Can I Run / Gemma 4 31B / on Apple M1 Ultra (128GB)

Can I Run Gemma 4 31B on a Apple M1 Ultra (128GB)?

Yes

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

Model size
31.3B
GPU memory
128GB
Smallest quant
Q3_K_S
Best fit
f32

12 quantizations fit your 128GB

QuantMin VRAMRecommendedFile sizeHeadroom
f32BEST126.2 GB127.7 GB2.3 GB+1.8 GB
fp1663.6 GB65.1 GB0.9 GB+64.4 GB
Q8_034.3 GB35.8 GB0.5 GB+93.7 GB
Q6_K26.8 GB28.3 GB25.2 GB+101.2 GB
Q5_K_M23.2 GB24.7 GB21.7 GB+104.8 GB
Q5_K_S22.6 GB24.1 GB21.1 GB+105.4 GB
Q4_120.6 GB22.1 GB19.1 GB+107.4 GB
Q4_K_M20.0 GB21.5 GB18.3 GB+108.0 GB
Q4_K_S18.9 GB20.4 GB17.4 GB+109.1 GB
Q4_018.6 GB20.1 GB17.3 GB+109.4 GB
Q3_K_M14.1 GB15.6 GB14.7 GB+113.9 GB
Q3_K_S13.1 GB14.6 GB13.2 GB+115.0 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 M1 Ultra (128GB)

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

FAQ

Can the Apple M1 Ultra (128GB) run Gemma 4 31B?

Yes. The Apple M1 Ultra (128GB)'s 128GB of unified memory is enough to run Gemma 4 31B at f32 quantization (126.2GB required).

What's the best quantization to use?

f32 is the highest-precision quantization that fits in your 128GB. It uses about 126.2GB of memory and 127.7GB 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.