Have you thought about getting a second 128GB device? Open weights models are rapidly increasing in size, unfortunately.
replyConsidered getting a 512G mac studio, but I don't like Apple devices due to the closed software stack. I would never have gotten this Mac Studio if Strix Halo existed mid 2024.
replyFor now I will just wait for AMD or Intel to release a x86 platform with 256G of unified memory, which would allow me to run larger models and stick to Linux as the inference platform.
I aspire to casually ponder whether I need a $9,500 computer to run the latest Qwen model
replyYou'll need more since RAM prices are up thanks to AI.
replyWhy 128GB?
replyAt 80B, you could do 2 A6000s.
What device is 128gb?
Spark DGX and any A10 devices, strix halo with max memory config, several mac mini/mac studio configs, HP ZBook Ultra G1a, most servers
replyIf you're targeting end user devices then a more reasonable target is 20GB VRAM since there are quite a lot of gpu/ram/APU combinations in that range. (orders of magnitude more than 128GB).
AMD Strix Halo / Ryzen AI Max+ (in the Asus Flow Z13 13 inch "gaming" tablet as well as the Framework Desktop) has 128 GB of shared APU memory.
replyNot quite. They have 128GB of ram that can be allocated in the BIOS, up to 96GB to the GPU.
replyYou don't have to statically allocate the VRAM in the BIOS. It can be dynamically allocated. Jeff Geerling found you can reliably use up to 108 GB [1].
reply[1]: https://www.jeffgeerling.com/blog/2025/increasing-vram-alloc...
allocation is irrelevant. as an owner of one of these you can absolutely use the full 128GB (minus OS overhead) for inference workloads
replyCare to go into a bit more on machine specs? I am interested in picking up a rig to do some LLM stuff and not sure where to get started. I also just need a new machine, mine is 8y-o (with some gaming gpu upgrades) at this point and It's That Time Again. No biggie tho, just curious what a good modern machine might look like.
replyThose Ryzen AI Max+ 395 systems are all more or less the same. For inference you want the one with 128GB soldered RAM. There are ones from Framework, Gmktec, Minisforum etc. Gmktec used to be the cheapest but with the rising RAM prices its Framework noe i think. You cant really upgrade/configure them. For benchmarks look into r/localllama - there are plenty.
replyMinisforum, Gmktec also have Ryzen AI HX 370 mini PCs with 128Gb (2x64Gb) max LPDDR5. It's dirt cheap, you can get one barebone with ~€750 on Amazon (the 395 similarly retails for ~€1k)... It should be fully supported in Ubuntu 25.04 or 25.10 with ROCm for iGPU inference (NPU isn't available ATM AFAIK), which is what I'd use it for. But I just don't know how the HX 370 compares to eg. the 395, iGPU-wise. I was thinking of getting one to run Lemonade, Qwen3-coder-next FP8, BTW... but I don't know how much RAM should I equip it with - shouldn't 96Gb be enough? Suggestions welcome!
replyRyzen AI HX 370 is not what you want, you need strix halo APU with unified memory
replyKeep in mind most of the Strix Halo machines are limited to 10Gbe networking at best.
replyyou can use separate network adapter with RoCEv2/RDMA support like Intel E810
replyThat's the maximum you can get for $3k-$4k with ryzen max+ 395 and apple studio Ms. They're cheaper than dedicated GPUs by far.
replyMac Studios or Strix Halo. GPT-OSS 120b, Qwen3-Next, Step 3.5-Flash all work great on a M1 Ultra.
replyAll the GB10-based devices -- DGX Spark, Dell Pro Max, etc.
replyGuess, it is mac m series
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