Can I run NVIDIA Nemotron 3 Nano 30B A3B (MoE) locally?
NVIDIA Nemotron 3 Nano 30B A3B (MoE) has 31.58 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 20.7 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2025-12-04. It's a mixture-of-experts model: all weights must fit in memory, but it generates faster than a dense model of the same size.
Memory needed by quantization
| Quant | Weights | Total needed (est.) |
|---|---|---|
| IQ1_S | 6.2 GB | 7.1 GB |
| IQ2_XXS | 8.1 GB | 9.2 GB |
| IQ2_M | 10.7 GB | 11.8 GB |
| Q2_K | 12.5 GB | 13.8 GB |
| IQ3_XXS | 12.1 GB | 13.3 GB |
| Q3_K_S | 14.4 GB | 15.8 GB |
| IQ3_M | 14.4 GB | 15.8 GB |
| Q3_K_M | 15.8 GB | 17.2 GB |
| IQ4_XS | 16.8 GB | 18.2 GB |
| Q4_0 | 17.8 GB | 19.3 GB |
| Q4_K_M | 19.1 GB | 20.7 GB |
| MXFP4 | 18.3 GB | 19.8 GB |
| Q5_K_M | 22.5 GB | 24.2 GB |
| Q6_K | 25.9 GB | 27.8 GB |
| Q8_0 | 33.6 GB | 35.9 GB |
| F16 | 63.2 GB | 66.9 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 0.03 GB | 0.01 GB | 0.01 GB |
| 8k | 0.05 GB | 0.03 GB | 0.01 GB |
| 16k | 0.10 GB | 0.05 GB | 0.03 GB |
| 32k | 0.20 GB | 0.11 GB | 0.06 GB |
| 64k | 0.40 GB | 0.21 GB | 0.11 GB |
| 128k | 0.81 GB | 0.43 GB | 0.23 GB |
From config.json: 6 KV-caching attention layers, 2 KV heads × 128 head dim. Max context 256k. The tables above assume 4k context.
Which GPUs and Macs can run it?
✅ fits · ⚠️ fits with little headroom · ❌ doesn't fit on this one device (multiple GPUs or RAM offload may work; check your setup). Apple Silicon assumes macOS lets the GPU use ~67–75% of unified memory. All fit verdicts are estimates.
Get the weekly "new models & what it takes to run them" email
Free. One email a week. Unsubscribe anytime.