Can I Run NVIDIA Nemotron 3 Super 120B A12B BF16 on a Apple M2 Ultra (192GB)?
Runs at Q8_0 — near-lossless quality.
4 quantizations fit your 192GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 132.3 GB | 133.8 GB | 131.3 GB | +59.7 GB |
| Q6_K | 102.8 GB | 104.3 GB | 101.8 GB | +89.2 GB |
| Q5_K_M | 88.8 GB | 90.3 GB | 87.8 GB | +103.2 GB |
| Q4_K_M | 75.9 GB | 77.4 GB | 74.9 GB | +116.1 GB |
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Top-ranked open-source models that fit in 192GB.
FAQ
Can the Apple M2 Ultra (192GB) run NVIDIA Nemotron 3 Super 120B A12B BF16?
Yes. The Apple M2 Ultra (192GB)'s 192GB of unified memory is enough to run NVIDIA Nemotron 3 Super 120B A12B BF16 at Q8_0 quantization (132.3GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 192GB. It uses about 132.3GB of memory and 133.8GB 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.