Can I Run / Qwen3 VL 30B A3B Thinking / on Apple M3 Ultra (96GB)

Can I Run Qwen3 VL 30B A3B Thinking on a Apple M3 Ultra (96GB)?

Yes

Runs at full precision (fp16). Zero quality loss.

Model size
31.1B
GPU memory
96.0GB
Smallest quant
Q2_K
Best fit
fp16

12 quantizations fit your 96.0GB

QuantMin VRAMRecommendedFile sizeHeadroom
fp16BEST63.2 GB64.7 GB1.1 GB+32.8 GB
Q8_034.0 GB35.5 GB32.5 GB+62.0 GB
Q6_K26.6 GB28.1 GB25.1 GB+69.4 GB
Q5_K_M23.1 GB24.6 GB21.7 GB+72.9 GB
Q5_K_S22.5 GB24.0 GB21.1 GB+73.5 GB
Q4_120.4 GB21.9 GB19.2 GB+75.6 GB
Q4_K_M19.9 GB21.4 GB18.6 GB+76.2 GB
Q4_K_S18.8 GB20.3 GB17.5 GB+77.2 GB
Q4_018.5 GB20.0 GB17.4 GB+77.5 GB
Q3_K_M14.0 GB15.5 GB14.7 GB+82.0 GB
Q3_K_S13.0 GB14.5 GB13.3 GB+83.0 GB
Q2_K11.2 GB12.7 GB11.3 GB+84.8 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 M3 Ultra (96GB)

Top-ranked open-source models that fit in 96.0GB.

FAQ

Can the Apple M3 Ultra (96GB) run Qwen3 VL 30B A3B Thinking?

Yes. The Apple M3 Ultra (96GB)'s 96.0GB of unified memory is enough to run Qwen3 VL 30B A3B Thinking at fp16 quantization (63.2GB required).

What's the best quantization to use?

fp16 is the highest-precision quantization that fits in your 96.0GB. It uses about 63.2GB of memory and 64.7GB 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.