Lol, there are smaller versions of Deepseek-r1. These aren’t the “real” Deepseek model, but they are distilled from other foundation models (Qwen2.5 and Llama3 in this case).
For the 671b parameter file, the medium-quality version weighs in at 404 GB. That means you need 404 GB of RAM/VRAM just to load the thing. Then you need preferably ALL of that in VRAM (i.e. GPU memory) to get it to generate anything fast.
For comparison, I have 16 GB of VRAM and 64 GB of RAM on my desktop. If I run the 70b parameter version of Llama3 at Q4 quant (medium quality-ish), it’s a 40 GB file. It’ll run, but mostly on the CPU. It generates ~0.85 tokens per second. So a good response will take 10-30 minutes. Which is fine if you have time to wait, but not if you want an immediate response. If I had two beefy GPUs with 24 GB VRAM each, that’d be 48 total GB and I could run the whole model in VRAM and it’d be very fast.
That was entirely the point unfortunately.