Can I Run / gemma 4 12B it / on Apple M1 Ultra (128GB)

Can I Run gemma 4 12B it on a Apple M1 Ultra (128GB)?

Yes

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

Model size
12.0B
GPU memory
128GB
Smallest quant
Q2_K
Best fit
f32

14 quantizations fit your 128GB

QuantMin VRAMRecommendedFile sizeHeadroom
f32BEST49.0 GB50.5 GB0.2 GB+79.0 GB
fp1625.0 GB26.5 GB0.9 GB+103.0 GB
Q8_013.8 GB15.3 GB0.5 GB+114.3 GB
Q6_K10.9 GB12.4 GB9.8 GB+117.1 GB
Q5_K_M9.5 GB11.0 GB8.4 GB+118.5 GB
Q5_K_S9.3 GB10.8 GB8.2 GB+118.7 GB
Q4_18.5 GB10.0 GB7.4 GB+119.5 GB
Q4_K_M8.3 GB9.8 GB7.1 GB+119.7 GB
Q4_K_S7.9 GB9.4 GB6.8 GB+120.1 GB
Q4_07.8 GB9.3 GB6.7 GB+120.3 GB
Q3_K_L6.3 GB7.8 GB6.7 GB+121.7 GB
Q3_K_M6.0 GB7.5 GB5.7 GB+122.0 GB
Q3_K_S5.6 GB7.1 GB5.1 GB+122.4 GB
Q2_K5.0 GB6.5 GB5.1 GB+123.0 GB

Try it in the cloud first

Don't want to download gemma 4 12B it just to try it? Use a hosted API or rent a GPU by the second.

Affiliate links — we earn a commission at no cost to you.

Advertisement
Full model details
gemma 4 12B it

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 12B it?

Yes. The Apple M1 Ultra (128GB)'s 128GB of unified memory is enough to run gemma 4 12B it at f32 quantization (49.0GB required).

What's the best quantization to use?

f32 is the highest-precision quantization that fits in your 128GB. It uses about 49.0GB of memory and 50.5GB 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.