What GPU do I need to run nvidia/Cosmos3-Super-Text2Image-4Step?
64.0B parameters, published in BF16. View on Hugging Face
Cosmos3-Super-Text2Image-4Step is published by nvidia on Hugging Face, with 101,601 downloads and 13 likes to date. It's a Cosmos3ForConditionalGeneration model built for text-to-image, published natively in BF16.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for activation memory and allocator fragmentation. Diffusion and video models carry no KV-cache — the real driver of extra memory is output resolution and frame count, which this flat overhead does not model. Full formula and assumptions: methodology.
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 Cosmos3-Super-Text2Image-4Step at its published (BF16) precision: 6× RTX 3090 on simplepod, at $0.160/hr per GPU ($0.960/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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