Can I Run Qwen3 VL 32B Instruct on a Apple M3 Pro (36GB)?
Runs comfortably at Q6_K — minimal quality loss.
10 quantizations fit your 36.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 28.5 GB | 30.0 GB | 26.9 GB | +7.5 GB |
| Q5_K_M | 24.7 GB | 26.2 GB | 23.2 GB | +11.3 GB |
| Q5_K_S | 24.1 GB | 25.6 GB | 22.6 GB | +11.9 GB |
| Q4_1 | 21.9 GB | 23.4 GB | 20.6 GB | +14.1 GB |
| Q4_K_M | 21.3 GB | 22.8 GB | 19.8 GB | +14.8 GB |
| Q4_K_S | 20.1 GB | 21.6 GB | 18.8 GB | +15.9 GB |
| Q4_0 | 19.8 GB | 21.3 GB | 18.7 GB | +16.2 GB |
| Q3_K_M | 15.0 GB | 16.5 GB | 16.0 GB | +21.0 GB |
| Q3_K_S | 13.9 GB | 15.4 GB | 14.4 GB | +22.1 GB |
| Q2_K | 12.0 GB | 13.5 GB | 12.3 GB | +24.0 GB |
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All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 36.0GB.
FAQ
Can the Apple M3 Pro (36GB) run Qwen3 VL 32B Instruct?
Yes. The Apple M3 Pro (36GB)'s 36.0GB of unified memory is enough to run Qwen3 VL 32B Instruct at Q6_K quantization (28.5GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 36.0GB. It uses about 28.5GB of memory and 30.0GB 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.