Can I Run / Qwen3 VL 32B Instruct / on Apple M4 (32GB)

Can I Run Qwen3 VL 32B Instruct on a Apple M4 (32GB)?

Yes

Runs comfortably at Q6_K — minimal quality loss.

Model size
33.4B
GPU memory
32.0GB
Smallest quant
Q2_K
Best fit
Q6_K

10 quantizations fit your 32.0GB

QuantMin VRAMRecommendedFile sizeHeadroom
Q6_KBEST28.5 GB30.0 GB26.9 GB+3.5 GB
Q5_K_M24.7 GB26.2 GB23.2 GB+7.3 GB
Q5_K_S24.1 GB25.6 GB22.6 GB+7.9 GB
Q4_121.9 GB23.4 GB20.6 GB+10.1 GB
Q4_K_M21.3 GB22.8 GB19.8 GB+10.8 GB
Q4_K_S20.1 GB21.6 GB18.8 GB+11.9 GB
Q4_019.8 GB21.3 GB18.7 GB+12.2 GB
Q3_K_M15.0 GB16.5 GB16.0 GB+17.0 GB
Q3_K_S13.9 GB15.4 GB14.4 GB+18.1 GB
Q2_K12.0 GB13.5 GB12.3 GB+20.0 GB

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Full model details
Qwen3 VL 32B Instruct

All quant variants, benchmark scores, and use-case tags.

Best models for this GPU
Apple M4 (32GB)

Top-ranked open-source models that fit in 32.0GB.

FAQ

Can the Apple M4 (32GB) run Qwen3 VL 32B Instruct?

Yes. The Apple M4 (32GB)'s 32.0GB 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 32.0GB. 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.