What GPU do I need to run stabilityai/stable-diffusion-3.5-large?
8.1B parameters, published in BF16. View on Hugging FaceGated
stable-diffusion-3.5-large is published by stabilityai on Hugging Face, with 76,509 downloads and 3,716 likes to date. It's a unlisted-architecture model built for text-to-image, published natively in BF16, and gated — you'll need to accept the model's terms on Hugging Face before downloading weights.
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 stable-diffusion-3.5-large at its published (BF16) precision: 1× RTX 3090 on simplepod, at $0.160/hr per GPU ($0.160/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.
More stabilityai models
- stable-diffusion-xl-base-1.0 (2.6B, F32)
- sdxl-turbo (2.6B, F32)
- sd-turbo (866M, F32)
- stable-video-diffusion-img2vid-xt (1.5B, F32)
- stable-diffusion-3.5-medium (2.5B, BF16)
- stable-diffusion-3-medium-diffusers (2.1B, F16)
