels). Sure, my statement is true, but im still trying to deceive you
When you're comparing efficiency curves it's a reasonably valid comparison. If you're comparing your part, which peaks at X power, it's reasonable to compare that to competitors also at X power, even if they scale much higher than that. It's not the full picture, and a
fair comparison would also include competitor performance at Y (their peak) power, but that doesn't invalidate the X-X comparison or make it dishonest - it's just selective. Selective argumentation can indeed be misleading and can hide the truth, but it's quite a stretch to call this example lying or outright dishonest.
Also, no 3090 at a 3070's power level would be slower - a wide-and-slow design is nearly always much more efficient than a smaller, higher clocked one. That's a huge part of why Apple is managing their massive efficiency - they're just making
huge cores and
huge chips and running them at relatively modest clocks. But unless specifically bottlenecked elsewhere, and unless you go
really unreasonably low in power, a low-clocked large GPU will always be faster than a smaller GPU at the same power levels. There's a reason Nvidia's mobile SKUs nearly always have more CUDA cores but lower clocks than their desktop counterparts - that's how you improve efficiency in a given thermal envelope. It's just expensive to do so.