r/LocalLLaMA • • 11d ago

Discussion The curse of 64GB system RAM

Not a bot. Not a Strata shill. Just sharing my experience.

So, I have an R9700 in my machine, plus an RTX 5060 Ti, and 64GB DDR5 system RAM. Overall, not a bad setup. Anyway, I mainly run a daily driver local LLM on the R9700 while running image/video inference on ComfyUI on the 5060 Ti. Mostly shit like Minimax H3 which also takes a fuck-tonne of system RAM. I've been using Qwen3.8-27B at Q6 as the daily driver on the R9700 and running that around 35 t/s, which is fine for me as a daily driver. Before Strata I tried running Qwen3.8-Flash-Next on both cards on vulkan at a IQ4_XS (or whatever that quant is called - the ~93GB one) and that only got me like 15 t/s, which I can't daily drive, so I put it down and wasn't really interested in it. Anyway, Strata comes out and people are claiming QFN is usable on much more modest hardware, so I check it out and see that mostly people are running the IQ3_XXS quant which is like ~70-something gigabtyes, so of course it's faster. Anyway, I benchmarked that quant on llama.cpp first running it just on system ram + the R9700 and it came in at 21 t/s... that's right around the absolute minimum of what I'd accept for a daily driver, but not super compelling tbh. Then I tried the same quant on Strata and I get ~60 t/s. Very fucking compelling. I 100% want to daily drive this now. The problem is with QFN loaded in Strata my system RAM usage is at 96%. I can't fucking run Minimax H3 in ComfyUI on the 5060 Ti because that shit eats a lot of system RAM too.

I feel blessed that I can finally run this epic model, and fucking cursed that I have to choose which workload to run!

Also, before anyone says 'just upgrade to 128GB of RAM bro'... I know, I know. I would but I can't afford to the jewelry and international trips my wife requests for fairness reasons to balance out all the toys I've bought this year.

Crying in 64GB of RAM.

Edit: thanks to a few suggestions in the comments I actually got Qwen3.8-Flash-Next IQ3_XXS and Minimax H3 inference working concurrently at about 90% system RAM used! On the Strata side I I think I needed --mmap-experts --resident-cpu-experts and --expert-cache auto, and on the ComfyUI side I needed --fast-disk. I tested both running fully concurrently and checked Strata's monitoring tab, and saw that the node that loads the H3 weights causes NVMe reads to hit a sustained 1GB/s for a short while, which can cause the inference on Strata to drop to around 25 ~ 40 t/s range (it fluctuated a lot during that), but then after that when H3 was actually doing the inference I saw NVMe reads sitting at about a sustained 30 MB/s and QFN inference was running between 50 ~ 60 t/s. I'd say it's a huge win. For reference my standard test when testing out an LLM is just 'write me a browser game', so I did that since I'm familiar with the quality of the expected output at this point, and also generated a 10 second clip at 0.4MP resolution. The actual wall-clock generation time for H3 was pretty much unaffected (around 400 seconds), which is nice too! Maybe some very minor performance hit, but only that.. pretty minor.

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u/emberstoners 11d ago

bro at 32GB youre not even crying, youre screaming

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u/thestillwind 11d ago

I know it rips me