What GPU do I need to run stabilityai/sd-turbo?
866M parameters, published in F32. View on Hugging Face
sd-turbo is published by stabilityai on Hugging Face, with 579,648 downloads and 458 likes to date. It's a unlisted-architecture model built for text-to-image, published natively in F32.
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 sd-turbo at its published (F32) precision: 1× P4 on akash, at $0.032/hr per GPU ($0.032/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)
- stable-video-diffusion-img2vid-xt (1.5B, F32)
- stable-diffusion-3.5-medium (2.5B, BF16)
- stable-diffusion-3.5-large (8.1B, BF16)
- stable-diffusion-3-medium-diffusers (2.1B, F16)
