What GPU do I need to run nvidia/Nemotron-Labs-Diffusion-14B?

13.5B parameters, published in BF16. View on Hugging Face

13.5B
Parameters
BF16
Native precision
NemotronLabsDiffusionModel
Architecture
text-generation
Pipeline

Nemotron-Labs-Diffusion-14B is published by nvidia on Hugging Face, with 12,540 downloads and 154 likes to date. It's a NemotronLabsDiffusionModel 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
25.2 GB
30.2 GB
RTX 4080 Super (simplepod)
1
$0.380/hr
cheaper alt.
RTX 3070 (simplepod)
4
$0.200/hr
FP8 (quantized)
12.6 GB
15.1 GB
RTX 5060 Ti (simplepod)
1
$0.100/hr
INT4 (quantized)
6.3 GB
7.5 GB
RTX 3070 (simplepod)
1
$0.050/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 caveat: requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.

Cheapest way to run Nemotron-Labs-Diffusion-14B at its published (BF16) precision: 1× RTX 4080 Super on simplepod, at $0.380/hr per GPU ($0.380/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

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

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