Can I Run / Gemma 4 31B / on Apple M3 Pro (36GB)
Can I Run Gemma 4 31B on a Apple M3 Pro (36GB)?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
31.3B
GPU memory
36.0GB
Smallest quant
Q3_K_S
Best fit
Q8_0
10 quantizations fit your 36.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 34.3 GB | 35.8 GB | 0.5 GB | +1.7 GB |
| Q6_K | 26.8 GB | 28.3 GB | 25.2 GB | +9.2 GB |
| Q5_K_M | 23.2 GB | 24.7 GB | 21.7 GB | +12.8 GB |
| Q5_K_S | 22.6 GB | 24.1 GB | 21.1 GB | +13.4 GB |
| Q4_1 | 20.6 GB | 22.1 GB | 19.1 GB | +15.4 GB |
| Q4_K_M | 20.0 GB | 21.5 GB | 18.3 GB | +16.0 GB |
| Q4_K_S | 18.9 GB | 20.4 GB | 17.4 GB | +17.1 GB |
| Q4_0 | 18.6 GB | 20.1 GB | 17.3 GB | +17.4 GB |
| Q3_K_M | 14.1 GB | 15.6 GB | 14.7 GB | +21.9 GB |
| Q3_K_S | 13.1 GB | 14.6 GB | 13.2 GB | +22.9 GB |
Try it in the cloud first
Don't want to download Gemma 4 31B 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 31B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
Apple M3 Pro (36GB) →
Top-ranked open-source models that fit in 36.0GB.
FAQ
Can the Apple M3 Pro (36GB) run Gemma 4 31B?
Yes. The Apple M3 Pro (36GB)'s 36.0GB of unified memory is enough to run Gemma 4 31B at Q8_0 quantization (34.3GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 36.0GB. It uses about 34.3GB of memory and 35.8GB 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.