I want to run a 70B LLM locally with more than 1 T/s. I have a 3090 with 24GB VRAM and 64GB RAM on the system.
What I managed so far:
- Found instructions to make 70B run on VRAM only with a 2.5B that run fast but the perplexity was unbearable. LLM was barely coherent.
- I randomly made somehow 70B run with a variation of RAM/VRAM offloading but it run with 0.1 T/S
I saw people claiming reasonable T/s speeds. Sine I am a newbie, I barely can speak the domain language, and most instructions I found assume implicit knowledge I don’t have*.
I need explicit instructions on what 70B model to download exactly, which Model loader to use and how to set parameters that are salient in the context.
If you’re only getting 0.1 then you’ve probably overshot your layer offloading.
I can get up to 1.5 t/s with a 3090, at 5_K_M
Try running Llama.cpp from the command line with 30 layers offloaded to the gpu, and make sure your thread count is set to match your (physical) CPU core count
The other problem you’re likely running into is that 64gb of RAM is cutting it pretty close. Make sure your base OS usage is below 8GB if possible and try memory locking the model on load. The problem is that with that amount of system ram, its possible you have other applications running causing the OS to page the model data out to disk, which kills performance
Thank you. What does " at 5_K_M" mean ?
Can I use the text web UI with Llama.cpp as model loader or is this too much overhead for ?
I actually don’t know how much overhead that’s going to be. I’d start by just kicking it off on the command line first as a proof of concept, its super easy,
5_K_M is just the quantization I use. There’s almost no loss of perplexity with 5_K_M, but its also larger than 4 which is what most people use.
Holy crap…
Yeah… I thought I’ll be at least “in the room “ buying my setup last year, but it turns out I’m outside in the gutter 🫣😢