Can I Run NVIDIA Nemotron 3 Super on a Apple M5 Ultra (256GB)?
Runs at Q5_K_M — good quality with reasonable headroom.
10 quantizations fit your 256GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q5_K_MBEST | 242.4 GB | 243.9 GB | 35.4 GB | +13.6 GB |
| Q5_K_S | 235.6 GB | 237.1 GB | 34.4 GB | +20.4 GB |
| Q4_1 | 213.5 GB | 215.0 GB | 31.4 GB | +42.5 GB |
| Q4_K_M | 207.1 GB | 208.6 GB | 30.2 GB | +48.9 GB |
| Q4_K_S | 195.7 GB | 197.2 GB | 28.6 GB | +60.3 GB |
| Q4_0 | 192.3 GB | 193.8 GB | 28.5 GB | +63.8 GB |
| Q3_K_L | 152.3 GB | 153.8 GB | 26.3 GB | +103.7 GB |
| Q3_K_M | 143.4 GB | 144.9 GB | 24.3 GB | +112.6 GB |
| Q3_K_S | 131.9 GB | 133.4 GB | 22.0 GB | +124.1 GB |
| Q2_K | 112.8 GB | 114.3 GB | 18.7 GB | +143.2 GB |
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All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 256GB.
FAQ
Can the Apple M5 Ultra (256GB) run NVIDIA Nemotron 3 Super?
Yes. The Apple M5 Ultra (256GB)'s 256GB of unified memory is enough to run NVIDIA Nemotron 3 Super at Q5_K_M quantization (242.4GB required).
What's the best quantization to use?
Q5_K_M is the highest-precision quantization that fits in your 256GB. It uses about 242.4GB of memory and 243.9GB 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.