Can I run DeepSeek R1 14B?

DeepSeek R1 14B is a reasoning model, not a quick-chat companion. At 14.8B parameters it sits in the awkward middle: a 4-bit quant lands around 9 GB, which spills past a 12 GB card once you add context, and the recommended minimum is 16 GB of RAM. It runs cleanly on a 24 GB GPU like an RTX 4090 or a higher-memory Apple Silicon Mac, but on a 12 GB RTX 3060 you are right at the edge. The MIT license is the easy part: freely usable, including commercially, with no provider strings attached.

In daily use it thinks out loud before answering, so expect long chains of reasoning tokens on every prompt. On an RTX 4090 you get around 95 tok/s, fast enough that the reasoning streams by; on an RTX 3060 it drops to about 34 tok/s and on an M-Max Mac roughly 39 tok/s, where those long traces start to feel slow. The 128K context is real but expensive: filling it pushes total memory to about 31.1 GB, far beyond any 16 GB setup, so keep working context modest unless you have a 32 GB-plus machine.

Against Qwen 3 14B, which carries the same 14.8B parameter count but handles plain chat too, R1 14B is the more specialised pick: it generally rewards you on multi-step math and logic but feels heavy-handed for simple back-and-forth, where Qwen tends to be quicker and more direct. Its standout trait is transparent reasoning at a size you can actually self-host. If you want the same approach lighter, DeepSeek R1 7B drops to roughly half the parameters and fits more comfortably on a 12 GB card.