What GPU do I need to run inclusionAI/LLaDA2.0-mini?

16.3B parameters, published in BF16. View on Hugging Face

16.3B
Parameters
BF16
Native precision
LLaDA2MoeModelLM
Architecture
text-generation
Pipeline

LLaDA2.0-mini is published by inclusionAI on Hugging Face, with 223,275 downloads and 70 likes to date. It's a LLaDA2MoeModelLM 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)
BF1630.3 GB36.3 GBRTX A60001$0.363/hr
cheaper alt.RTX 5060 Ti3$0.330/hr
FP8 (quantized)15.1 GB18.2 GBRTX 4000 SFF Ada1$0.198/hr
INT4 (quantized)7.6 GB9.1 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 LLaDA2.0-mini at its published (BF16) precision: 1× RTX A6000, at $0.363/hr per GPU ($0.363/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

LLaDA2.0-mini: common questions

Can LLaDA2.0-mini run on a single GPU?

Yes, but not on a desktop card. At BF16 it needs 36.3 GB of VRAM, more than a single 32 GB desktop card holds. The cheapest live single-card fit is a 48.0 GB RTX A6000 at $0.363/hr.

What is the least VRAM LLaDA2.0-mini can run in?

9.1 GB, at INT4 (quantized), which fits a 12 GB card, against 36.3 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 LLaDA2.0-mini lower the GPU bill?

Yes. At BF16 the cheapest live fit is one RTX A6000 at $0.363/hr. At INT4 (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 LLaDA models

All 5 LLaDA models: VRAM and GPU requirements

Related reading: RTX A6000 pricing and specs, The NVIDIA Inception program, explained, Google Colab alternatives for dedicated GPU access, Free GPU credits for students and researchers, and RunPod volume disk vs. network volume, compared.

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