Can I run QwQ 32B?

QwQ 32B is Alibaba's reasoning specialist, not a general chat model, and that framing matters before you download anything. It is a dense 32.8B-parameter model that thinks out loud through long chains before answering, which makes it strong on math and multi-step problems but slow and verbose for quick questions. At a 4-bit quant it lands around 19.9 GB, so the 12 GB RTX 3060 simply will not hold it. You realistically want 32 GB of system or unified memory to run it at all, which puts it in workstation, 24 GB GPU, or higher-end Apple Silicon territory rather than a typical gaming card.

In daily use it feels deliberate rather than snappy. On an RTX 4090 you can expect roughly 43 tokens per second at 4-bit, which sounds fine until you remember this model spends most of those tokens reasoning before it reaches an answer, so a single hard prompt can run for a while. On an Apple M Max it drops to about 18 tokens per second, and on a DDR5 CPU it crawls near 3 tokens per second. The 128K context is genuine, but pushing it to the limit drives total memory to around 51.6 GB, well past the 32 GB floor, so keep working context modest unless you have the headroom.

Against DeepSeek R1 32B, the other dense 32B reasoner here, the two are close in footprint and intent, and which one wins tends to depend on the specific task rather than any clean blanket lead, so it is worth trying both. If you only have a few gigabytes, the tiny Qwen 3 0.6B or 1.7B chat models are a completely different tool, fine for quick replies but not for the deep reasoning QwQ is built for. QwQ's standout trait is delivering frontier-style step-by-step reasoning at a size you can self-host, and being Apache 2.0 it is free to use commercially with no licensing strings.