NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 GPU Requirements: VRAM & Cheapest GPU
NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 has about 31.6B parameters. See exactly how much GPU memory it needs at FP16, INT8, and INT4, and the cheapest GPU to run it, with live hourly pricing from 5+ data center partners.
To run NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 for inference at FP16, you need roughly 69 GB of VRAM. The cheapest fit on Spheron is A100 80GB at about $0.82/hr. Quantize to INT4 to run it on a smaller, cheaper GPU.
Estimated peak VRAM including weights, activations, and KV cache. Add 10% headroom for production traffic.
- 01$0.82/hr$0.82/hr1× A100 80GBCHEAPESTAmpere · HBM2e
- 02$0.91/hr$0.91/hr1× RTX PRO 6000 96GBBlackwell · GDDR7
- 03$0.96/hr$1.92/hr2× L40S 48GBAda Lovelace · GDDR6
- 04$2.01/hr$2.01/hr1× H100 80GBHopper · HBM3
- 05$0.65/hr$2.60/hr4× RTX 4090 24GBAda Lovelace · GDDR6X
Live pricing aggregated from 5+ data center partners. Per-minute billing, no commitments.
VRAM required to run NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
Estimated peak VRAM at context length 4,096 and batch size 1, including weights, activations, and KV cache. Quantizing to INT8 (Q8) or INT4 (Q4) cuts memory roughly in half and in quarter.
| Precision | Inference | LoRA fine-tune | Full fine-tune |
|---|---|---|---|
| FP16 | 69 GB | 103 GB | 275 GB |
| INT8 | 34 GB | 52 GB | 138 GB |
| INT4 | 17 GB | 26 GB | 69 GB |
Cheapest GPU to run NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 by precision
Full precision. Best quality, highest memory.
8-bit quantized. ~2x smaller, minimal quality loss.
4-bit quantized. ~4x smaller, runs on smaller GPUs.
Inference vs fine-tuning NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
Inference only holds the model weights plus a KV cache, so it is the cheapest setup. LoRA fine-tuning adds a small adapter and roughly 50% more memory. Full fine-tuning holds gradients and optimizer state on top of the weights, which is about 4x the inference footprint, so it often needs multiple GPUs even when inference fits on one. For NVIDIA-Nemotron-3-Nano-30B-A3B-BF16, an on-demand A100 80GB instance covers inference and LoRA, while a full fine-tune needs several times that memory and often spans multiple GPUs. Check the live GPU pricing for current rates.
Deployment guideDeploy Nemotron 3 Super step by stepHands-on production setup, GPU configs, and benchmarks for NVIDIA-Nemotron-3-Nano-30B-A3B-BF16.Read guideSimilar models
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