What GPU do I need to run nvidia/NVIDIA-Nemotron-Nano-12B-v2?

12.3B parameters, published in BF16. View on Hugging Face

Set up NVIDIA-Nemotron-Nano-12B-v2
12.3B
Parameters
BF16
Native precision
Unknown
Architecture
text-generation
Pipeline

NVIDIA-Nemotron-Nano-12B-v2 is published by nvidia on Hugging Face, with 69,398 downloads and 164 likes to date. It's a unlisted-architecture model built for text-generation, published natively in BF16.

VRAM required & cheapest live GPU fit

Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.

Precision
Weight size
Required VRAM
Cheapest live fit
GPUs needed
Est. $/hr (full fit)
BF16
22.9 GB
27.5 GB
RTX A6000 (runpod)
1
$0.330/hr
cheaper alt.
RTX 3060 (simplepod)
3
$0.240/hr
FP8 (quantized)
11.5 GB
13.8 GB
RTX 4080 (akash)
1
$0.158/hr
INT4 (quantized)
5.7 GB
6.9 GB
RTX 3060 (simplepod)
1
$0.080/hr

A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.

INT4 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.

Cheapest way to run NVIDIA-Nemotron-Nano-12B-v2 at its published (BF16) precision: 1× RTX A6000 on runpod, at $0.330/hr per GPU ($0.330/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

NVIDIA-Nemotron-Nano-12B-v2: common questions

Does NVIDIA-Nemotron-Nano-12B-v2 fit on a 32 GB GPU?

Yes. At BF16 it needs 27.5 GB of VRAM, so a 32 GB card holds it with 4.5 GB to spare. A 24 GB card is not enough for it at BF16.

What is the least VRAM NVIDIA-Nemotron-Nano-12B-v2 can run in?

6.9 GB, at INT4 (quantized), which fits an 8 GB card, against 27.5 GB at BF16. That row assumes an INT4 checkpoint has actually been published for this model, so check its Hugging Face page before planning around it.

Does quantizing NVIDIA-Nemotron-Nano-12B-v2 lower the GPU bill?

Yes. At BF16 the cheapest live fit is one RTX A6000 on runpod at $0.330/hr. At INT4 (quantized) it drops to one RTX 3060 on simplepod at $0.080/hr, provided a quantized checkpoint exists for it.

Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.

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