I use Virtual Machines and run local LLMs. LLMs need VRAM rather than CPU RAM. You shouldn’t be doing it on a laptop without a serious NPU or GPU, if at all. I don’t know if I will be using VMs heavily on this machine or not, but that would be a good reason to have more RAM. Even so 32 GiB should be enough for a few VMs running concurrently.
Honestly, I think that for many people, if they’re using a laptop or phone, doing LLM stuff remotely makes way more sense. It’s just too power-intensive to do a lot of that on battery. That doesn’t mean not-controlling the hardware – I keep a machine with a beefy GPU connected to the network, can use it remotely. But something like Stable Diffusion normally requires only pretty limited bandwidth to use remotely.
If people really need to do a bunch of local LLM work, like they have a hefty source of power but lack connectivity, or maybe they’re running some kind of software that needs to move a lot of data back and forth to the LLM hardware, I think I might consider lugging around a small headless LLM box with a beefy GPU and a laptop, plug the LLM box into the laptop via Ethernet or whatnot, and do the LLM stuff on the headless box. Laptops are just not a fantastic form factor for heavy crunching; they’ve got limited ability to dissipate heat and tight space constraints to work with.
Yeah it is easier to do it on a desktop or over a network. That’s what I was trying to imply. Although having an NPU can help. Regardless I would rather be using my own server than something like ChatGPT.
If games, modding uses a lot. It can go to the point of needing more than 32gb, but rarely so.
Usually, you’d want 64gb or more for things like video editing, 3d modeling, running simulations, LLMs, or virtual machines.
I use Virtual Machines and run local LLMs. LLMs need VRAM rather than CPU RAM. You shouldn’t be doing it on a laptop without a serious NPU or GPU, if at all. I don’t know if I will be using VMs heavily on this machine or not, but that would be a good reason to have more RAM. Even so 32 GiB should be enough for a few VMs running concurrently.
That’s fair. I’ve put it there as more of a possible use case rather than something you should be consistently doing.
Although iGPU can perform quite well when given a lot of RAM, afaik.
Honestly, I think that for many people, if they’re using a laptop or phone, doing LLM stuff remotely makes way more sense. It’s just too power-intensive to do a lot of that on battery. That doesn’t mean not-controlling the hardware – I keep a machine with a beefy GPU connected to the network, can use it remotely. But something like Stable Diffusion normally requires only pretty limited bandwidth to use remotely.
If people really need to do a bunch of local LLM work, like they have a hefty source of power but lack connectivity, or maybe they’re running some kind of software that needs to move a lot of data back and forth to the LLM hardware, I think I might consider lugging around a small headless LLM box with a beefy GPU and a laptop, plug the LLM box into the laptop via Ethernet or whatnot, and do the LLM stuff on the headless box. Laptops are just not a fantastic form factor for heavy crunching; they’ve got limited ability to dissipate heat and tight space constraints to work with.
Yeah it is easier to do it on a desktop or over a network. That’s what I was trying to imply. Although having an NPU can help. Regardless I would rather be using my own server than something like ChatGPT.