I'm going to ballpark it between 2.5-3x faster than the desktop. Except for the tg128 test, where the difference is "minimal" (but I didn't do the math).
jeffbee · 1h ago
I had been hoping that these would be a bit faster than the 9950X because of the different memory architecture, but it appears that due to the lower power design point the AI Max+ 395 loses across the board, by large margins. So I guess these really are niche products for ML users only, and people with generic workloads that want more than the 9950X offers are shopping for a Threadripper.
dijit · 1h ago
Sounds about right.
I’m struggling to justify the cost of a Threadripper (let alone pro!) for a AAA game studio though.
I wonder who can justify these machines. High frequency trading? data science? shouldn’t that be done on servers?
kadoban · 19m ago
Threadripper very rarely seems to make any sense. The only times it seems like you want it are for huge memory support/bandwidth and/or a huge number of pcie slots. But it's not cheap or supported enough compared to epyc to really make sense to me any time I've been specing out a system along those lines.
jeffbee · 24m ago
Yeah I don't get it either. To get marginally more resources than the 9950X you have to make a significant leap in price to a $1500+ CPU on a $1000 motherboard.
rtkwe · 34m ago
It also seems like the tools aren't there to fully utilize them. Unless I misunderstood he was running off CPU only for all the test so there's still the iGPU and NPU performance that's not been utilized in these tests.
geerlingguy · 27m ago
No, only a couple initial tests with Ollama used CPU. I ran most tests on Vulkan / iGPU, and some on ROCm (read further down the thread).
I found it difficult to install ROCm on Fedora 42 but after upgrading to Rawhide it was easy, so I re-tested everything with ROCm vs Vulkan.
Ollama, for some silly reason, doesn't support Vulkan even though I've used a fork many times to get full GPU acceleration with it on Pi, Ampere, and even this AMD system... (moral of the story just stick with llama.cpp).
No experimental flag option, no "you can use the fork that works fine but we don't have capacity to support this" just a hard "no, we think it's unreliable". I guess they just want you to drop them and use llama.cpp.
Comparing it against the RTX 4000 SFF Ada (20GB) which is around $1.2k (if you believe the original price on the nvidia website https://marketplace.nvidia.com/en-us/enterprise/laptops-work...). Which I have access to on a Hetzner GEX44.
I'm going to ballpark it between 2.5-3x faster than the desktop. Except for the tg128 test, where the difference is "minimal" (but I didn't do the math).
I’m struggling to justify the cost of a Threadripper (let alone pro!) for a AAA game studio though.
I wonder who can justify these machines. High frequency trading? data science? shouldn’t that be done on servers?
I found it difficult to install ROCm on Fedora 42 but after upgrading to Rawhide it was easy, so I re-tested everything with ROCm vs Vulkan.
Ollama, for some silly reason, doesn't support Vulkan even though I've used a fork many times to get full GPU acceleration with it on Pi, Ampere, and even this AMD system... (moral of the story just stick with llama.cpp).
https://x.com/ollama/status/1952783981000446029
No experimental flag option, no "you can use the fork that works fine but we don't have capacity to support this" just a hard "no, we think it's unreliable". I guess they just want you to drop them and use llama.cpp.