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.

PrecisionWeight sizeRequired VRAMCheapest live fitGPUs neededEst. $/hr (full fit)
BF1625.2 GB30.2 GBRTX 4080 Super1$0.338/hr
cheaper alt.RTX 5060 Ti2$0.220/hr
FP8 (quantized)12.6 GB15.1 GBRTX 5060 Ti1$0.110/hr
INT4 (quantized)6.3 GB7.5 GBRTX 5060 Ti1$0.110/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 Nemotron-Labs-Diffusion-14B at its published (BF16) precision: 1× RTX 4080 Super, at $0.338/hr per GPU ($0.338/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

Nemotron-Labs-Diffusion-14B: common questions

Does Nemotron-Labs-Diffusion-14B fit on a 32 GB GPU?

Yes. At BF16 it needs 30.2 GB of VRAM, so a 32 GB card holds it with 1.8 GB to spare. A 24 GB card is not enough for it at BF16.

What is the least VRAM Nemotron-Labs-Diffusion-14B can run in?

7.5 GB, at INT4 (quantized), which fits an 8 GB card, against 30.2 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 Nemotron-Labs-Diffusion-14B lower the GPU bill?

Yes. At BF16 the cheapest live fit is one RTX 4080 Super at $0.338/hr. At FP8 (quantized) it drops to one RTX 5060 Ti at $0.110/hr, provided a quantized checkpoint exists for it.

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

More Nemotron Labs models

All 4 Nemotron Labs models: VRAM and GPU requirements

Related reading: H100 pricing and specs, The best GPUs for AI, ranked, and Best GPU for LLM inference.

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