Stable Diffusion 1 models

3 Stable Diffusion 1 models from Stability AI on Hugging Face, from 860M to 860M parameters, published by Stability AI in F32. The smallest official model, stable-diffusion-v1-4, needs about 3.8 GB of VRAM at its published precision; the cheapest live fit is V100 at $0.088/hr.

Part of the Stable Diffusion series · Next generation: Stable Diffusion 2

Pick a size

One row per official Stable Diffusion 1 size: the VRAM it needs at each precision, the cheapest GPU that holds it today, and the KV cache for a 32K-token context.

ModelParametersNative VRAMFP8 VRAMINT4 VRAMLive GPU fit (native)Est. $/hrKV cache at 32K
stable-diffusion-v1-4860M3.8 GB1.0 GB0.5 GBV100$0.088/hrnot published for this architecture

VRAM is weights times a flat 1.2 overhead; the KV cache is a separate per-model figure at 16-bit, shown where the architecture is published. See the methodology.

Official models (1)

ModelParametersPublished asVRAM neededLive GPU fitEst. $/hr
stable-diffusion-v1-4860MF323.8 GBV100$0.088/hr

Fine-tunes and community models (2)

ModelParametersPublished asVRAM neededLive GPU fitEst. $/hr
stable-diffusion-v1-5860MF323.8 GBV100$0.088/hr
stable-diffusion-v1-5860MF323.8 GBV100$0.088/hr

VRAM is for the precision the model is published in: the weights times a flat 1.2 overhead, with the KV cache not included. See the methodology. The fit shown is the lowest-priced single GPU type that holds the model at that precision, or the lowest-priced multi-GPU set (up to 8) when none does.

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