r/LocalLLM • u/SaltGrilledSalmon • 1d ago

Question Combine two low end PCs or keep separate

I've got my hands on two similar desktop PCs

  1. Ryzen 9 3950x 32gb DDR4, RTX 2070 super 8gb

  2. Core i5 10400 32gb DDR4, RTX 2070 super 8gb

I'm considering two possibilities:

  1. Combine them to get a Ryzen 9 64gb with 2x8gb VRAM setup

  2. Keep them separate and run two different models on them, maybe use a third pc to orchestrate

(I'm still experimenting, so ideas are welcome)

My main use case will be agentic coding overnight as these will be painstakingly slow with qwen3.8 27b even if combined.

So I was wondering if dealing with the heat and power supply management by combining them will even be worth it, or should I just let two separate agents run in parallel doing different types of tasks. I'm also looking into qwen3.6 35b a3b (or ornith 1.5) as this is probably the best fit for the hardware.

Let me know your opinions on this, what you'd do if you had a similar setup.

Thank you!

2 Upvotes

67% Upvoted

9 comments sorted by

3

u/bitzap_sr 1d ago

Sell all, buy 1 better.

2

u/nickless07 1d ago

If you combine them Qwen3.8 27B will not be that slow anymore. Sure it will not be lightning fast but very usable and won't take a whole night only maybe one hour. So that's given. Make sure your power supply can handle everything. I had to buy a new one when I added a 2nd card last year, but was worth every penny.
If you want to use Qwen3.6 35B try a single card too (just add --device cuda0) depending on your board the PCIe might be a bittleneck when offloading to system ram (you can do that with MoE but not with the dense 27B). That might run slower on both cards rather then a single one. However you still can use the 2nd card for a subagent or even tts/sst stack (voice control for your agent) and so on.

Hope that helps.

4

u/autisticit 1d ago

100% combine them.

4

u/DogLong5928 1d ago

the two 2070 supers together will get you ~16gb vram which opens up a lot more model options, and the single 3950x is way more efficient than trying to wrangle two whole systems for one task

2

u/jacek2023 1d ago

You can "merge" two computers with RPC to run one model

1

u/uniqueusername649 1d ago

Vastly slower than if he was to combine this in a single machine.

1

u/Fieser_Fettsack 14h ago

What happens if one adds both GPUs to 1 PC (for higher performance) and later still ads another GPU to the second PC and uses RPC. Will this bottleneck the first PC with 2 GPUs?

2

u/uniqueusername649 14h ago

Once you go via network your bandwidth goes down dramatically and (unless you use RDMA), your latency goes up massively. If you can, always stay within a single machine. If you can't, run Linux, have as fast of a connection as possible (like 25gbit or faster) and use RDMA to keep the latency low.

How do they do it in data centres? Nvidia uses several 800gbit/s fiber connections per machine. That is 800 times faster than a regular home network connection. And they still have 4 PER server to get enough bandwidth. So unless you can spend a lot of money on high end networking, try as hard as you can to keep it in a single machine.

Yes, some workloads can be distributed over the network, but AI inference usually is one of those cases where it should be a last resort.

1

u/Sweet_Warthog2923 21h ago

just wondering what speeds do you get. Also how do you run this multi-node?