Can I Run QwQ 32B on a Apple M2 Ultra (64GB)?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
32.0B
GPU memory
64.0GB
Smallest quant
Q4_K_M
Best fit
Q8_0
4 quantizations fit your 64.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 35.0 GB | 36.5 GB | 34.0 GB | +29.0 GB |
| Q6_K | 27.4 GB | 28.9 GB | 26.4 GB | +36.6 GB |
| Q5_K_M | 23.7 GB | 25.2 GB | 22.7 GB | +40.3 GB |
| Q4_K_M | 20.4 GB | 21.9 GB | 19.4 GB | +43.6 GB |
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Full model details
QwQ 32B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
Apple M2 Ultra (64GB) →
Top-ranked open-source models that fit in 64.0GB.
FAQ
Can the Apple M2 Ultra (64GB) run QwQ 32B?
Yes. The Apple M2 Ultra (64GB)'s 64.0GB of unified memory is enough to run QwQ 32B at Q8_0 quantization (35.0GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 64.0GB. It uses about 35.0GB of memory and 36.5GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.