sd-cli — multi-arch stable-diffusion.cpp builds (incl. Blackwell)
Prebuilt sd-cli binaries from leejet/stable-diffusion.cpp,
plus the build recipe. Two CUDA variants, each a fat binary covering every NVIDIA
GPU architecture from its floor up through Blackwell.
Supported GPU architectures
| SM | Architecture | Example GPUs | cu12 | cu13 |
|---|---|---|---|---|
| sm_70 | Volta | Tesla V100, Titan V | yes | no |
| sm_75 | Turing | RTX 20-series, GTX 16-series, T4 | yes | yes |
| sm_80 | Ampere (DC) | A100, A30 | yes | yes |
| sm_86 | Ampere | RTX 30-series, A40, A10, A2000 | yes | yes |
| sm_89 | Ada Lovelace | RTX 40-series, L4, L40S | yes | yes |
| sm_90 | Hopper | H100, H200, GH200 | yes | yes |
| sm_100 | Blackwell (DC) | B100, B200, GB200 | yes | yes |
| sm_120 | Blackwell | RTX 50-series, RTX PRO 6000 Blackwell | yes | yes |
Both binaries also embed sm_120 PTX (virtual arch), so they JIT-forward onto future architectures. Use cu12 for older drivers / Volta; cu13 for CUDA-13 hosts (Volta was dropped upstream in CUDA 13).
Usage
Download from the Files tab (here) or Releases (GitHub). Dynamically
linked against the CUDA runtime (cudart/cublas/nccl) — same as upstream — so run
on a box where those libs are on the loader path (a PyTorch/CUDA image, or
pip install nvidia-cuda-runtime-cu12 nvidia-cublas-cu12 nvidia-nccl-cu12 +
LD_LIBRARY_PATH).
sd-cli-cu12 -m model.gguf -p "a lovely cat" -o out.png
Build it yourself via the included Dockerfiles + build-and-validate-sd-cli.sh.
License
Build recipe: MIT (see LICENSE). Binaries derive from stable-diffusion.cpp and ggml, both MIT — see NOTICE.