What GPU do I need to run RunDiffusion/Juggernaut-Z-Image?
6.2B parameters, published in F16. View on Hugging Face
Set up Juggernaut-Z-ImageJuggernaut-Z-Image is published by RunDiffusion on Hugging Face, with 16,393 downloads and 129 likes to date. It's a unlisted-architecture model built for text-to-image, published natively in F16.
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.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| FP16 | 11.5 GB | 13.8 GB | V100 | 1 | $0.088/hr |
| FP8 (quantized) | 5.7 GB | 6.9 GB | RTX 5060 Ti | 1 | $0.110/hr |
| INT4 (quantized) | 2.9 GB | 3.4 GB | RTX 5060 Ti | 1 | $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 Juggernaut-Z-Image at its published (F16) precision: 1× V100, at $0.088/hr per GPU ($0.088/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Juggernaut-Z-Image: common questions
Does Juggernaut-Z-Image fit on a 16 GB GPU?
Yes. At FP16 it needs 13.8 GB of VRAM, so a 16 GB card holds it with 2.2 GB to spare. A 12 GB card is not enough for it at FP16.
What is the least VRAM Juggernaut-Z-Image can run in?
3.4 GB, at INT4 (quantized), which fits a 6 GB card, against 13.8 GB at FP16. That row assumes an INT4 checkpoint has actually been published for this model, so check its Hugging Face page before planning around it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
Related reading: V100 pricing and specs, and The best GPUs for AI, ranked.
