Can I Run Nemotron 3 Nano Omni 30B A3B Reasoning BF16 on a NVIDIA RTX 6000 Ada?
Runs at Q8_0 — near-lossless quality.
4 quantizations fit your 48.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 32.9 GB | 34.4 GB | 31.9 GB | +15.1 GB |
| Q6_K | 25.7 GB | 27.2 GB | 24.7 GB | +22.3 GB |
| Q5_K_M | 22.3 GB | 23.8 GB | 21.3 GB | +25.7 GB |
| Q4_K_M | 19.2 GB | 20.7 GB | 18.2 GB | +28.8 GB |
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FAQ
Can the NVIDIA RTX 6000 Ada run Nemotron 3 Nano Omni 30B A3B Reasoning BF16?
Yes. The NVIDIA RTX 6000 Ada's 48.0GB of VRAM is enough to run Nemotron 3 Nano Omni 30B A3B Reasoning BF16 at Q8_0 quantization (32.9GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 48.0GB. It uses about 32.9GB of memory and 34.4GB 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.