I just did a search for M3 Max on Primate's website. Here's the start of the results--the most I could squeeze into a screenshot on my MBP's screen. Just by eye, the SC scores average >100 points higher than the lowball score Zest28 posted.
The problem with these multi-core scores is that they don't account for multi-core tasks that actually have interdependencies, which is something that was addressed in GB6. For instance, here we also have the old $1,000 64-core AMD EPYC 7702 (released Aug 2019) outperforming the newer $5,000 32-core AMD EPYC 75F3 (released Mar 2021). So if you have a bunch of separate task that you can run on separate cores, and just need to throw a lot of cores at the problem, this benchmark may be useful--but only if the limited types of tasks it incorporates correspond to the types of tasks you are doing yourself.Well, even ~$200 Intel and AMD CPUs handily outperform the best M2 models at this point, so nothing new under the sun. But as @galad writes: comparing apples with oranges.
PassMark Intel vs AMD CPU Benchmarks - High End
PassMark Software - CPU Benchmarks - Over 1 million CPUs and 1,000 models benchmarked and compared in graph form, updated daily!www.cpubenchmark.net
Geekbench 6 takes it too far in the other direction, because it assumes that the computer is doing only one thing at a time. That may be adequate for consumer devices, but it doesn't really reflect the way higher-end computers are often used.
If we think about it, GB6 is designed for multiple threads to co-operate and finish a common task. If a CPU architecture does well using GB6, does it follow that the same CPU architecture will do just as well completing multiple un-related tasks?
If you have a 16-core processor, GB5 runs 16 independent tasks with 1 core each. GB6 does the opposite, running just one task that is allowed to use all 16 cores. I was suggesting something in the middle, such as 4 independent tasks with 4 cores each. The scaling would likely be somewhere between what you see in GB5 and GB6.
But my argument then still stands correct? If a CPU architecture does well with completing a shared task, does it follow that it will work just as well with the other extreme and anything that is in between as you have suggested?
Not to mention free heating. I am struggling to detect any heat emanating from my M1 MBA on my laptop even after consecutive hours on zoom. Practically freezing. 😕
Yes, if device A does well on GB6 MC, it would also do well on GB5 MC. But this doesn't account for comparative assessment.
It's usually more about the task itself than the hardware. Most tasks parallelize well up to certain number of cores but get diminishing returns from further parallelization. In many consumer tasks, the threshold can be as low as 2-4 cores. There may be a limited number of independent subtasks that you can run in parallel, or there may be sequential parts that don't benefit from any parallelization. In the kind of bioinformatics stuff I do at work, you can usually parallelize over 16-32 cores before you start running into I/O or synchronization bottlenecks.
That's a reasonable point. And it also raises an interesting question: Just how far does GB6 take it, i.e., are all it's MC tasks ones with significant intedependencies, or are there are mix between those an embarrasingly parallel tasks? And of the ones in the former category, how challening are their interdependencies as compared with the most-used MC apps?
Call us when you can get that power in a laptop, unplugged from the wall.
Doing a task in parallel corresponds more to efficient and fast memory management, while having an IPC that can take advantage of the apis.
Why do you have to compare them all the time? It is clear that intel and amd with the most powerful graphics cards will always be better than m-chips with different consoles, no matter how ultra, no matter maxi, no matter hyper.
Custom air and water cooling solves all high temp problems.
The key word here is "planning", and produces top-end Nvidia graphics cards.
