Can I Run Nemotron 3 Nano Omni (free) on a NVIDIA RTX 5000 Ada?
Runs comfortably at Q6_K — minimal quality loss.
2 quantizations fit your 32.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 28.2 GB | 29.7 GB | 33.5 GB | +3.8 GB |
| Q4_K_M | 21.0 GB | 22.5 GB | 24.5 GB | +11.0 GB |
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Top-ranked open-source models that fit in 32.0GB.
FAQ
Can the NVIDIA RTX 5000 Ada run Nemotron 3 Nano Omni (free)?
Yes. The NVIDIA RTX 5000 Ada's 32.0GB of VRAM is enough to run Nemotron 3 Nano Omni (free) at Q6_K quantization (28.2GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 32.0GB. It uses about 28.2GB of memory and 29.7GB 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.