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aurareturn

3.5 - 4.5 tokens/s on the $2,000 AMD Epyc setup. Deepseek 671b q4.

The AMD Epyc build is severely bandwidth and compute constrained.

~40 tokens/s on M3 Ultra 512GB by my calculation.

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IMO, it would be more interesting to have a 3-way comparison of price/performance between DeepSeek 671b running on :

1. M3 Ultra 512 2. AMD Epyc (which Gen ? AVX512 and DDR5 might make a difference in both performance and cost , Gen 4 or Gen 5 have 8 or 9 t/s https://github.com/ggml-org/llama.cpp/discussions/11733 ) 2. AMD Epyc + 4090 or 5090 running KTransformers (over 10 t/s decode ? https://github.com/kvcache-ai/ktransformers/blob/main/doc/en...)

Thanks!

If the M3 can run 24/7 without overheating it's a great deal to run agents. Especially considering that it should run only using 350W... so roughly $50/mo in electricity costs.

Out of curiosity, if you dont mind: what kind of an agent would you run 24/7 locally?

I'd assume this thing peaks at 350W (or whatever) but idles at around 40w tops?

I’m guessing they might be thinking long training jobs as opposed to model use in an end product if done sort.

What kind of Nvidia-based rig would one need to achieve 40 tokens/sec on Deepseek 671b? And how much would it cost?

Around 5x Nvidia A100 80GB can fit 671b Q4. $50k just for the GPUs and likely much more when including cooling, power, motherboard, CPU, system RAM, etc.

So the M3 Ultra is amazing value then. And from what I could tell, an equivalent AMD Epyc would still be so constrained that we're talking 4-5 tokens/s. Is this a fair assumption?

The Epyc would only set you back $2000 though, so it’s only a slightly worse price/return.

No. The advantage of Epic is you get 12 channels of ram so it should be ~6x faster than a consumer cpu.

I realize that but apparently people are still getting very low tokens/sec on Epyc. Why is that? I don't get it, as on paper it should be fast.

How many tokens/s would that be though?

That's what I'm trying to get to. Looking to set up a rig, and AMD Epyc seems reasonable but I'd rather go Mac if it's giving many more tokens per second. It does sound like the Mac with M3 Ultra will easily give 40 tokens/s, where as the Epyc is just internally constrained too much, giving 4-5 tokens/s but I'd like someone to confirm that, instead of buying the HW and finding out myself. :)

Probably a lot more. Those are server-grade GPUs. We're talking prosumer grade Macs.

I don't know how to calculate tokens/s for H100s linked together. ChatGPT might help you though. :)

Well, ChatGPT quotes 25k-75k tokens/s with 5 H100 (so very very far from the 40 tokens/s), but I doubt this is accurate (e.g. it completly ignored the fact they are linked together and instead just multiplied the estimation of the tokens/s for one H100 by 5).

If this is remotely accurate though it's still at least an order of magnitude more convenient than the M3 Ultra, even after factoring in all the other costs associated with the infrastructure.

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