Can I Run / Qwen3 VL 30B A3B Thinking / on Apple M1 Ultra (128GB)

Can I Run Qwen3 VL 30B A3B Thinking on a Apple M1 Ultra (128GB)?

Yes

Runs at full precision (f32). Zero quality loss.

Model size
31.1B
GPU memory
128GB
Smallest quant
Q2_K
Best fit
f32

13 quantizations fit your 128GB

QuantMin VRAMRecommendedFile sizeHeadroom
f32BEST125.4 GB126.9 GB2.1 GB+2.6 GB
fp1663.2 GB64.7 GB1.1 GB+64.8 GB
Q8_034.0 GB35.5 GB32.5 GB+94.0 GB
Q6_K26.6 GB28.1 GB25.1 GB+101.4 GB
Q5_K_M23.1 GB24.6 GB21.7 GB+104.9 GB
Q5_K_S22.5 GB24.0 GB21.1 GB+105.5 GB
Q4_120.4 GB21.9 GB19.2 GB+107.6 GB
Q4_K_M19.9 GB21.4 GB18.6 GB+108.2 GB
Q4_K_S18.8 GB20.3 GB17.5 GB+109.2 GB
Q4_018.5 GB20.0 GB17.4 GB+109.5 GB
Q3_K_M14.0 GB15.5 GB14.7 GB+114.0 GB
Q3_K_S13.0 GB14.5 GB13.3 GB+115.0 GB
Q2_K11.2 GB12.7 GB11.3 GB+116.8 GB

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Full model details
Qwen3 VL 30B A3B Thinking

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

Best models for this GPU
Apple M1 Ultra (128GB)

Top-ranked open-source models that fit in 128GB.

FAQ

Can the Apple M1 Ultra (128GB) run Qwen3 VL 30B A3B Thinking?

Yes. The Apple M1 Ultra (128GB)'s 128GB of unified memory is enough to run Qwen3 VL 30B A3B Thinking at f32 quantization (125.4GB required).

What's the best quantization to use?

f32 is the highest-precision quantization that fits in your 128GB. It uses about 125.4GB of memory and 126.9GB 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.