Can I Run Llama 3.3 Nemotron Super 49B V1.5 on a Apple M2 Ultra (64GB)?
Runs at Q8_0 — near-lossless quality.
14 quantizations fit your 64.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 54.0 GB | 55.5 GB | 53.0 GB | +10.0 GB |
| Q6_K | 42.1 GB | 43.6 GB | 40.9 GB | +21.9 GB |
| Q5_1 | 38.4 GB | 39.9 GB | 37.4 GB | +25.6 GB |
| Q5_K_M | 36.4 GB | 37.9 GB | 35.4 GB | +27.6 GB |
| Q5_K_S | 35.4 GB | 36.9 GB | 34.4 GB | +28.6 GB |
| Q5_0 | 35.3 GB | 36.8 GB | 34.3 GB | +28.7 GB |
| Q4_1 | 32.2 GB | 33.7 GB | 31.4 GB | +31.8 GB |
| Q4_K_M | 31.3 GB | 32.8 GB | 30.2 GB | +32.8 GB |
| Q4_K_S | 29.6 GB | 31.1 GB | 28.6 GB | +34.4 GB |
| Q4_0 | 29.1 GB | 30.6 GB | 28.5 GB | +34.9 GB |
| Q3_K_L | 23.2 GB | 24.7 GB | 26.3 GB | +40.8 GB |
| Q3_K_M | 21.9 GB | 23.4 GB | 24.3 GB | +42.1 GB |
| Q3_K_S | 20.2 GB | 21.7 GB | 22.0 GB | +43.8 GB |
| Q2_K | 17.4 GB | 18.9 GB | 18.7 GB | +46.6 GB |
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All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 64.0GB.
FAQ
Can the Apple M2 Ultra (64GB) run Llama 3.3 Nemotron Super 49B V1.5?
Yes. The Apple M2 Ultra (64GB)'s 64.0GB of unified memory is enough to run Llama 3.3 Nemotron Super 49B V1.5 at Q8_0 quantization (54.0GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 64.0GB. It uses about 54.0GB of memory and 55.5GB 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.