Can I Run Nemotron 3 Nano Omni 30B A3B Reasoning BF16 on a Apple M2 Max (64GB)?
Runs at full precision (fp16). Zero quality loss.
5 quantizations fit your 64.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| fp16BEST | 61.0 GB | 62.5 GB | 60.0 GB | +3.0 GB |
| Q8_0 | 32.9 GB | 34.4 GB | 31.9 GB | +31.1 GB |
| Q6_K | 25.7 GB | 27.2 GB | 24.7 GB | +38.3 GB |
| Q5_K_M | 22.3 GB | 23.8 GB | 21.3 GB | +41.7 GB |
| Q4_K_M | 19.2 GB | 20.7 GB | 18.2 GB | +44.8 GB |
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FAQ
Can the Apple M2 Max (64GB) run Nemotron 3 Nano Omni 30B A3B Reasoning BF16?
Yes. The Apple M2 Max (64GB)'s 64.0GB of unified memory is enough to run Nemotron 3 Nano Omni 30B A3B Reasoning BF16 at fp16 quantization (61.0GB required).
What's the best quantization to use?
fp16 is the highest-precision quantization that fits in your 64.0GB. It uses about 61.0GB of memory and 62.5GB 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.