Can I Run / gemma 4 31B / on Apple M5 Ultra (512GB)

Can I Run gemma 4 31B on a Apple M5 Ultra (512GB)?

Yes

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

Model size
32.7B
GPU memory
512GB
Smallest quant
Q2_K
Best fit
fp16

11 quantizations fit your 512GB

QuantMin VRAMRecommendedFile sizeHeadroom
fp16BEST66.4 GB67.9 GB1.2 GB+445.6 GB
Q8_035.7 GB37.2 GB32.6 GB+476.3 GB
Q6_K27.9 GB29.4 GB25.2 GB+484.1 GB
Q5_K_M24.2 GB25.7 GB21.9 GB+487.8 GB
Q5_K_S23.6 GB25.1 GB21.3 GB+488.4 GB
Q4_K_M20.8 GB22.3 GB18.7 GB+491.2 GB
Q4_K_S19.7 GB21.2 GB17.8 GB+492.3 GB
Q3_K_L15.6 GB17.1 GB16.6 GB+496.4 GB
Q3_K_M14.7 GB16.2 GB15.3 GB+497.3 GB
Q3_K_S13.6 GB15.1 GB13.8 GB+498.4 GB
Q2_K11.8 GB13.3 GB11.9 GB+500.3 GB

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Full model details
gemma 4 31B

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

Best models for this GPU
Apple M5 Ultra (512GB)

Top-ranked open-source models that fit in 512GB.

FAQ

Can the Apple M5 Ultra (512GB) run gemma 4 31B?

Yes. The Apple M5 Ultra (512GB)'s 512GB of unified memory is enough to run gemma 4 31B at fp16 quantization (66.4GB required).

What's the best quantization to use?

fp16 is the highest-precision quantization that fits in your 512GB. It uses about 66.4GB of memory and 67.9GB 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.